Isolating gait-related movement artifacts in electroencephalography during human walking

PubMed Central

Kline, Julia E.; Huang, Helen J.; Snyder, Kristine L.; Ferris, Daniel P.

2016-01-01

Objective High-density electroencephelography (EEG) can provide insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. Approach We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4–1.6 m/s. We then tested artifact removal methods including moving average and wavelet-based techniques. Main Results Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Significance Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removing of EEG movement artifact to advance the field. PMID:26083595

Isolating gait-related movement artifacts in electroencephalography during human walking.

PubMed

Kline, Julia E; Huang, Helen J; Snyder, Kristine L; Ferris, Daniel P

2015-08-01

High-density electroencephelography (EEG) can provide an insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4 to 1.6 m s(-1). We then tested artifact removal methods including moving average and wavelet-based techniques. Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removal of EEG movement artifact to advance the field.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers

PubMed Central

Luu, Loc; Dinh, Anh

2018-01-01

The aim of this study is on the investigation of motion noise removal techniques using two-accelerometer sensor system and various placements of the sensors on gentle movement and walking of the patients. A Wi-Fi based data acquisition system and a framework on Matlab are developed to collect and process data while the subjects are in motion. The tests include eight volunteers who have no record of heart disease. The walking and running data on the subjects are analyzed to find the minimal-noise bandwidth of the SCG signal. This bandwidth is used to design filters in the motion noise removal techniques and peak signal detection. There are two main techniques of combining signals from the two sensors to mitigate the motion artifact: analog processing and digital processing. The analog processing comprises analog circuits performing adding or subtracting functions and bandpass filter to remove artifact noises before entering the data acquisition system. The digital processing processes all the data using combinations of total acceleration and z-axis only acceleration. The two techniques are tested on three placements of accelerometer sensors including horizontal, vertical, and diagonal on gentle motion and walking. In general, the total acceleration and z-axis acceleration are the best techniques to deal with gentle motion on all sensor placements which improve average systolic signal-noise-ratio (SNR) around 2 times and average diastolic SNR around 3 times comparing to traditional methods using only one accelerometer. With walking motion, ADDER and z-axis acceleration are the best techniques on all placements of the sensors on the body which enhance about 7 times of average systolic SNR and about 11 times of average diastolic SNR comparing to only one accelerometer method. Among the sensor placements, the performance of horizontal placement of the sensors is outstanding comparing with other positions on all motions. PMID:29614821

Five-dimensional motion compensation for respiratory and cardiac motion with cone-beam CT of the thorax region

NASA Astrophysics Data System (ADS)

Sauppe, Sebastian; Hahn, Andreas; Brehm, Marcus; Paysan, Pascal; Seghers, Dieter; Kachelrieß, Marc

2016-03-01

We propose an adapted method of our previously published five-dimensional (5D) motion compensation (MoCo) algorithm1, developed for micro-CT imaging of small animals, to provide for the first time motion artifact-free 5D cone-beam CT (CBCT) images from a conventional flat detector-based CBCT scan of clinical patients. Image quality of retrospectively respiratory- and cardiac-gated volumes from flat detector CBCT scans is deteriorated by severe sparse projection artifacts. These artifacts further complicate motion estimation, as it is required for MoCo image reconstruction. For high quality 5D CBCT images at the same x-ray dose and the same number of projections as todays 3D CBCT we developed a double MoCo approach based on motion vector fields (MVFs) for respiratory and cardiac motion. In a first step our already published four-dimensional (4D) artifact-specific cyclic motion-compensation (acMoCo) approach is applied to compensate for the respiratory patient motion. With this information a cyclic phase-gated deformable heart registration algorithm is applied to the respiratory motion-compensated 4D CBCT data, thus resulting in cardiac MVFs. We apply these MVFs on double-gated images and thereby respiratory and cardiac motion-compensated 5D CBCT images are obtained. Our 5D MoCo approach processing patient data acquired with the TrueBeam 4D CBCT system (Varian Medical Systems). Our double MoCo approach turned out to be very efficient and removed nearly all streak artifacts due to making use of 100% of the projection data for each reconstructed frame. The 5D MoCo patient data show fine details and no motion blurring, even in regions close to the heart where motion is fastest.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

PubMed

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Moving metal artifact reduction in cone-beam CT scans with implanted cylindrical gold markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toftegaard, Jakob, E-mail: jaktofte@rm.dk; Fledelius, Walther; Worm, Esben S.

2014-12-15

Purpose: Implanted gold markers for image-guided radiotherapy lead to streaking artifacts in cone-beam CT (CBCT) scans. Several methods for metal artifact reduction (MAR) have been published, but they all fail in scans with large motion. Here the authors propose and investigate a method for automatic moving metal artifact reduction (MMAR) in CBCT scans with cylindrical gold markers. Methods: The MMAR CBCT reconstruction method has six steps. (1) Automatic segmentation of the cylindrical markers in the CBCT projections. (2) Removal of each marker in the projections by replacing the pixels within a masked area with interpolated values. (3) Reconstruction of amore » marker-free CBCT volume from the manipulated CBCT projections. (4) Reconstruction of a standard CBCT volume with metal artifacts from the original CBCT projections. (5) Estimation of the three-dimensional (3D) trajectory during CBCT acquisition for each marker based on the segmentation in Step 1, and identification of the smallest ellipsoidal volume that encompasses 95% of the visited 3D positions. (6) Generation of the final MMAR CBCT reconstruction from the marker-free CBCT volume of Step 3 by replacing the voxels in the 95% ellipsoid with the corresponding voxels of the standard CBCT volume of Step 4. The MMAR reconstruction was performed retrospectively using a half-fan CBCT scan for 29 consecutive stereotactic body radiation therapy patients with 2–3 gold markers implanted in the liver. The metal artifacts of the MMAR reconstructions were scored and compared with a standard MAR reconstruction by counting the streaks and by calculating the standard deviation of the Hounsfield units in a region around each marker. Results: The markers were found with the same autosegmentation settings in 27 CBCT scans, while two scans needed slightly changed settings to find all markers automatically in Step 1 of the MMAR method. MMAR resulted in 15 scans with no streaking artifacts, 11 scans with 1–4 streaks, and 3 scans with severe streaking artifacts. The corresponding numbers for MAR were 8 (no streaks), 1 (1–4 streaks), and 20 (severe streaking artifacts). The MMAR method was superior to MAR in scans with more than 8 mm 3D marker motion and comparable to MAR for scans with less than 8 mm motion. In addition, the MMAR method was tested on a 4D CBCT reconstruction for which it worked equally well as for the 3D case. The markers in the 4D case had very low motion blur. Conclusions: An automatic method for MMAR in CBCT scans was proposed and shown to effectively remove almost all streaking artifacts in a large set of clinical CBCT scans with implanted gold markers in the liver. Residual streaking artifacts observed in three CBCT scans may be removed with better marker segmentation.« less

IMART software for correction of motion artifacts in images collected in intravital microscopy

PubMed Central

Dunn, Kenneth W; Lorenz, Kevin S; Salama, Paul; Delp, Edward J

2014-01-01

Intravital microscopy is a uniquely powerful tool, providing the ability to characterize cell and organ physiology in the natural context of the intact, living animal. With the recent development of high-resolution microscopy techniques such as confocal and multiphoton microscopy, intravital microscopy can now characterize structures at subcellular resolution and capture events at sub-second temporal resolution. However, realizing the potential for high resolution requires remarkable stability in the tissue. Whereas the rigid structure of the skull facilitates high-resolution imaging of the brain, organs of the viscera are free to move with respiration and heartbeat, requiring additional apparatus for immobilization. In our experience, these methods are variably effective, so that many studies are compromised by residual motion artifacts. Here we demonstrate the use of IMART, a software tool for removing motion artifacts from intravital microscopy images collected in time series or in three dimensions. PMID:26090271

Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Virtanen, Jaakko; Noponen, Tommi; Kotilahti, Kalle; Virtanen, Juha; Ilmoniemi, Risto J.

2011-08-01

In medical near-infrared spectroscopy (NIRS), movements of the subject often cause large step changes in the baselines of the measured light attenuation signals. This prevents comparison of hemoglobin concentration levels before and after movement. We present an accelerometer-based motion artifact removal (ABAMAR) algorithm for correcting such baseline motion artifacts (BMAs). ABAMAR can be easily adapted to various long-term monitoring applications of NIRS. We applied ABAMAR to NIRS data collected in 23 all-night sleep measurements and containing BMAs from involuntary movements during sleep. For reference, three NIRS researchers independently identified BMAs from the data. To determine whether the use of an accelerometer improves BMA detection accuracy, we compared ABAMAR to motion detection based on peaks in the moving standard deviation (SD) of NIRS data. The number of BMAs identified by ABAMAR was similar to the number detected by the humans, and 79% of the artifacts identified by ABAMAR were confirmed by at least two humans. While the moving SD of NIRS data could also be used for motion detection, on average 2 out of the 10 largest SD peaks in NIRS data each night occurred without the presence of movement. Thus, using an accelerometer improves BMA detection accuracy in NIRS.

Time-of-flight depth image enhancement using variable integration time

NASA Astrophysics Data System (ADS)

Kim, Sun Kwon; Choi, Ouk; Kang, Byongmin; Kim, James Dokyoon; Kim, Chang-Yeong

2013-03-01

Time-of-Flight (ToF) cameras are used for a variety of applications because it delivers depth information at a high frame rate. These cameras, however, suffer from challenging problems such as noise and motion artifacts. To increase signal-to-noise ratio (SNR), the camera should calculate a distance based on a large amount of infra-red light, which needs to be integrated over a long time. On the other hand, the integration time should be short enough to suppress motion artifacts. We propose a ToF depth imaging method to combine advantages of short and long integration times exploiting an imaging fusion scheme proposed for color imaging. To calibrate depth differences due to the change of integration times, a depth transfer function is estimated by analyzing the joint histogram of depths in the two images of different integration times. The depth images are then transformed into wavelet domains and fused into a depth image with suppressed noise and low motion artifacts. To evaluate the proposed method, we captured a moving bar of a metronome with different integration times. The experiment shows the proposed method could effectively remove the motion artifacts while preserving high SNR comparable to the depth images acquired during long integration time.

Coronary calcium visualization using dual energy chest radiography with sliding organ registration

NASA Astrophysics Data System (ADS)

Wen, Di; Nye, Katelyn; Zhou, Bo; Gilkeson, Robert C.; Wilson, David L.

2016-03-01

Coronary artery calcification (CAC) is the lead biomarker for atherosclerotic heart disease. We are developing a new technique to image CAC using ubiquitously ordered, low cost, low radiation dual energy (DE) chest radiography (using the two-shot GE Revolution XRd system). In this paper, we proposed a novel image processing method (CorCalDx) based on sliding organ registration to create a bone-image-like, coronary calcium image (CCI) that significantly reduces motion artifacts and improves CAC conspicuity. Experiments on images of a physical dynamic cardiac phantom showed that CorCalDx reduced 73% of the motion artifact area as compared to standard DE over a range of heart rates up to 90 bpm and varying x-ray radiation exposures. Residual motion artifact in the phantom CCI is greatly suppressed in gray level and area (0.88% of the heart area). In a Functional Measurement Test (FMT) with 20 clinical exams, image quality improvement of CorCalDx against standard DE (measured from -10 to +10) was significantly suggested (p<0.0001) by three radiologists for cardiac motion artifacts (7.2+/-2.1) and cardiac anatomy visibility (6.1+/-3.5). CorCalDx was always chosen best in every image tested. In preliminary assessments of 12 patients with 18 calcifications, 90% of motion artifact regions in standard DE results were removed in CorCalDx results, with 100% sensitivity of calcification detection, showing great potential of CorCalDx to improve CAC detection and grading in DE chest radiography.

Artifact detection in electrodermal activity using sparse recovery

NASA Astrophysics Data System (ADS)

Kelsey, Malia; Palumbo, Richard Vincent; Urbaneja, Alberto; Akcakaya, Murat; Huang, Jeannie; Kleckner, Ian R.; Barrett, Lisa Feldman; Quigley, Karen S.; Sejdic, Ervin; Goodwin, Matthew S.

2017-05-01

Electrodermal Activity (EDA) - a peripheral index of sympathetic nervous system activity - is a primary measure used in psychophysiology. EDA is widely accepted as an indicator of physiological arousal, and it has been shown to reveal when psychologically novel events occur. Traditionally, EDA data is collected in controlled laboratory experiments. However, recent developments in wireless biosensing have led to an increase in out-of-lab studies. This transition to ambulatory data collection has introduced challenges. In particular, artifacts such as wearer motion, changes in temperature, and electrical interference can be misidentified as true EDA responses. The inability to distinguish artifact from signal hinders analyses of ambulatory EDA data. Though manual procedures for identifying and removing EDA artifacts exist, they are time consuming - which is problematic for the types of longitudinal data sets represented in modern ambulatory studies. This manuscript presents a novel technique to automatically identify and remove artifacts in EDA data using curve fitting and sparse recovery methods. Our method was evaluated using labeled data to determine the accuracy of artifact identification. Procedures, results, conclusions, and future directions are presented.

The Zigbee wireless ECG measurement system design with a motion artifact remove algorithm by using adaptive filter and moving weighted factor

NASA Astrophysics Data System (ADS)

Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

2012-04-01

The Electrocardiogram(ECG) signal is one of the bio-signals to check body status. Traditionally, the ECG signal was checked in the hospital. In these days, as the number of people who is interesting with periodic their health check increase, the requirement of self-diagnosis system development is being increased as well. Ubiquitous concept is one of the solutions of the self-diagnosis system. Zigbee wireless sensor network concept is a suitable technology to satisfy the ubiquitous concept. In measuring ECG signal, there are several kinds of methods in attaching electrode on the body called as Lead I, II, III, etc. In addition, several noise components occurred by different measurement situation such as experimenter's respiration, sensor's contact point movement, and the wire movement attached on sensor are included in pure ECG signal. Therefore, this paper is based on the two kinds of development concept. The first is the Zibee wireless communication technology, which can provide convenience and simpleness, and the second is motion artifact remove algorithm, which can detect clear ECG signal from measurement subject. The motion artifact created by measurement subject's movement or even respiration action influences to distort ECG signal, and the frequency distribution of the noises is around from 0.2Hz to even 30Hz. The frequencies are duplicated in actual ECG signal frequency, so it is impossible to remove the artifact without any distortion of ECG signal just by using low-pass filter or high-pass filter. The suggested algorithm in this paper has two kinds of main parts to extract clear ECG signal from measured original signal through an electrode. The first part is to extract motion noise signal from measured signal, and the second part is to extract clear ECG by using extracted motion noise signal and measured original signal. The paper suggests several techniques in order to extract motion noise signal such as predictability estimation theory, low pass filter, a filter including a moving weighted factor, peak to peak detection, and interpolation techniques. In addition, this paper introduces an adaptive filter in order to extract clear ECG signal by using extracted baseline noise signal and measured signal from sensor.

Optical measurement of blood flow in exercising skeletal muscle: a pilot study

NASA Astrophysics Data System (ADS)

Wang, Detian; Baker, Wesley B.; Parthasarathy, Ashwin B.; Zhu, Liguo; Li, Zeren; Yodh, Arjun G.

2017-07-01

Blood flow monitoring during rhythm exercising is very important for sports medicine and muscle dieases. Diffuse correlation spectroscopy(DCS) is a relative new invasive way to monitor blood flow but suffering from muscle fiber motion. In this study we focus on how to remove exercise driven artifacts and obtain accurate estimates of the increase in blood flow from exercise. Using a novel fast software correlator, we measured blood flow in forearm flexor muscles of N=2 healthy adults during handgrip exercise, at a sampling rate of 20 Hz. Combining the blood flow and acceleration data, we resolved the motion artifact in the DCS signal induced by muscle fiber motion, and isolated the blood flow component of the signal from the motion artifact. The results show that muscle fiber motion strongly affects the DCS signal, and if not accounted for, will result in an overestimate of blood flow more than 1000%. Our measurements indicate rapid dilation of arterioles following exercise onset, which enabled blood flow to increase to a plateau of 200% in 10s. The blood flow also rapidly recovered to baseline following exercise in 10s. Finally, preliminary results on the dependence of blood flow from exercise intensity changes will be discussed.

Noise-immune complex correlation for vasculature imaging based on standard and Jones-matrix optical coherence tomography

NASA Astrophysics Data System (ADS)

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Li, En; Miura, Masahiro; Yasuno, Yoshiaki

2016-03-01

A new optical coherence angiography (OCA) method, called correlation mapping OCA (cmOCA), is presented by using the SNR-corrected complex correlation. An SNR-correction theory for the complex correlation calculation is presented. The method also integrates a motion-artifact-removal method for the sample motion induced decorrelation artifact. The theory is further extended to compute more reliable correlation by using multi- channel OCT systems, such as Jones-matrix OCT. The high contrast vasculature imaging of in vivo human posterior eye has been obtained. Composite imaging of cmOCA and degree of polarization uniformity indicates abnormalities of vasculature and pigmented tissues simultaneously.

Motion artifact removal algorithm by ICA for e-bra: a women ECG measurement system

NASA Astrophysics Data System (ADS)

Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

2013-04-01

Wearable ECG(ElectroCardioGram) measurement systems have increasingly been developing for people who suffer from CVD(CardioVascular Disease) and have very active lifestyles. Especially, in the case of female CVD patients, several abnormal CVD symptoms are accompanied with CVDs. Therefore, monitoring women's ECG signal is a significant diagnostic method to prevent from sudden heart attack. The E-bra ECG measurement system from our previous work provides more convenient option for women than Holter monitor system. The e-bra system was developed with a motion artifact removal algorithm by using an adaptive filter with LMS(least mean square) and a wandering noise baseline detection algorithm. In this paper, ICA(independent component analysis) algorithms are suggested to remove motion artifact factor for the e-bra system. Firstly, the ICA algorithms are developed with two kinds of statistical theories: Kurtosis, Endropy and evaluated by performing simulations with a ECG signal created by sgolayfilt function of MATLAB, a noise signal including 0.4Hz, 1.1Hz and 1.9Hz, and a weighed vector W estimated by kurtosis or entropy. A correlation value is shown as the degree of similarity between the created ECG signal and the estimated new ECG signal. In the real time E-Bra system, two pseudo signals are extracted by multiplying with a random weighted vector W, the measured ECG signal from E-bra system, and the noise component signal by noise extraction algorithm from our previous work. The suggested ICA algorithm basing on kurtosis or entropy is used to estimate the new ECG signal Y without noise component.

Impact of image quality on OCT angiography based quantitative measurements.

PubMed

Al-Sheikh, Mayss; Ghasemi Falavarjani, Khalil; Akil, Handan; Sadda, SriniVas R

2017-01-01

To study the impact of image quality on quantitative measurements and the frequency of segmentation error with optical coherence tomography angiography (OCTA). Seventeen eyes of 10 healthy individuals were included in this study. OCTA was performed using a swept-source device (Triton, Topcon). Each subject underwent three scanning sessions 1-2 min apart; the first two scans were obtained under standard conditions and for the third session, the image quality index was reduced using application of a topical ointment. En face OCTA images of the retinal vasculature were generated using the default segmentation for the superficial and deep retinal layer (SRL, DRL). Intraclass correlation coefficient (ICC) was used as a measure for repeatability. The frequency of segmentation error, motion artifact, banding artifact and projection artifact was also compared among the three sessions. The frequency of segmentation error, and motion artifact was statistically similar between high and low image quality sessions (P = 0.707, and P = 1 respectively). However, the frequency of projection and banding artifact was higher with a lower image quality. The vessel density in the SRL was highly repeatable in the high image quality sessions (ICC = 0.8), however, the repeatability was low, comparing the high and low image quality measurements (ICC = 0.3). In the DRL, the repeatability of the vessel density measurements was fair in the high quality sessions (ICC = 0.6 and ICC = 0.5, with and without automatic artifact removal, respectively) and poor comparing high and low image quality sessions (ICC = 0.3 and ICC = 0.06, with and without automatic artifact removal, respectively). The frequency of artifacts is higher and the repeatability of the measurements is lower with lower image quality. The impact of image quality index should be always considered in OCTA based quantitative measurements.

Effect of pressure and padding on motion artifact of textile electrodes.

PubMed

Cömert, Alper; Honkala, Markku; Hyttinen, Jari

2013-04-08

With the aging population and rising healthcare costs, wearable monitoring is gaining importance. The motion artifact affecting dry electrodes is one of the main challenges preventing the widespread use of wearable monitoring systems. In this paper we investigate the motion artifact and ways of making a textile electrode more resilient against motion artifact. Our aim is to study the effects of the pressure exerted onto the electrode, and the effects of inserting padding between the applied pressure and the electrode. We measure real time electrode-skin interface impedance, ECG from two channels, the motion artifact related surface potential, and exerted pressure during controlled motion by a measurement setup designed to estimate the relation of motion artifact to the signals. We use different foam padding materials with various mechanical properties and apply electrode pressures between 5 and 25 mmHg to understand their effect. A QRS and noise detection algorithm based on a modified Pan-Tompkins QRS detection algorithm estimates the electrode behaviour in respect to the motion artifact from two channels; one dominated by the motion artifact and one containing both the motion artifact and the ECG. This procedure enables us to quantify a given setup's susceptibility to the motion artifact. Pressure is found to strongly affect signal quality as is the use of padding. In general, the paddings reduce the motion artifact. However the shape and frequency components of the motion artifact vary for different paddings, and their material and physical properties. Electrode impedance at 100 kHz correlates in some cases with the motion artifact but it is not a good predictor of the motion artifact. From the results of this study, guidelines for improving electrode design regarding padding and pressure can be formulated as paddings are a necessary part of the system for reducing the motion artifact, and further, their effect maximises between 15 mmHg and 20 mmHg of exerted pressure. In addition, we present new methods for evaluating electrode sensitivity to motion, utilizing the detection of noise peaks that fall into the same frequency band as R-peaks.

Real-time motion analytics during brain MRI improve data quality and reduce costs.

PubMed

Dosenbach, Nico U F; Koller, Jonathan M; Earl, Eric A; Miranda-Dominguez, Oscar; Klein, Rachel L; Van, Andrew N; Snyder, Abraham Z; Nagel, Bonnie J; Nigg, Joel T; Nguyen, Annie L; Wesevich, Victoria; Greene, Deanna J; Fair, Damien A

2017-11-01

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

Motion vector field upsampling for improved 4D cone-beam CT motion compensation of the thorax

NASA Astrophysics Data System (ADS)

Sauppe, Sebastian; Rank, Christopher M.; Brehm, Marcus; Paysan, Pascal; Seghers, Dieter; Kachelrieß, Marc

2017-03-01

To improve the accuracy of motion vector fields (MVFs) required for respiratory motion compensated (MoCo) CT image reconstruction without increasing the computational complexity of the MVF estimation approach, we propose a MVF upsampling method that is able to reduce the motion blurring in reconstructed 4D images. While respiratory gating improves the temporal resolution, it leads to sparse view sampling artifacts. MoCo image reconstruction has the potential to remove all motion artifacts while simultaneously making use of 100% of the rawdata. However the MVF accuracy is still below the temporal resolution of the CBCT data acquisition. Increasing the number of motion bins would increase reconstruction time and amplify sparse view artifacts, but not necessarily the accuracy of MVF. Therefore we propose a new method to upsample estimated MVFs and use those for MoCo. To estimate the MVFs, a modified version of the Demons algorithm is used. Our proposed method is able to interpolate the original MVFs up to a factor that each projection has its own individual MVF. To validate the method we use an artificially deformed clinical CT scan, with a breathing pattern of a real patient, and patient data acquired with a TrueBeamTM4D CBCT system (Varian Medical Systems). We evaluate our method for different numbers of respiratory bins, each again with different upsampling factors. Employing our upsampling method, motion blurring in the reconstructed 4D images, induced by irregular breathing and the limited temporal resolution of phase-correlated images, is substantially reduced.

Denoising the Speaking Brain: Toward a Robust Technique for Correcting Artifact-Contaminated fMRI Data under Severe Motion

PubMed Central

Xu, Yisheng; Tong, Yunxia; Liu, Siyuan; Chow, Ho Ming; AbdulSabur, Nuria Y.; Mattay, Govind S.; Braun, Allen R.

2014-01-01

A comprehensive set of methods based on spatial independent component analysis (sICA) is presented as a robust technique for artifact removal, applicable to a broad range of functional magnetic resonance imaging (fMRI) experiments that have been plagued by motion-related artifacts. Although the applications of sICA for fMRI denoising have been studied previously, three fundamental elements of this approach have not been established as follows: 1) a mechanistically-based ground truth for component classification; 2) a general framework for evaluating the performance and generalizability of automated classifiers; 3) a reliable method for validating the effectiveness of denoising. Here we perform a thorough investigation of these issues and demonstrate the power of our technique by resolving the problem of severe imaging artifacts associated with continuous overt speech production. As a key methodological feature, a dual-mask sICA method is proposed to isolate a variety of imaging artifacts by directly revealing their extracerebral spatial origins. It also plays an important role for understanding the mechanistic properties of noise components in conjunction with temporal measures of physical or physiological motion. The potentials of a spatially-based machine learning classifier and the general criteria for feature selection have both been examined, in order to maximize the performance and generalizability of automated component classification. The effectiveness of denoising is quantitatively validated by comparing the activation maps of fMRI with those of positron emission tomography acquired under the same task conditions. The general applicability of this technique is further demonstrated by the successful reduction of distance-dependent effect of head motion on resting-state functional connectivity. PMID:25225001

Denoising the speaking brain: toward a robust technique for correcting artifact-contaminated fMRI data under severe motion.

PubMed

Xu, Yisheng; Tong, Yunxia; Liu, Siyuan; Chow, Ho Ming; AbdulSabur, Nuria Y; Mattay, Govind S; Braun, Allen R

2014-12-01

A comprehensive set of methods based on spatial independent component analysis (sICA) is presented as a robust technique for artifact removal, applicable to a broad range of functional magnetic resonance imaging (fMRI) experiments that have been plagued by motion-related artifacts. Although the applications of sICA for fMRI denoising have been studied previously, three fundamental elements of this approach have not been established as follows: 1) a mechanistically-based ground truth for component classification; 2) a general framework for evaluating the performance and generalizability of automated classifiers; and 3) a reliable method for validating the effectiveness of denoising. Here we perform a thorough investigation of these issues and demonstrate the power of our technique by resolving the problem of severe imaging artifacts associated with continuous overt speech production. As a key methodological feature, a dual-mask sICA method is proposed to isolate a variety of imaging artifacts by directly revealing their extracerebral spatial origins. It also plays an important role for understanding the mechanistic properties of noise components in conjunction with temporal measures of physical or physiological motion. The potentials of a spatially-based machine learning classifier and the general criteria for feature selection have both been examined, in order to maximize the performance and generalizability of automated component classification. The effectiveness of denoising is quantitatively validated by comparing the activation maps of fMRI with those of positron emission tomography acquired under the same task conditions. The general applicability of this technique is further demonstrated by the successful reduction of distance-dependent effect of head motion on resting-state functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

NASA Astrophysics Data System (ADS)

Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

2016-04-01

Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects, totaling 19 sessions, with and without {H}∞ filtering of the raw data. Significance. The proposed method allows real-time adaptive artifact removal for EEG-based closed-loop BMI applications and mobile EEG studies in general, thereby increasing the range of tasks that can be studied in action and context while reducing the need for discarding data due to artifacts. Significant increase in decoding performances also justify the effectiveness of the method to be used in real-time closed-loop BMI applications.

Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares.

PubMed

Zhou, Zhenyu; Liu, Wei; Cui, Jiali; Wang, Xunheng; Arias, Diana; Wen, Ying; Bansal, Ravi; Hao, Xuejun; Wang, Zhishun; Peterson, Bradley S; Xu, Dongrong

2011-02-01

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model. Copyright © 2011 Elsevier Inc. All rights reserved.

Multi-Shot Sensitivity-Encoded Diffusion Data Recovery Using Structured Low-Rank Matrix Completion (MUSSELS)

PubMed Central

Mani, Merry; Jacob, Mathews; Kelley, Douglas; Magnotta, Vincent

2017-01-01

Purpose To introduce a novel method for the recovery of multi-shot diffusion weighted (MS-DW) images from echo-planar imaging (EPI) acquisitions. Methods Current EPI-based MS-DW reconstruction methods rely on the explicit estimation of the motion-induced phase maps to recover artifact-free images. In the new formulation, the k-space data of the artifact-free DWI is recovered using a structured low-rank matrix completion scheme, which does not require explicit estimation of the phase maps. The structured matrix is obtained as the lifting of the multi-shot data. The smooth phase-modulations between shots manifest as null-space vectors of this matrix, which implies that the structured matrix is low-rank. The missing entries of the structured matrix are filled in using a nuclear-norm minimization algorithm subject to the data-consistency. The formulation enables the natural introduction of smoothness regularization, thus enabling implicit motion-compensated recovery of the MS-DW data. Results Our experiments on in-vivo data show effective removal of artifacts arising from inter-shot motion using the proposed method. The method is shown to achieve better reconstruction than the conventional phase-based methods. Conclusion We demonstrate the utility of the proposed method to effectively recover artifact-free images from Cartesian fully/under-sampled and partial Fourier acquired data without the use of explicit phase estimates. PMID:27550212

Iterative Covariance-based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings

PubMed Central

Putney, Joy; Hilbert, Douglas; Paskaranandavadivel, Niranchan; Cheng, Leo K.; O'Grady, Greg; Angeli, Timothy R.

2016-01-01

Objective The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation. Methods A novel iterative COvaraiance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance. Results Application of COBRA substantially increased the signal-to-artifact ratio (12.8±2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average (-11.1±3.9 dB). Conclusion COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90±0.04; positive-predictive value = 0.74±0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms. Significance Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains. PMID:26829772

Evaluation of motion artifact metrics for coronary CT angiography.

PubMed

Ma, Hongfeng; Gros, Eric; Szabo, Aniko; Baginski, Scott G; Laste, Zachary R; Kulkarni, Naveen M; Okerlund, Darin; Schmidt, Taly G

2018-02-01

This study quantified the performance of coronary artery motion artifact metrics relative to human observer ratings. Motion artifact metrics have been used as part of motion correction and best-phase selection algorithms for Coronary Computed Tomography Angiography (CCTA). However, the lack of ground truth makes it difficult to validate how well the metrics quantify the level of motion artifact. This study investigated five motion artifact metrics, including two novel metrics, using a dynamic phantom, clinical CCTA images, and an observer study that provided ground-truth motion artifact scores from a series of pairwise comparisons. Five motion artifact metrics were calculated for the coronary artery regions on both phantom and clinical CCTA images: positivity, entropy, normalized circularity, Fold Overlap Ratio (FOR), and Low-Intensity Region Score (LIRS). CT images were acquired of a dynamic cardiac phantom that simulated cardiac motion and contained six iodine-filled vessels of varying diameter and with regions of soft plaque and calcifications. Scans were repeated with different gantry start angles. Images were reconstructed at five phases of the motion cycle. Clinical images were acquired from 14 CCTA exams with patient heart rates ranging from 52 to 82 bpm. The vessel and shading artifacts were manually segmented by three readers and combined to create ground-truth artifact regions. Motion artifact levels were also assessed by readers using a pairwise comparison method to establish a ground-truth reader score. The Kendall's Tau coefficients were calculated to evaluate the statistical agreement in ranking between the motion artifacts metrics and reader scores. Linear regression between the reader scores and the metrics was also performed. On phantom images, the Kendall's Tau coefficients of the five motion artifact metrics were 0.50 (normalized circularity), 0.35 (entropy), 0.82 (positivity), 0.77 (FOR), 0.77(LIRS), where higher Kendall's Tau signifies higher agreement. The FOR, LIRS, and transformed positivity (the fourth root of the positivity) were further evaluated in the study of clinical images. The Kendall's Tau coefficients of the selected metrics were 0.59 (FOR), 0.53 (LIRS), and 0.21 (Transformed positivity). In the study of clinical data, a Motion Artifact Score, defined as the product of FOR and LIRS metrics, further improved agreement with reader scores, with a Kendall's Tau coefficient of 0.65. The metrics of FOR, LIRS, and the product of the two metrics provided the highest agreement in motion artifact ranking when compared to the readers, and the highest linear correlation to the reader scores. The validated motion artifact metrics may be useful for developing and evaluating methods to reduce motion in Coronary Computed Tomography Angiography (CCTA) images. © 2017 American Association of Physicists in Medicine.

Investigating the possible effect of electrode support structure on motion artifact in wearable bioelectric signal monitoring.

PubMed

Cömert, Alper; Hyttinen, Jari

2015-05-15

With advances in technology and increasing demand, wearable biosignal monitoring is developing and new applications are emerging. One of the main challenges facing the widespread use of wearable monitoring systems is the motion artifact. The sources of the motion artifact lie in the skin-electrode interface. Reducing the motion and deformation at this interface should have positive effects on signal quality. In this study, we aim to investigate whether the structure supporting the electrode can be designed to reduce the motion artifact with the hypothesis that this can be achieved by stabilizing the skin deformations around the electrode. We compare four textile electrodes with different support structure designs: a soft padding larger than the electrode area, a soft padding larger than the electrode area with a novel skin deformation restricting design, a soft padding the same size as the electrode area, and a rigid support the same size as the electrode. With five subjects and two electrode locations placed over different kinds of tissue at various mounting forces, we simultaneously measured the motion artifact, a motion affected ECG, and the real-time skin-electrode impedance during the application of controlled motion to the electrodes. The design of the electrode support structure has an effect on the generated motion artifact; good design with a skin stabilizing structure makes the electrodes physically more motion artifact resilient, directly affecting signal quality. Increasing the applied mounting force shows a positive effect up to 1,000 gr applied force. The properties of tissue under the electrode are an important factor in the generation of the motion artifact and the functioning of the electrodes. The relationship of motion artifact amplitude to the electrode movement magnitude is seen to be linear for smaller movements. For larger movements, the increase of motion generated a disproportionally larger artifact. The motion artifact and the induced impedance change were caused by the electrode motion and contained the same frequency components as the applied electrode motion pattern. We found that stabilizing the skin around the electrode using an electrode structure that manages to successfully distribute the force and movement to an area beyond the borders of the electrical contact area reduces the motion artifact when compared to structures that are the same size as the electrode area.

Photoplethysmograph signal reconstruction based on a novel hybrid motion artifact detection-reduction approach. Part I: Motion and noise artifact detection.

PubMed

Chong, Jo Woon; Dao, Duy K; Salehizadeh, S M A; McManus, David D; Darling, Chad E; Chon, Ki H; Mendelson, Yitzhak

2014-11-01

Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment. For motion artifact detection, we compute four time-domain parameters: (1) standard deviation of peak-to-peak intervals (2) standard deviation of peak-to-peak amplitudes (3) standard deviation of systolic and diastolic interval ratios, and (4) mean standard deviation of pulse shape. We have adopted a support vector machine (SVM) which takes these parameters from clean and corrupted PPG signals and builds a decision boundary to classify them. We apply several distinct features of the PPG data to enhance classification performance. The algorithm we developed was verified on PPG data segments recorded by simulation, laboratory-controlled and walking/stair-climbing experiments, respectively, and we compared several well-established MNA detection methods to our proposed algorithm. All compared detection algorithms were evaluated in terms of motion artifact detection accuracy, heart rate (HR) error, and oxygen saturation (SpO2) error. For laboratory controlled finger, forehead recorded PPG data and daily-activity movement data, our proposed algorithm gives 94.4, 93.4, and 93.7% accuracies, respectively. Significant reductions in HR and SpO2 errors (2.3 bpm and 2.7%) were noted when the artifacts that were identified by SVM-MNA were removed from the original signal than without (17.3 bpm and 5.4%). The accuracy and error values of our proposed method were significantly higher and lower, respectively, than all other detection methods. Another advantage of our method is its ability to provide highly accurate onset and offset detection times of MNAs. This capability is important for an automated approach to signal reconstruction of only those data points that need to be reconstructed, which is the subject of the companion paper to this article. Finally, our MNA detection algorithm is real-time realizable as the computational speed on the 7-s PPG data segment was found to be only 7 ms with a Matlab code.

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

PubMed Central

YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

GPU accelerated optical coherence tomography angiography using strip-based registration (Conference Presentation)

NASA Astrophysics Data System (ADS)

Heisler, Morgan; Lee, Sieun; Mammo, Zaid; Jian, Yifan; Ju, Myeong Jin; Miao, Dongkai; Raposo, Eric; Wahl, Daniel J.; Merkur, Andrew; Navajas, Eduardo; Balaratnasingam, Chandrakumar; Beg, Mirza Faisal; Sarunic, Marinko V.

2017-02-01

High quality visualization of the retinal microvasculature can improve our understanding of the onset and development of retinal vascular diseases, which are a major cause of visual morbidity and are increasing in prevalence. Optical Coherence Tomography Angiography (OCT-A) images are acquired over multiple seconds and are particularly susceptible to motion artifacts, which are more prevalent when imaging patients with pathology whose ability to fixate is limited. The acquisition of multiple OCT-A images sequentially can be performed for the purpose of removing motion artifact and increasing the contrast of the vascular network through averaging. Due to the motion artifacts, a robust registration pipeline is needed before feature preserving image averaging can be performed. In this report, we present a novel method for a GPU-accelerated pipeline for acquisition, processing, segmentation, and registration of multiple, sequentially acquired OCT-A images to correct for the motion artifacts in individual images for the purpose of averaging. High performance computing, blending CPU and GPU, was introduced to accelerate processing in order to provide high quality visualization of the retinal microvasculature and to enable a more accurate quantitative analysis in a clinically useful time frame. Specifically, image discontinuities caused by rapid micro-saccadic movements and image warping due to smoother reflex movements were corrected by strip-wise affine registration estimated using Scale Invariant Feature Transform (SIFT) keypoints and subsequent local similarity-based non-rigid registration. These techniques improve the image quality, increasing the value for clinical diagnosis and increasing the range of patients for whom high quality OCT-A images can be acquired.

Motion artifact detection and correction in functional near-infrared spectroscopy: a new hybrid method based on spline interpolation method and Savitzky-Golay filtering.

PubMed

Jahani, Sahar; Setarehdan, Seyed K; Boas, David A; Yücel, Meryem A

2018-01-01

Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important challenge in realizing the full potential of NIRS for real-life applications. Various motion correction algorithms have been used to alleviate the effect of motion artifacts on the estimation of the hemodynamic response function. While smoothing methods, such as wavelet filtering, are excellent in removing motion-induced sharp spikes, the baseline shifts in the signal remain after this type of filtering. Methods, such as spline interpolation, on the other hand, can properly correct baseline shifts; however, they leave residual high-frequency spikes. We propose a hybrid method that takes advantage of different correction algorithms. This method first identifies the baseline shifts and corrects them using a spline interpolation method or targeted principal component analysis. The remaining spikes, on the other hand, are corrected by smoothing methods: Savitzky-Golay (SG) filtering or robust locally weighted regression and smoothing. We have compared our new approach with the existing correction algorithms in terms of hemodynamic response function estimation using the following metrics: mean-squared error, peak-to-peak error ([Formula: see text]), Pearson's correlation ([Formula: see text]), and the area under the receiver operator characteristic curve. We found that spline-SG hybrid method provides reasonable improvements in all these metrics with a relatively short computational time. The dataset and the code used in this study are made available online for the use of all interested researchers.

A novel fast helical 4D-CT acquisition technique to generate low-noise sorting artifact-free images at user-selected breathing phases.

PubMed

Thomas, David; Lamb, James; White, Benjamin; Jani, Shyam; Gaudio, Sergio; Lee, Percy; Ruan, Dan; McNitt-Gray, Michael; Low, Daniel

2014-05-01

To develop a novel 4-dimensional computed tomography (4D-CT) technique that exploits standard fast helical acquisition, a simultaneous breathing surrogate measurement, deformable image registration, and a breathing motion model to remove sorting artifacts. Ten patients were imaged under free-breathing conditions 25 successive times in alternating directions with a 64-slice CT scanner using a low-dose fast helical protocol. An abdominal bellows was used as a breathing surrogate. Deformable registration was used to register the first image (defined as the reference image) to the subsequent 24 segmented images. Voxel-specific motion model parameters were determined using a breathing motion model. The tissue locations predicted by the motion model in the 25 images were compared against the deformably registered tissue locations, allowing a model prediction error to be evaluated. A low-noise image was created by averaging the 25 images deformed to the first image geometry, reducing statistical image noise by a factor of 5. The motion model was used to deform the low-noise reference image to any user-selected breathing phase. A voxel-specific correction was applied to correct the Hounsfield units for lung parenchyma density as a function of lung air filling. Images produced using the model at user-selected breathing phases did not suffer from sorting artifacts common to conventional 4D-CT protocols. The mean prediction error across all patients between the breathing motion model predictions and the measured lung tissue positions was determined to be 1.19 ± 0.37 mm. The proposed technique can be used as a clinical 4D-CT technique. It is robust in the presence of irregular breathing and allows the entire imaging dose to contribute to the resulting image quality, providing sorting artifact-free images at a patient dose similar to or less than current 4D-CT techniques. Copyright © 2014 Elsevier Inc. All rights reserved.

Sources and implications of whole-brain fMRI signals in humans

PubMed Central

Power, Jonathan D; Plitt, Mark; Laumann, Timothy O; Martin, Alex

2016-01-01

Whole-brain fMRI signals are a subject of intense interest: variance in the global fMRI signal (the spatial mean of all signals in the brain) indexes subject arousal, and psychiatric conditions such as schizophrenia and autism have been characterized by differences in the global fMRI signal. Further, vigorous debates exist on whether global signals ought to be removed from fMRI data. However, surprisingly little research has focused on the empirical properties of whole-brain fMRI signals. Here we map the spatial and temporal properties of the global signal, individually, in 1000+ fMRI scans. Variance in the global fMRI signal is strongly linked to head motion, to hardware artifacts, and to respiratory patterns and their attendant physiologic changes. Many techniques used to prepare fMRI data for analysis fail to remove these uninteresting kinds of global signal fluctuations. Thus, many studies include, at the time of analysis, prominent global effects of yawns, breathing changes, and head motion, among other signals. Such artifacts will mimic dynamic neural activity and will spuriously alter signal covariance throughout the brain. Methods capable of isolating and removing global artifactual variance while preserving putative “neural” variance are needed; this paper adopts no position on the topic of global signal regression. PMID:27751941

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Detection of Mental State and Reduction of Artifacts Using Functional Near Infrared Spectroscopy (FNIRS)

NASA Technical Reports Server (NTRS)

Harrivel, Angela (Inventor); Hearn, Tristan (Inventor)

2017-01-01

fNIRS may be used in real time or near-real time to detect the mental state of individuals. Phase measurement can be applied to drive an adaptive filter for the removal of motion artifacts in real time or near-real time. In this manner, the application of fNIRS may be extended to practical non-laboratory environments. For example, the mental state of an operator of a vehicle may be monitored, and alerts may be issued and/or an autopilot may be engaged when the mental state of the operator indicates that the operator is inattentive.

Reduction of display artifacts by random sampling

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.; Nagel, D. C.; Watson, A. B.; Yellott, J. I., Jr.

1983-01-01

The application of random-sampling techniques to remove visible artifacts (such as flicker, moire patterns, and paradoxical motion) introduced in TV-type displays by discrete sequential scanning is discussed and demonstrated. Sequential-scanning artifacts are described; the window of visibility defined in spatiotemporal frequency space by Watson and Ahumada (1982 and 1983) and Watson et al. (1983) is explained; the basic principles of random sampling are reviewed and illustrated by the case of the human retina; and it is proposed that the sampling artifacts can be replaced by random noise, which can then be shifted to frequency-space regions outside the window of visibility. Vertical sequential, single-random-sequence, and continuously renewed random-sequence plotting displays generating 128 points at update rates up to 130 Hz are applied to images of stationary and moving lines, and best results are obtained with the single random sequence for the stationary lines and with the renewed random sequence for the moving lines.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

PubMed

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-07-07

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

PubMed Central

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-01-01

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method. PMID:26198231

[Joint correction for motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging].

PubMed

Wu, Wenchuan; Fang, Sheng; Guo, Hua

2014-06-01

Aiming at motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging (MRI), we proposed a joint correction method in this paper to correct the two kinds of artifacts simultaneously without additional acquisition of navigation data and field map. We utilized the proposed method using multi-shot variable density spiral sequence to acquire MRI data and used auto-focusing technique for image deblurring. We also used direct method or iterative method to correct motion induced phase errors in the process of deblurring. In vivo MRI experiments demonstrated that the proposed method could effectively suppress motion artifacts and off-resonance artifacts and achieve images with fine structures. In addition, the scan time was not increased in applying the proposed method.

Motion artifact detection in four-dimensional computed tomography images

NASA Astrophysics Data System (ADS)

Bouilhol, G.; Ayadi, M.; Pinho, R.; Rit, S.; Sarrut, D.

2014-03-01

Motion artifacts appear in four-dimensional computed tomography (4DCT) images because of suboptimal acquisition parameters or patient breathing irregularities. Frequency of motion artifacts is high and they may introduce errors in radiation therapy treatment planning. Motion artifact detection can be useful for image quality assessment and 4D reconstruction improvement but manual detection in many images is a tedious process. We propose a novel method to evaluate the quality of 4DCT images by automatic detection of motion artifacts. The method was used to evaluate the impact of the optimization of acquisition parameters on image quality at our institute. 4DCT images of 114 lung cancer patients were analyzed. Acquisitions were performed with a rotation period of 0.5 seconds and a pitch of 0.1 (74 patients) or 0.081 (40 patients). A sensitivity of 0.70 and a specificity of 0.97 were observed. End-exhale phases were less prone to motion artifacts. In phases where motion speed is high, the number of detected artifacts was systematically reduced with a pitch of 0.081 instead of 0.1 and the mean reduction was 0.79. The increase of the number of patients with no artifact detected was statistically significant for the 10%, 70% and 80% respiratory phases, indicating a substantial image quality improvement.

Reduction of respiratory ghosting motion artifacts in conventional two-dimensional multi-slice Cartesian turbo spin-echo: which k-space filling order is the best?

PubMed

Inoue, Yuuji; Yoneyama, Masami; Nakamura, Masanobu; Takemura, Atsushi

2018-06-01

The two-dimensional Cartesian turbo spin-echo (TSE) sequence is widely used in routine clinical studies, but it is sensitive to respiratory motion. We investigated the k-space orders in Cartesian TSE that can effectively reduce motion artifacts. The purpose of this study was to demonstrate the relationship between k-space order and degree of motion artifacts using a moving phantom. We compared the degree of motion artifacts between linear and asymmetric k-space orders. The actual spacing of ghost artifacts in the asymmetric order was doubled compared with that in the linear order in the free-breathing situation. The asymmetric order clearly showed less sensitivity to incomplete breath-hold at the latter half of the imaging period. Because of the actual number of partitions of the k-space and the temporal filling order, the asymmetric k-space order of Cartesian TSE was superior to the linear k-space order for reduction of ghosting motion artifacts.

POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): a general algorithm for reducing motion-related artifacts

PubMed Central

Chu, Mei-Lan; Chang, Hing-Chiu; Chung, Hsiao-Wen; Truong, Trong-Kha; Bashir, Mustafa R.; Chen, Nan-kuei

2014-01-01

Purpose A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion weighted imaging (DWI). Theory Images with reduced artifacts are reconstructed with an iterative POCS procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. Methods The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved DWI data corresponding to different k-space trajectories and matrix condition numbers. Results Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. Conclusion POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods. PMID:25394325

High Efficiency, Low Distortion 3D Diffusion Tensor Imaging with Variable Density Spiral Fast Spin Echoes (3D DW VDS RARE)

PubMed Central

Frank, Lawrence R.; Jung, Youngkyoo; Inati, Souheil; Tyszka, J. Michael; Wong, Eric C.

2009-01-01

We present an acquisition and reconstruction method designed to acquire high resolution 3D fast spin echo diffusion tensor images while mitigating the major sources of artifacts in DTI - field distortions, eddy currents and motion. The resulting images, being 3D, are of high SNR, and being fast spin echoes, exhibit greatly reduced field distortions. This sequence utilizes variable density spiral acquisition gradients, which allow for the implementation of a self-navigation scheme by which both eddy current and motion artifacts are removed. The result is that high resolution 3D DTI images are produced without the need for eddy current compensating gradients or B0 field correction. In addition, a novel method for fast and accurate reconstruction of the non-Cartesian data is employed. Results are demonstrated in the brains of normal human volunteers. PMID:19778618

Motion artifacts in MRI: A complex problem with many partial solutions.

PubMed

Zaitsev, Maxim; Maclaren, Julian; Herbst, Michael

2015-10-01

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations. © 2015 Wiley Periodicals, Inc.

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion.

PubMed

Symeonidou, Evangelia-Regkina; Nordin, Andrew D; Hairston, W David; Ferris, Daniel P

2018-04-03

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0-2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG.

A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging

PubMed Central

Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X.; Wan, Mingxi

2014-01-01

Purpose The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). Materials and methods The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). Results The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). Conclusion The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements. PMID:24727862

A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.

PubMed

Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X; Wan, Mingxi

2014-01-01

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Brain-Computer Interfaces for 1-D and 2-D Cursor Control: Designs Using Volitional Control of the EEG Spectrum or Steady-State Visual Evoked Potentials

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Matthews, Bryan; Rosipal, Roman

2005-01-01

We have developed and tested two EEG-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KF LS classifier to map power spectra of 30-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject s average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: a) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal EOG signals, b) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from eight electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about three minutes. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 seconds for movement initiation and turning.

[Affine transformation-based automatic registration for peripheral digital subtraction angiography (DSA)].

PubMed

Kong, Gang; Dai, Dao-Qing; Zou, Lu-Min

2008-07-01

In order to remove the artifacts of peripheral digital subtraction angiography (DSA), an affine transformation-based automatic image registration algorithm is introduced here. The whole process is described as follows: First, rectangle feature templates are constructed with their centers of the extracted Harris corners in the mask, and motion vectors of the central feature points are estimated using template matching technology with the similarity measure of maximum histogram energy. And then the optimal parameters of the affine transformation are calculated with the matrix singular value decomposition (SVD) method. Finally, bilinear intensity interpolation is taken to the mask according to the specific affine transformation. More than 30 peripheral DSA registrations are performed with the presented algorithm, and as the result, moving artifacts of the images are removed with sub-pixel precision, and the time consumption is less enough to satisfy the clinical requirements. Experimental results show the efficiency and robustness of the algorithm.

Characterization of Severe Arterial Phase Respiratory Motion Artifact on Gadoxetate Disodium-Enhanced MRI - Assessment of Interrater Agreement and Reliability.

PubMed

Ringe, Kristina Imeen; Luetkens, Julian A; Fimmers, Rolf; Hammerstingl, Renate Maria; Layer, Günter; Maurer, Martin H; Nähle, Claas Philip; Michalik, Sabine; Reimer, Peter; Schraml, Christina; Schreyer, Andreas G; Stumpp, Patrick; Vogl, Thomas J; Wacker, Frank K; Willinek, Winfried; Kukuk, Guido Mattias

2018-04-01

 To assess the interrater agreement and reliability of experienced abdominal radiologists in the characterization and grading of arterial phase gadoxetate disodium-related respiratory motion artifact on liver MRI.  This prospective multicenter study was initiated by the working group for abdominal imaging within the German Roentgen Society (DRG), and approved by the local IRB of each participating center. 11 board-certified radiologists independently reviewed 40 gadoxetate disodium-enhanced liver MRI datasets. Motion artifacts in the arterial phase were assessed on a 5-point scale. Interrater agreement and reliability were calculated using the intraclass correlation coefficient (ICC) and Kendall coefficient of concordance (W), with p < 0.05 deemed significant.  The ICC for interrater agreement and reliability were 0.983 (CI 0.973 - 0.990) and 0.985 (CI 0.978 - 0.991), respectively (both p < 0.0001), indicating excellent agreement and reliability. Kendall's W for interrater agreement was 0.865. A severe motion artifact, defined as a mean motion score ≥ 4 in the arterial phase was observed in 12 patients. In these specific cases, a motion score ≥ 4 was assigned by all readers in 75 % (n = 9/12 cases).  Differentiation and grading of arterial phase respiratory motion artifact is possible with a high level of inter-/intrarater agreement and interrater reliability, which is crucial for assessing the incidence of this phenomenon in larger multicenter studies.   · Inter- and intrarater agreement for motion artifact scoring is excellent among experienced readers.. · Interrater reliability for motion artifact scoring is excellent among experienced readers.. · Characterization of severe motion artifacts proved feasible in this multicenter study.. · Ringe KI, Luetkens JA, Fimmers R et al. Characterization of Severe Arterial Phase Respiratory Motion Artifact on Gadoxetate Disodium-Enhanced MRI - Assessment of Interrater Agreement and Reliability. Fortschr Röntgenstr 2017; 190: 341 - 347. © Georg Thieme Verlag KG Stuttgart · New York.

MR-based motion correction for PET imaging using wired active MR microcoils in simultaneous PET-MR: Phantom study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Chuan; Brady, Thomas J.; El Fakhri, Georges

2014-04-15

Purpose: Artifacts caused by head motion present a major challenge in brain positron emission tomography (PET) imaging. The authors investigated the feasibility of using wired active MR microcoils to track head motion and incorporate the measured rigid motion fields into iterative PET reconstruction. Methods: Several wired active MR microcoils and a dedicated MR coil-tracking sequence were developed. The microcoils were attached to the outer surface of an anthropomorphic{sup 18}F-filled Hoffman phantom to mimic a brain PET scan. Complex rotation/translation motion of the phantom was induced by a balloon, which was connected to a ventilator. PET list-mode and MR tracking datamore » were acquired simultaneously on a PET-MR scanner. The acquired dynamic PET data were reconstructed iteratively with and without motion correction. Additionally, static phantom data were acquired and used as the gold standard. Results: Motion artifacts in PET images were effectively removed by wired active MR microcoil based motion correction. Motion correction yielded an activity concentration bias ranging from −0.6% to 3.4% as compared to a bias ranging from −25.0% to 16.6% if no motion correction was applied. The contrast recovery values were improved by 37%–156% with motion correction as compared to no motion correction. The image correlation (mean ± standard deviation) between the motion corrected (uncorrected) images of 20 independent noise realizations and static reference was R{sup 2} = 0.978 ± 0.007 (0.588 ± 0.010, respectively). Conclusions: Wired active MR microcoil based motion correction significantly improves brain PET quantitative accuracy and image contrast.« less

MR-based motion correction for PET imaging using wired active MR microcoils in simultaneous PET-MR: Phantom study1

PubMed Central

Huang, Chuan; Ackerman, Jerome L.; Petibon, Yoann; Brady, Thomas J.; El Fakhri, Georges; Ouyang, Jinsong

2014-01-01

Purpose: Artifacts caused by head motion present a major challenge in brain positron emission tomography (PET) imaging. The authors investigated the feasibility of using wired active MR microcoils to track head motion and incorporate the measured rigid motion fields into iterative PET reconstruction. Methods: Several wired active MR microcoils and a dedicated MR coil-tracking sequence were developed. The microcoils were attached to the outer surface of an anthropomorphic 18F-filled Hoffman phantom to mimic a brain PET scan. Complex rotation/translation motion of the phantom was induced by a balloon, which was connected to a ventilator. PET list-mode and MR tracking data were acquired simultaneously on a PET-MR scanner. The acquired dynamic PET data were reconstructed iteratively with and without motion correction. Additionally, static phantom data were acquired and used as the gold standard. Results: Motion artifacts in PET images were effectively removed by wired active MR microcoil based motion correction. Motion correction yielded an activity concentration bias ranging from −0.6% to 3.4% as compared to a bias ranging from −25.0% to 16.6% if no motion correction was applied. The contrast recovery values were improved by 37%–156% with motion correction as compared to no motion correction. The image correlation (mean ± standard deviation) between the motion corrected (uncorrected) images of 20 independent noise realizations and static reference was R2 = 0.978 ± 0.007 (0.588 ± 0.010, respectively). Conclusions: Wired active MR microcoil based motion correction significantly improves brain PET quantitative accuracy and image contrast. PMID:24694141

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion

PubMed Central

Symeonidou, Evangelia-Regkina; Nordin, Andrew D.; Hairston, W. David

2018-01-01

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0–2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG. PMID:29614020

Automatic motion correction for in vivo human skin optical coherence tomography angiography through combined rigid and nonrigid registration

NASA Astrophysics Data System (ADS)

Wei, David Wei; Deegan, Anthony J.; Wang, Ruikang K.

2017-06-01

When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.

Automatic motion correction for in vivo human skin optical coherence tomography angiography through combined rigid and nonrigid registration.

PubMed

Wei, David Wei; Deegan, Anthony J; Wang, Ruikang K

2017-06-01

When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.

Correction of motion artifacts in endoscopic optical coherence tomography and autofluorescence images based on azimuthal en face image registration.

PubMed

Abouei, Elham; Lee, Anthony M D; Pahlevaninezhad, Hamid; Hohert, Geoffrey; Cua, Michelle; Lane, Pierre; Lam, Stephen; MacAulay, Calum

2018-01-01

We present a method for the correction of motion artifacts present in two- and three-dimensional in vivo endoscopic images produced by rotary-pullback catheters. This method can correct for cardiac/breathing-based motion artifacts and catheter-based motion artifacts such as nonuniform rotational distortion (NURD). This method assumes that en face tissue imaging contains slowly varying structures that are roughly parallel to the pullback axis. The method reduces motion artifacts using a dynamic time warping solution through a cost matrix that measures similarities between adjacent frames in en face images. We optimize and demonstrate the suitability of this method using a real and simulated NURD phantom and in vivo endoscopic pulmonary optical coherence tomography and autofluorescence images. Qualitative and quantitative evaluations of the method show an enhancement of the image quality. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Physical activity classification using time-frequency signatures of motion artifacts in multi-channel electrical impedance plethysmographs.

PubMed

Khan, Hassan Aqeel; Gore, Amit; Ashe, Jeff; Chakrabartty, Shantanu

2017-07-01

Physical activities are known to introduce motion artifacts in electrical impedance plethysmographic (EIP) sensors. Existing literature considers motion artifacts as a nuisance and generally discards the artifact containing portion of the sensor output. This paper examines the notion of exploiting motion artifacts for detecting the underlying physical activities which give rise to the artifacts in question. In particular, we investigate whether the artifact pattern associated with a physical activity is unique; and does it vary from one human-subject to another? Data was recorded from 19 adult human-subjects while conducting 5 distinct, artifact inducing, activities. A set of novel features based on the time-frequency signatures of the sensor outputs are then constructed. Our analysis demonstrates that these features enable high accuracy detection of the underlying physical activity. Using an SVM classifier we are able to differentiate between 5 distinct physical activities (coughing, reaching, walking, eating and rolling-on-bed) with an average accuracy of 85.46%. Classification is performed solely using features designed specifically to capture the time-frequency signatures of different physical activities. This enables us to measure both respiratory and motion information using only one type of sensor. This is in contrast to conventional approaches to physical activity monitoring; which rely on additional hardware such as accelerometers to capture activity information.

A generic EEG artifact removal algorithm based on the multi-channel Wiener filter

NASA Astrophysics Data System (ADS)

Somers, Ben; Francart, Tom; Bertrand, Alexander

2018-06-01

Objective. The electroencephalogram (EEG) is an essential neuro-monitoring tool for both clinical and research purposes, but is susceptible to a wide variety of undesired artifacts. Removal of these artifacts is often done using blind source separation techniques, relying on a purely data-driven transformation, which may sometimes fail to sufficiently isolate artifacts in only one or a few components. Furthermore, some algorithms perform well for specific artifacts, but not for others. In this paper, we aim to develop a generic EEG artifact removal algorithm, which allows the user to annotate a few artifact segments in the EEG recordings to inform the algorithm. Approach. We propose an algorithm based on the multi-channel Wiener filter (MWF), in which the artifact covariance matrix is replaced by a low-rank approximation based on the generalized eigenvalue decomposition. The algorithm is validated using both hybrid and real EEG data, and is compared to other algorithms frequently used for artifact removal. Main results. The MWF-based algorithm successfully removes a wide variety of artifacts with better performance than current state-of-the-art methods. Significance. Current EEG artifact removal techniques often have limited applicability due to their specificity to one kind of artifact, their complexity, or simply because they are too ‘blind’. This paper demonstrates a fast, robust and generic algorithm for removal of EEG artifacts of various types, i.e. those that were annotated as unwanted by the user.

Correction of motion artifacts in OCT-AFI data collected in airways (Conference Presentation)

NASA Astrophysics Data System (ADS)

Abouei, Elham; Lane, Pierre M.; Pahlevaninezhad, Hamid; Lee, Anthony; Lam, Stephen; MacAulay, Calum E.

2016-03-01

Abstract: Optical coherence tomography (OCT) provides in vivo imaging with near-histologic resolution of tissue morphology. OCT has been successfully employed in clinical practice in non-pulmonary fields of medicine such as ophthalmology and cardiology. Studies suggest that OCT has the potential to be a powerful tool for the detection and localization of malignant and non-malignant pulmonary diseases. The combination of OCT with autofluorescence imaging (AFI) provides valuable information about the structural and metabolic state of tissues. Successful application of OCT or OCT-AFI to the field of pulmonary medicine requires overcoming several challenges. This work address those associated with motion: cardiac cycle, breathing and non-uniform rotation distortion (NURD) artifacts. Mechanically rotated endoscopic probes often suffer from image degradation due to NURD. In addition cardiac and breathing motion artifacts may be present in-vivo that are not seen ex-vivo. These motion artifacts can be problematic in OCT-AFI systems with slower acquisition rates and have been observed to generate identifiable prominent artifacts which make confident interpretation of observed structures (blood vessels, etc) difficult. Understanding and correcting motion artifact could improve the image quality and interpretation. In this work, the motion artifacts in pulmonary OCT-AFI data sets are estimated in both AFI and OCT images using a locally adaptive registration algorithm that can be used to correct/reduce such artifacts. Performance of the algorithm is evaluated on images of a NURD phantom and on in-vivo OCT-AFI datasets of peripheral lung airways.

Metallic artifact in MRI after removal of orthopedic implants.

PubMed

Bagheri, Mohammad Hadi; Hosseini, Mehrdad Mohammad; Emami, Mohammad Jafar; Foroughi, Amin Aiboulhassani

2012-03-01

The aim of the present study was to evaluate the metallic artifacts in MRI of the orthopedic patients after removal of metallic implants. From March to August 2009, 40 orthopedic patients operated for removal of orthopedic metallic implants were studied by post-operative MRI from the site of removal of implants. A grading scale of 0-3 was assigned for artifact in MR images whereby 0 was considered no artifact; and I-III were considered mild, moderate, and severe metallic artifacts, respectively. These grading records were correlated with other variables including the type, size, number, and composition of metallic devices; and the site and duration of orthopedic devices stay in the body. Metallic susceptibly artifacts were detected in MRI of 18 of 40 cases (45%). Screws and pins in removed hardware were the most important factors for causing artifacts in MRI. The artifacts were found more frequently in the patients who had more screws and pins in the removed implants. Gender, age, site of implantation of the device, length of the hardware, composition of the metallic implants (stainless steel versus titanium), and duration of implantation of the hardware exerted no effect in producing metallic artifacts after removal of implants. Short TE sequences of MRI (such as T1 weighted) showed fewer artifacts. Susceptibility of metallic artifacts is a frequent phenomenon in MRI of patients upon removal of metallic orthopedic implants. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

PubMed

Zhang, Qingxue; Zhou, Dian; Zeng, Xuan

2016-11-01

This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (ECG) signals continuously and heavily corrupted by random motion artifacts in wearable applications. The framework includes two stages, i.e. heartbeat identification and refinement, respectively. In the first stage, an adaptive threshold-based auto-segmentation approach is proposed to select out heartbeat candidates, including the real heartbeats and large amounts of motion-artifact-induced interferential spikes. Then twenty-six features are extracted for each candidate in time, spatial, frequency and statistical domains, and evaluated by a spare support vector machine (SVM) to select out ten critical features which can effectively reveal residual heartbeat information. Afterwards, an SVM model, created on the training data using the selected feature set, is applied to find high confident heartbeats from a large number of candidates in the testing data. In the second stage, the SVM classification results are further refined by two steps: (1) a rule-based classifier with two attributes named 'continuity check' and 'locality check' for outlier (false positives) removal, and (2) a heartbeat interpolation strategy for missing-heartbeat (false negatives) recovery. The framework is evaluated on a wrist-ECG dataset acquired by a semi-customized platform and also a public dataset. When the signal-to-noise ratio is as low as  -7 dB, the mean absolute error of the estimated IHR is 1.4 beats per minute (BPM) and the root mean square error is 6.5 BPM. The proposed framework greatly outperforms well-established approaches, demonstrating that it can effectively identify the heartbeats from ECG signals continuously corrupted by intense motion artifacts and robustly estimate the IHR. This study is expected to contribute to robust long-term wearable IHR monitoring for pervasive heart health and fitness management.

[Design of a pulse oximeter used to low perfusion and low oxygen saturation].

PubMed

Tan, Shuangping; Ai, Zhiguang; Yang, Yuxing; Xie, Qingguo

2013-05-01

This paper presents a new pulse oximeter used to low perfusion at 0.125% and wide oxygen saturation range from 35% to 100%. In order to acquire the best PPG signals, the variable gain amplifier(VGA) is adopted in hardware. The self-developed auto-correlation modeling method is adopted in software and it can extract pulse wave from low perfusion signals and remove motion artifacts partly.

Spatiotemporal filtering of MR-temperature artifacts arising from bowel motion during transurethral MR-HIFU

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmitt, Alain, E-mail: aschmitt@sri.utoronto.ca; Mougenot, Charles; Chopra, Rajiv

2014-11-01

Purpose: Transurethral MR-HIFU is a minimally invasive image-guided treatment for localized prostate cancer that enables precise targeting of tissue within the gland. The treatment is performed within a clinical MRI to obtain real-time MR thermometry used as an active feedback to control the spatial heating pattern in the prostate and to monitor for potential damage to surrounding tissues. This requires that the MR thermometry measurements are an accurate representation of the true tissue temperature. The proton resonance frequency shift thermometry method used is sensitive to tissue motion and changes in the local magnetic susceptibility that can be caused by themore » motion of air bubbles in the rectum, which can impact the performance of transurethral MR-HIFU in these regions of the gland. Methods: A method is proposed for filtering of temperature artifacts based on the temporal variance of the temperature, using empirical and dynamic positional knowledge of the ultrasonic heating beam, and an estimation of the measurement noise. A two-step correction strategy is introduced which eliminates artifact-detected temperature variations while keeping the noise level low through spatial averaging. Results: The filter has been evaluated by postprocessing data from five human transurethral ultrasound treatments. The two-step correction process led to reduced final temperature standard deviation in the prostate and rectum areas where the artifact was located, without negatively affecting areas distal to the artifact. The performance of the filter was also found to be consistent across all six of the data sets evaluated. The evaluation of the detection criterion parameter M determined that a value of M = 3 achieves a conservative filter with minimal loss of spatial resolution during the process. Conclusions: The filter was able to remove most artifacts due to the presence of moving air bubbles in the rectum during transurethral MR-HIFU. A quantitative estimation of the filter capabilities shows a systematic improvement in the standard deviation of the corrected temperature maps in the rectum zone as well as in the entire acquired slice.« less

Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI

PubMed Central

Abbott, David F.; Masterton, Richard A. J.; Archer, John S.; Fleming, Steven W.; Warren, Aaron E. L.; Jackson, Graeme D.

2015-01-01

One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject’s head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG–fMRI system that differs substantially from current commercially available EEG–fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG–fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner. PMID:25601852

Adaptive motion artifact reducing algorithm for wrist photoplethysmography application

NASA Astrophysics Data System (ADS)

Zhao, Jingwei; Wang, Guijin; Shi, Chenbo

2016-04-01

Photoplethysmography (PPG) technology is widely used in wearable heart pulse rate monitoring. It might reveal the potential risks of heart condition and cardiopulmonary function by detecting the cardiac rhythms in physical exercise. However the quality of wrist photoelectric signal is very sensitive to motion artifact since the thicker tissues and the fewer amount of capillaries. Therefore, motion artifact is the major factor that impede the heart rate measurement in the high intensity exercising. One accelerometer and three channels of light with different wavelengths are used in this research to analyze the coupled form of motion artifact. A novel approach is proposed to separate the pulse signal from motion artifact by exploiting their mixing ratio in different optical paths. There are four major steps of our method: preprocessing, motion artifact estimation, adaptive filtering and heart rate calculation. Five healthy young men are participated in the experiment. The speeder in the treadmill is configured as 12km/h, and all subjects would run for 3-10 minutes by swinging the arms naturally. The final result is compared with chest strap. The average of mean square error (MSE) is less than 3 beats per minute (BPM/min). Proposed method performed well in intense physical exercise and shows the great robustness to individuals with different running style and posture.

SU-F-J-115: Target Volume and Artifact Evaluation of a New Device-Less 4D CT Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, R; Pan, T

2016-06-15

Purpose: 4DCT is often used in radiation therapy treatment planning to define the extent of motion of the visible tumor (IGTV). Recent available software allows 4DCT images to be created without the use of an external motion surrogate. This study aims to compare this device-less algorithm to a standard device-driven technique (RPM) in regards to artifacts and the creation of treatment volumes. Methods: 34 lung cancer patients who had previously received a cine 4DCT scan on a GE scanner with an RPM determined respiratory signal were selected. Cine images were sorted into 10 phases based on both the RPM signalmore » and the device-less algorithm. Contours were created on standard and device-less maximum intensity projection (MIP) images using a region growing algorithm and manual adjustment to remove other structures. Variations in measurements due to intra-observer differences in contouring were assessed by repeating a subset of 6 patients 2 additional times. Artifacts in each phase image were assessed using normalized cross correlation at each bed position transition. A score between +1 (artifacts “better” in all phases for device-less) and −1 (RPM similarly better) was assigned for each patient based on these results. Results: Device-less IGTV contours were 2.1 ± 1.0% smaller than standard IGTV contours (not significant, p = 0.15). The Dice similarity coefficient (DSC) was 0.950 ± 0.006 indicating good similarity between the contours. Intra-observer variation resulted in standard deviations of 1.2 percentage points in percent volume difference and 0.005 in DSC measurements. Only two patients had improved artifacts with RPM, and the average artifact score (0.40) was significantly greater than zero. Conclusion: Device-less 4DCT can be used in place of the standard method for target definition due to no observed difference between standard and device-less IGTVs. Phase image artifacts were significantly reduced with the device-less method.« less

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

PubMed

Rantalainen, Timo; Chivers, Paola; Beck, Belinda R; Robertson, Sam; Hart, Nicolas H; Nimphius, Sophia; Weeks, Benjamin K; McIntyre, Fleur; Hands, Beth; Siafarikas, Aris

Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual inspection) and objective assessments of the scans. However, previously reported objective methods either cannot be applied on the reconstructed image or have not been tested for distal bone sites. Therefore, the purpose of the present study was to develop and validate motion artifact classifiers to quantify motion artifact in pQCT scans. Whether textural features could provide adequate motion artifact classification performance in 2 adolescent datasets with pQCT scans from tibial and radial diaphyses and epiphyses was tested. The first dataset was split into training (66% of sample) and validation (33% of sample) datasets. Visual classification was used as the ground truth. Moderate to substantial classification performance (J48 classifier, kappa coefficients from 0.57 to 0.80) was observed in the validation dataset with the novel texture-based classifier. In applying the same classifier to the second cross-sectional dataset, a slight-to-fair (κ = 0.01-0.39) classification performance was observed. Overall, this novel textural analysis-based classifier provided a moderate-to-substantial classification of motion artifact when the classifier was specifically trained for the measurement device and population. Classification based on textural features may be used to prescreen obviously acceptable and unacceptable scans, with a subsequent human-operated visual classification of any remaining scans. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

NASA Astrophysics Data System (ADS)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan

2013-01-01

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.

PubMed

Trejo, Leonard J; Rosipal, Roman; Matthews, Bryan

2006-06-01

We have developed and tested two electroencephalogram (EEG)-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KPLS classifier to map power spectra of 62-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject's average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: 1) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal electrooculograms (EOG) signals, 2) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from 12 electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about 3 min. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 s for movement initiation and turning. We have also developed a realistic demonstration of our system for control of a moving map display (http://ti.arc.nasa.gov/).

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

PubMed

Power, Jonathan D; Plitt, Mark; Kundu, Prantik; Bandettini, Peter A; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection

PubMed Central

Plitt, Mark; Kundu, Prantik; Bandettini, Peter A.; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). PMID:28880888

Motion-induced phase error estimation and correction in 3D diffusion tensor imaging.

PubMed

Van, Anh T; Hernando, Diego; Sutton, Bradley P

2011-11-01

A multishot data acquisition strategy is one way to mitigate B0 distortion and T2∗ blurring for high-resolution diffusion-weighted magnetic resonance imaging experiments. However, different object motions that take place during different shots cause phase inconsistencies in the data, leading to significant image artifacts. This work proposes a maximum likelihood estimation and k-space correction of motion-induced phase errors in 3D multishot diffusion tensor imaging. The proposed error estimation is robust, unbiased, and approaches the Cramer-Rao lower bound. For rigid body motion, the proposed correction effectively removes motion-induced phase errors regardless of the k-space trajectory used and gives comparable performance to the more computationally expensive 3D iterative nonlinear phase error correction method. The method has been extended to handle multichannel data collected using phased-array coils. Simulation and in vivo data are shown to demonstrate the performance of the method.

Dynamic and Inherent B0 Correction for DTI Using Stimulated Echo Spiral Imaging

PubMed Central

Avram, Alexandru V.; Guidon, Arnaud; Truong, Trong-Kha; Liu, Chunlei; Song, Allen W.

2013-01-01

Purpose To present a novel technique for high-resolution stimulated echo (STE) diffusion tensor imaging (DTI) with self-navigated interleaved spirals (SNAILS) readout trajectories that can inherently and dynamically correct for image artifacts due to spatial and temporal variations in the static magnetic field (B0) resulting from eddy currents, tissue susceptibilities, subject/physiological motion, and hardware instabilities. Methods The Hahn spin echo formed by the first two 90° radio-frequency pulses is balanced to consecutively acquire two additional images with different echo times (TE) and generate an inherent field map, while the diffusion-prepared STE signal remains unaffected. For every diffusion-encoding direction, an intrinsically registered field map is estimated dynamically and used to effectively and inherently correct for off-resonance artifacts in the reconstruction of the corresponding diffusion-weighted image (DWI). Results After correction with the dynamically acquired field maps, local blurring artifacts are specifically removed from individual STE DWIs and the estimated diffusion tensors have significantly improved spatial accuracy and larger fractional anisotropy. Conclusion Combined with the SNAILS acquisition scheme, our new method provides an integrated high-resolution short-TE DTI solution with inherent and dynamic correction for both motion-induced phase errors and off-resonance effects. PMID:23630029

A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness.

PubMed

Kim, Kyungsoo; Punte, Andrea Kleine; Mertens, Griet; Van de Heyning, Paul; Park, Kyung-Joon; Choi, Hongsoo; Choi, Ji-Woong; Song, Jae-Jin

2015-11-30

Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed CI artifacts. The proposed method selectively removes CI artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. CI artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with CIs. Copyright © 2015 Elsevier B.V. All rights reserved.

Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI.

PubMed

Koush, Yury; Zvyagintsev, Mikhail; Dyck, Miriam; Mathiak, Krystyna A; Mathiak, Klaus

2012-01-02

Real-time fMRI allows analysis and visualization of the brain activity online, i.e. within one repetition time. It can be used in neurofeedback applications where subjects attempt to control an activation level in a specified region of interest (ROI) of their brain. The signal derived from the ROI is contaminated with noise and artifacts, namely with physiological noise from breathing and heart beat, scanner drift, motion-related artifacts and measurement noise. We developed a Bayesian approach to reduce noise and to remove artifacts in real-time using a modified Kalman filter. The system performs several signal processing operations: subtraction of constant and low-frequency signal components, spike removal and signal smoothing. Quantitative feedback signal quality analysis was used to estimate the quality of the neurofeedback time series and performance of the applied signal processing on different ROIs. The signal-to-noise ratio (SNR) across the entire time series and the group event-related SNR (eSNR) were significantly higher for the processed time series in comparison to the raw data. Applied signal processing improved the t-statistic increasing the significance of blood oxygen level-dependent (BOLD) signal changes. Accordingly, the contrast-to-noise ratio (CNR) of the feedback time series was improved as well. In addition, the data revealed increase of localized self-control across feedback sessions. The new signal processing approach provided reliable neurofeedback, performed precise artifacts removal, reduced noise, and required minimal manual adjustments of parameters. Advanced and fast online signal processing algorithms considerably increased the quality as well as the information content of the control signal which in turn resulted in higher contingency in the neurofeedback loop. Copyright © 2011 Elsevier Inc. All rights reserved.

Suppression of motion-induced streak artifacts along chords in fan-beam BPF-reconstructions of motion-contaminated projection data

NASA Astrophysics Data System (ADS)

King, Martin; Xia, Dan; Yu, Lifeng; Pan, Xiaochuan; Giger, Maryellen

2006-03-01

Usage of the backprojection filtration (BPF) algorithm for reconstructing images from motion-contaminated fan-beam data may result in motion-induced streak artifacts, which appear in the direction of the chords on which images are reconstructed. These streak artifacts, which are most pronounced along chords tangent to the edges of the moving object, may be suppressed by use of the weighted BPF (WBPF) algorithm, which can exploit the inherent redundancies in fan-beam data. More specifically, reconstructions using full-scan and short-scan data can allow for substantial suppression of these streaks, whereas those using reduced-scan data can allow for partial suppression. Since multiple different reconstructions of the same chord can be obtained by varying the amount of redundant data used, we have laid the groundwork for a possible method to characterize the amount of motion encoded within the data used for reconstructing an image on a particular chord. Furthermore, since motion artifacts in WBPF reconstructions using full-scan and short-scan data appear similar to those in corresponding fan-beam filtered backprojection (FFBP) reconstructions for the cases performed in this study, the BPF and WBPF algorithms potentially may be used to arrive at a more fundamental characterization of how motion artifacts appear in FFBP reconstructions.

MRI-Based Nonrigid Motion Correction in Simultaneous PET/MRI

PubMed Central

Chun, Se Young; Reese, Timothy G.; Ouyang, Jinsong; Guerin, Bastien; Catana, Ciprian; Zhu, Xuping; Alpert, Nathaniel M.; El Fakhri, Georges

2014-01-01

Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application. Methods Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies. Results Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5–8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%–276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%–92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results. Conclusion Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection compared with respiratory gating and no motion correction while reducing radiation dose. In vivo primate and rabbit studies confirmed the improvement in PET image quality and provide the rationale for evaluation in simultaneous whole-body PET/MRI clinical studies. PMID:22743250

Adaptive cancellation of motion artifact in wearable biosensors.

PubMed

Yousefi, Rasoul; Nourani, Mehrdad; Panahi, Issa

2012-01-01

The performance of wearable biosensors is highly influenced by motion artifact. In this paper, a model is proposed for analysis of motion artifact in wearable photoplethysmography (PPG) sensors. Using this model, we proposed a robust real-time technique to estimate fundamental frequency and generate a noise reference signal. A Least Mean Square (LMS) adaptive noise canceler is then designed and validated using our synthetic noise generator. The analysis and results on proposed technique for noise cancellation shows promising performance.

Quality Control of Structural MRI Images Applied Using FreeSurfer—A Hands-On Workflow to Rate Motion Artifacts

PubMed Central

Backhausen, Lea L.; Herting, Megan M.; Buse, Judith; Roessner, Veit; Smolka, Michael N.; Vetter, Nora C.

2016-01-01

In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g., FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e., determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here, we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies. PMID:27999528

Automatic removal of eye-movement and blink artifacts from EEG signals.

PubMed

Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

Effects of Spatio-Temporal Aliasing on Out-the-Window Visual Systems

NASA Technical Reports Server (NTRS)

Sweet, Barbara T.; Stone, Leland S.; Liston, Dorion B.; Hebert, Tim M.

2014-01-01

Designers of out-the-window visual systems face a challenge when attempting to simulate the outside world as viewed from a cockpit. Many methodologies have been developed and adopted to aid in the depiction of particular scene features, or levels of static image detail. However, because aircraft move, it is necessary to also consider the quality of the motion in the simulated visual scene. When motion is introduced in the simulated visual scene, perceptual artifacts can become apparent. A particular artifact related to image motion, spatiotemporal aliasing, will be addressed. The causes of spatio-temporal aliasing will be discussed, and current knowledge regarding the impact of these artifacts on both motion perception and simulator task performance will be reviewed. Methods of reducing the impact of this artifact are also addressed

Rapid estimation of 4DCT motion-artifact severity based on 1D breathing-surrogate periodicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Guang, E-mail: lig2@mskcc.org; Caraveo, Marshall; Wei, Jie

2014-11-01

Purpose: Motion artifacts are common in patient four-dimensional computed tomography (4DCT) images, leading to an ill-defined tumor volume with large variations for radiotherapy treatment and a poor foundation with low imaging fidelity for studying respiratory motion. The authors developed a method to estimate 4DCT image quality by establishing a correlation between the severity of motion artifacts in 4DCT images and the periodicity of the corresponding 1D respiratory waveform (1DRW) used for phase binning in 4DCT reconstruction. Methods: Discrete Fourier transformation (DFT) was applied to analyze 1DRW periodicity. The breathing periodicity index (BPI) was defined as the sum of the largestmore » five Fourier coefficients, ranging from 0 to 1. Distortional motion artifacts (excluding blurring) of cine-scan 4DCT at the junctions of adjacent couch positions around the diaphragm were classified in three categories: incomplete, overlapping, and duplicate anatomies. To quantify these artifacts, discontinuity of the diaphragm at the junctions was measured in distance and averaged along six directions in three orthogonal views. Artifacts per junction (APJ) across the entire diaphragm were calculated in each breathing phase and phase-averaged APJ{sup ¯}, defined as motion-artifact severity (MAS), was obtained for each patient. To make MAS independent of patient-specific motion amplitude, two new MAS quantities were defined: MAS{sup D} is normalized to the maximum diaphragmatic displacement and MAS{sup V} is normalized to the mean diaphragmatic velocity (the breathing period was obtained from DFT analysis of 1DRW). Twenty-six patients’ free-breathing 4DCT images and corresponding 1DRW data were studied. Results: Higher APJ values were found around midventilation and full inhalation while the lowest APJ values were around full exhalation. The distribution of MAS is close to Poisson distribution with a mean of 2.2 mm. The BPI among the 26 patients was calculated with a value ranging from 0.25 to 0.93. The DFT calculation was within 3 s per 1DRW. Correlations were found between 1DRW periodicity and 4DCT artifact severity: −0.71 for MAS{sup D} and −0.73 for MAS{sup V}. A BPI greater than 0.85 in a 1DRW suggests minimal motion artifacts in the corresponding 4DCT images. Conclusions: The breathing periodicity index and motion-artifact severity index are introduced to assess the relationship between 1DRW and 4DCT. A correlation between 1DRW periodicity and 4DCT artifact severity has been established. The 1DRW periodicity provides a rapid means to estimate 4DCT image quality. The rapid 1DRW analysis and the correlative relationship can be applied prospectively to identify irregular breathers as candidates for breath coaching prior to 4DCT scan and retrospectively to select high-quality 4DCT images for clinical motion-management research.« less

Rapid estimation of 4DCT motion-artifact severity based on 1D breathing-surrogate periodicity

PubMed Central

Li, Guang; Caraveo, Marshall; Wei, Jie; Rimner, Andreas; Wu, Abraham J.; Goodman, Karyn A.; Yorke, Ellen

2014-01-01

Purpose: Motion artifacts are common in patient four-dimensional computed tomography (4DCT) images, leading to an ill-defined tumor volume with large variations for radiotherapy treatment and a poor foundation with low imaging fidelity for studying respiratory motion. The authors developed a method to estimate 4DCT image quality by establishing a correlation between the severity of motion artifacts in 4DCT images and the periodicity of the corresponding 1D respiratory waveform (1DRW) used for phase binning in 4DCT reconstruction. Methods: Discrete Fourier transformation (DFT) was applied to analyze 1DRW periodicity. The breathing periodicity index (BPI) was defined as the sum of the largest five Fourier coefficients, ranging from 0 to 1. Distortional motion artifacts (excluding blurring) of cine-scan 4DCT at the junctions of adjacent couch positions around the diaphragm were classified in three categories: incomplete, overlapping, and duplicate anatomies. To quantify these artifacts, discontinuity of the diaphragm at the junctions was measured in distance and averaged along six directions in three orthogonal views. Artifacts per junction (APJ) across the entire diaphragm were calculated in each breathing phase and phase-averaged APJ¯, defined as motion-artifact severity (MAS), was obtained for each patient. To make MAS independent of patient-specific motion amplitude, two new MAS quantities were defined: MASD is normalized to the maximum diaphragmatic displacement and MASV is normalized to the mean diaphragmatic velocity (the breathing period was obtained from DFT analysis of 1DRW). Twenty-six patients’ free-breathing 4DCT images and corresponding 1DRW data were studied. Results: Higher APJ values were found around midventilation and full inhalation while the lowest APJ values were around full exhalation. The distribution of MAS is close to Poisson distribution with a mean of 2.2 mm. The BPI among the 26 patients was calculated with a value ranging from 0.25 to 0.93. The DFT calculation was within 3 s per 1DRW. Correlations were found between 1DRW periodicity and 4DCT artifact severity: −0.71 for MASD and −0.73 for MASV. A BPI greater than 0.85 in a 1DRW suggests minimal motion artifacts in the corresponding 4DCT images. Conclusions: The breathing periodicity index and motion-artifact severity index are introduced to assess the relationship between 1DRW and 4DCT. A correlation between 1DRW periodicity and 4DCT artifact severity has been established. The 1DRW periodicity provides a rapid means to estimate 4DCT image quality. The rapid 1DRW analysis and the correlative relationship can be applied prospectively to identify irregular breathers as candidates for breath coaching prior to 4DCT scan and retrospectively to select high-quality 4DCT images for clinical motion-management research. PMID:25370631

Reference-Free Removal of EEG-fMRI Ballistocardiogram Artifacts with Harmonic Regression

PubMed Central

Krishnaswamy, Pavitra; Bonmassar, Giorgio; Poulsen, Catherine; Pierce, Eric T; Purdon, Patrick L.; Brown, Emery N.

2016-01-01

Combining electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) offers the potential for imaging brain activity with high spatial and temporal resolution. This potential remains limited by the significant ballistocardiogram (BCG) artifacts induced in the EEG by cardiac pulsation-related head movement within the magnetic field. We model the BCG artifact using a harmonic basis, pose the artifact removal problem as a local harmonic regression analysis, and develop an efficient maximum likelihood algorithm to estimate and remove BCG artifacts. Our analysis paradigm accounts for time-frequency overlap between the BCG artifacts and neurophysiologic EEG signals, and tracks the spatiotemporal variations in both the artifact and the signal. We evaluate performance on: simulated oscillatory and evoked responses constructed with realistic artifacts; actual anesthesia-induced oscillatory recordings; and actual visual evoked potential recordings. In each case, the local harmonic regression analysis effectively removes the BCG artifacts, and recovers the neurophysiologic EEG signals. We further show that our algorithm outperforms commonly used reference-based and component analysis techniques, particularly in low SNR conditions, the presence of significant time-frequency overlap between the artifact and the signal, and/or large spatiotemporal variations in the BCG. Because our algorithm does not require reference signals and has low computational complexity, it offers a practical tool for removing BCG artifacts from EEG data recorded in combination with fMRI. PMID:26151100

Automatic EEG artifact removal: a weighted support vector machine approach with error correction.

PubMed

Shao, Shi-Yun; Shen, Kai-Quan; Ong, Chong Jin; Wilder-Smith, Einar P V; Li, Xiao-Ping

2009-02-01

An automatic electroencephalogram (EEG) artifact removal method is presented in this paper. Compared to past methods, it has two unique features: 1) a weighted version of support vector machine formulation that handles the inherent unbalanced nature of component classification and 2) the ability to accommodate structural information typically found in component classification. The advantages of the proposed method are demonstrated on real-life EEG recordings with comparisons made to several benchmark methods. Results show that the proposed method is preferable to the other methods in the context of artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities. Qualitative evaluation of the reconstructed EEG epochs also demonstrates that after artifact removal inherent brain activities are largely preserved.

Real-Time Correction By Optical Tracking with Integrated Geometric Distortion Correction for Reducing Motion Artifacts in fMRI

NASA Astrophysics Data System (ADS)

Rotenberg, David J.

Artifacts caused by head motion are a substantial source of error in fMRI that limits its use in neuroscience research and clinical settings. Real-time scan-plane correction by optical tracking has been shown to correct slice misalignment and non-linear spin-history artifacts, however residual artifacts due to dynamic magnetic field non-uniformity may remain in the data. A recently developed correction technique, PLACE, can correct for absolute geometric distortion using the complex image data from two EPI images, with slightly shifted k-space trajectories. We present a correction approach that integrates PLACE into a real-time scan-plane update system by optical tracking, applied to a tissue-equivalent phantom undergoing complex motion and an fMRI finger tapping experiment with overt head motion to induce dynamic field non-uniformity. Experiments suggest that including volume by volume geometric distortion correction by PLACE can suppress dynamic geometric distortion artifacts in a phantom and in vivo and provide more robust activation maps.

POCS-enhanced correction of motion artifacts in parallel MRI.

PubMed

Samsonov, Alexey A; Velikina, Julia; Jung, Youngkyoo; Kholmovski, Eugene G; Johnson, Chris R; Block, Walter F

2010-04-01

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset, the artifact-free images are restored from the remaining data using coil sensitivity profiles. The error detection and data restoration are based on informational redundancy of phased-array data and may be applied to full and reduced datasets. An important advantage of the new POCS-based method is that, in addition to multicoil data redundancy, it can use a priori known properties about the imaged object for improved MR image artifact correction. The use of such information was shown to improve significantly k-space error detection and image artifact correction. The method was validated on data corrupted by simulated and real motion such as head motion and pulsatile flow.

Optical Mapping of Membrane Potential and Epicardial Deformation in Beating Hearts.

PubMed

Zhang, Hanyu; Iijima, Kenichi; Huang, Jian; Walcott, Gregory P; Rogers, Jack M

2016-07-26

Cardiac optical mapping uses potentiometric fluorescent dyes to image membrane potential (Vm). An important limitation of conventional optical mapping is that contraction is usually arrested pharmacologically to prevent motion artifacts from obscuring Vm signals. However, these agents may alter electrophysiology, and by abolishing contraction, also prevent optical mapping from being used to study coupling between electrical and mechanical function. Here, we present a method to simultaneously map Vm and epicardial contraction in the beating heart. Isolated perfused swine hearts were stained with di-4-ANEPPS and fiducial markers were glued to the epicardium for motion tracking. The heart was imaged at 750 Hz with a video camera. Fluorescence was excited with cyan or blue LEDs on alternating camera frames, thus providing a 375-Hz effective sampling rate. Marker tracking enabled the pixel(s) imaging any epicardial site within the marked region to be identified in each camera frame. Cyan- and blue-elicited fluorescence have different sensitivities to Vm, but other signal features, primarily motion artifacts, are common. Thus, taking the ratio of fluorescence emitted by a motion-tracked epicardial site in adjacent frames removes artifacts, leaving Vm (excitation ratiometry). Reconstructed Vm signals were validated by comparison to monophasic action potentials and to conventional optical mapping signals. Binocular imaging with additional video cameras enabled marker motion to be tracked in three dimensions. From these data, epicardial deformation during the cardiac cycle was quantified by computing finite strain fields. We show that the method can simultaneously map Vm and strain in a left-sided working heart preparation and can image changes in both electrical and mechanical function 5 min after the induction of regional ischemia. By allowing high-resolution optical mapping in the absence of electromechanical uncoupling agents, the method relieves a long-standing limitation of optical mapping and has potential to enhance new studies in coupled cardiac electromechanics. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A Novel Stimulus Artifact Removal Technique for High-Rate Electrical Stimulation

PubMed Central

Heffer, Leon F; Fallon, James B

2008-01-01

Electrical stimulus artifact corrupting electrophysiological recordings often make the subsequent analysis of the underlying neural response difficult. This is particularly evident when investigating short-latency neural activity in response to high-rate electrical stimulation. We developed and evaluated an off-line technique for the removal of stimulus artifact from electrophysiological recordings. Pulsatile electrical stimulation was presented at rates of up to 5000 pulses/s during extracellular recordings of guinea pig auditory nerve fibers. Stimulus artifact was removed by replacing the sample points at each stimulus artifact event with values interpolated along a straight line, computed from neighbouring sample points. This technique required only that artifact events be identifiable and that the artifact duration remained less than both the inter-stimulus interval and the time course of the action potential. We have demonstrated that this computationally efficient sample-and-interpolate technique removes the stimulus artifact with minimal distortion of the action potential waveform. We suggest that this technique may have potential applications in a range of electrophysiological recording systems. PMID:18339428

A novel approach to dual excitation ratiometric optical mapping of cardiac action potentials with di-4-ANEPPS using pulsed LED excitation.

PubMed

Bachtel, Andrew D; Gray, Richard A; Stohlman, Jayna M; Bourgeois, Elliot B; Pollard, Andrew E; Rogers, Jack M

2011-07-01

We developed a new method for ratiometric optical mapping of transmembrane potential (V(m)) in cardiac preparations stained with di-4-ANEPPS. V(m)-dependent shifts of excitation and emission spectra establish two excitation bands (<481 and >481 nm) that produce fluorescence changes of opposite polarity within a single emission band (575-620 nm). The ratio of these positive and negative fluorescence signals (excitation ratiometry) increases V(m) sensitivity and removes artifacts common to both signals. We pulsed blue (450 ± 10 nm) and cyan (505 ± 15 nm) light emitting diodes (LEDs) at 375 Hz in alternating phase synchronized to a camera (750 frames-per-second). Fluorescence was bandpass filtered (585 ± 20 nm). This produced signals with upright (blue) and inverted (cyan) action potentials (APs) interleaved in sequential frames. In four whole swine hearts with motion chemically arrested, fractional fluorescence for blue, cyan, and ratio signals was 1.2 ± 0.3%, 1.2 ± 0.3%, and 2.4 ± 0.6%, respectively. Signal-to-noise ratios were 4.3 ± 1.4, 4.0 ± 1.2, and 5.8 ± 1.9, respectively. After washing out the electromechanical uncoupling agent, we characterized motion artifact by cross-correlating blue, cyan, and ratio signals with a signal with normal AP morphology. Ratiometry improved cross-correlation coefficients from 0.50 ± 0.48 to 0.81 ± 0.25, but did not cancel all motion artifacts. These findings demonstrate the feasibility of pulsed LED excitation ratiometry in myocardium. © 2011 IEEE

A Novel Approach to Dual Excitation Ratiometric Optical Mapping of Cardiac Action Potentials with Di-4-ANEPPS using Pulsed LED Excitation

PubMed Central

Bachtel, Andrew D.; Gray, Richard A.; Stohlman, Jayna M.; Bourgeois, Elliot B.; Pollard, Andrew E.

2011-01-01

We developed a new method for ratiometric optical mapping of transmembrane potential (Vm) in cardiac preparations stained with di-4-ANEPPS. Vm-dependent shifts of excitation and emission spectra establish two excitation bands (<481 and >481 nm) that produce fluorescence changes of opposite polarity within a single emission band (575–620 nm). The ratio of these positive and negative fluorescence signals (excitation ratiometry) increases Vm sensitivity and removes artifacts common to both signals. We pulsed blue (450±10 nm) and cyan (505±15 nm) light emitting diodes (LEDs) at 375 Hz in alternating phase synchronized to a camera (750 frames-per-second). Fluorescence was bandpass filtered (585±20 nm). This produced signals with upright (blue) and inverted (cyan) action potentials (APs) interleaved in sequential frames. In 4 whole swine hearts with motion chemically arrested, fractional fluorescence for blue, cyan, and ratio signals was 1.2±0.3%, 1.2±0.3%, and 2.4±0.6%, respectively. Signal-to-noise ratios were 4.3±1.4, 4.0±1.2, and 5.8±1.9, respectively. After washing out the electromechanical uncoupling agent, we characterized motion artifact by cross-correlating blue, cyan, and ratio signals with a signal with normal AP morphology. Ratiometry improved cross-correlation coefficients from 0.50±0.48 to 0.81±0.25, but did not cancel all motion artifacts. These findings demonstrate the feasibility of pulsed LED excitation ratiometry in myocardium. PMID:21536528

Automated reference-free detection of motion artifacts in magnetic resonance images.

PubMed

Küstner, Thomas; Liebgott, Annika; Mauch, Lukas; Martirosian, Petros; Bamberg, Fabian; Nikolaou, Konstantin; Yang, Bin; Schick, Fritz; Gatidis, Sergios

2018-04-01

Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture. T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation. Using these patches as input data, a convolutional neural network (CNN) was trained to derive probability maps for the presence of motion artifacts. A deep visualization offers a human-interpretable quality control of the trained CNN. Results were visually assessed on probability maps and as classification accuracy on a per-patch, per-slice and per-volunteer basis. On visual assessment, a clear difference of probability maps was observed between data sets with and without motion. The overall accuracy of motion detection on a per-patch/per-volunteer basis reached 97%/100% in the head and 75%/100% in the abdomen, respectively. Automated detection of motion artifacts in MRI is feasible with good accuracy in the head and abdomen. The proposed method provides quantification and localization of artifacts as well as a visualization of the learned content. It may be extended to other anatomic areas and used for quality assurance of MR images.

Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph.

PubMed

Warren, Kristen M; Harvey, Joshua R; Chon, Ki H; Mendelson, Yitzhak

2016-03-07

Photoplethysmographic (PPG) waveforms are used to acquire pulse rate (PR) measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA), limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels. In this paper, we investigate the performance of a custom-built multichannel forehead-mounted photoplethysmographic sensor under a variety of intense motion artifacts. We introduce an advanced multichannel template-matching algorithm that chooses the channel with the least motion artifact to calculate PR for each time instant. We show that for a wide variety of random motion, channels respond differently to motion artifacts, and the multichannel estimate outperforms single-channel estimates in terms of motion tolerance, signal quality, and PR errors. We have acquired 31 data sets consisting of PPG waveforms corrupted by random motion and show that the accuracy of PR measurements achieved was increased by up to 2.7 bpm when the multichannel-switching algorithm was compared to individual channels. The percentage of PR measurements with error ≤ 5 bpm during motion increased by 18.9% when the multichannel switching algorithm was compared to the mean PR from all channels. Moreover, our algorithm enables automatic selection of the best signal fidelity channel at each time point among the multichannel PPG data.

Comparison of motion correction techniques applied to functional near-infrared spectroscopy data from children

NASA Astrophysics Data System (ADS)

Hu, Xiao-Su; Arredondo, Maria M.; Gomba, Megan; Confer, Nicole; DaSilva, Alexandre F.; Johnson, Timothy D.; Shalinsky, Mark; Kovelman, Ioulia

2015-12-01

Motion artifacts are the most significant sources of noise in the context of pediatric brain imaging designs and data analyses, especially in applications of functional near-infrared spectroscopy (fNIRS), in which it can completely affect the quality of the data acquired. Different methods have been developed to correct motion artifacts in fNIRS data, but the relative effectiveness of these methods for data from child and infant subjects (which is often found to be significantly noisier than adult data) remains largely unexplored. The issue is further complicated by the heterogeneity of fNIRS data artifacts. We compared the efficacy of the six most prevalent motion artifact correction techniques with fNIRS data acquired from children participating in a language acquisition task, including wavelet, spline interpolation, principal component analysis, moving average (MA), correlation-based signal improvement, and combination of wavelet and MA. The evaluation of five predefined metrics suggests that the MA and wavelet methods yield the best outcomes. These findings elucidate the varied nature of fNIRS data artifacts and the efficacy of artifact correction methods with pediatric populations, as well as help inform both the theory and practice of optical brain imaging analysis.

Motion-artifact-robust, polarization-resolved second-harmonic-generation microscopy based on rapid polarization switching with electro-optic Pockells cell and its application to in vivo visualization of collagen fiber orientation in human facial skin

PubMed Central

Tanaka, Yuji; Hase, Eiji; Fukushima, Shuichiro; Ogura, Yuki; Yamashita, Toyonobu; Hirao, Tetsuji; Araki, Tsutomu; Yasui, Takeshi

2014-01-01

Polarization-resolved second-harmonic-generation (PR-SHG) microscopy is a powerful tool for investigating collagen fiber orientation quantitatively with low invasiveness. However, the waiting time for the mechanical polarization rotation makes it too sensitive to motion artifacts and hence has hampered its use in various applications in vivo. In the work described in this article, we constructed a motion-artifact-robust, PR-SHG microscope based on rapid polarization switching at every pixel with an electro-optic Pockells cell (PC) in synchronization with step-wise raster scanning of the focus spot and alternate data acquisition of a vertical-polarization-resolved SHG signal and a horizontal-polarization-resolved one. The constructed PC-based PR-SHG microscope enabled us to visualize orientation mapping of dermal collagen fiber in human facial skin in vivo without the influence of motion artifacts. Furthermore, it implied the location and/or age dependence of the collagen fiber orientation in human facial skin. The robustness to motion artifacts in the collagen orientation measurement will expand the application scope of SHG microscopy in dermatology and collagen-related fields. PMID:24761292

A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.

PubMed

Sengottuvel, S; Khan, Pathan Fayaz; Mariyappa, N; Patel, Rajesh; Saipriya, S; Gireesan, K

2018-06-01

Cutaneous measurements of electrogastrogram (EGG) signals are heavily contaminated by artifacts due to cardiac activity, breathing, motion artifacts, and electrode drifts whose effective elimination remains an open problem. A common methodology is proposed by combining independent component analysis (ICA) and ensemble empirical mode decomposition (EEMD) to denoise gastric slow-wave signals in multichannel EGG data. Sixteen electrodes are fixed over the upper abdomen to measure the EGG signals under three gastric conditions, namely, preprandial, postprandial immediately, and postprandial 2 h after food for three healthy subjects and a subject with a gastric disorder. Instantaneous frequencies of intrinsic mode functions that are obtained by applying the EEMD technique are analyzed to individually identify and remove each of the artifacts. A critical investigation on the proposed ICA-EEMD method reveals its ability to provide a higher attenuation of artifacts and lower distortion than those obtained by the ICA-EMD method and conventional techniques, like bandpass and adaptive filtering. Characteristic changes in the slow-wave frequencies across the three gastric conditions could be determined from the denoised signals for all the cases. The results therefore encourage the use of the EEMD-based technique for denoising gastric signals to be used in clinical practice.

Radial Ultrashort TE Imaging Removes the Need for Breath-Holding in Hepatic Iron Overload Quantification by R2* MRI.

PubMed

Tipirneni-Sajja, Aaryani; Krafft, Axel J; McCarville, M Beth; Loeffler, Ralf B; Song, Ruitian; Hankins, Jane S; Hillenbrand, Claudia M

2017-07-01

The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers. FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2* maps were calculated, and mean liver R2* values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis. FB multiecho GRE images displayed motion artifacts and significantly lower R2* values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2* maps, and mean R2* values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2* CV that was approximately twofold higher than the R2* CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2* CV was relatively constant over the range of R2* values for FB multiecho UTE, but it increased with increases in R2* for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2* estimation with increasing iron burden. FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2* estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment in sedated children and patients who cannot complete BH maneuvers.

Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

PubMed

Mannan, Malik M Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M Ahmad

2016-02-19

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

A novel CT acquisition and analysis technique for breathing motion modeling

NASA Astrophysics Data System (ADS)

Low, Daniel A.; White, Benjamin M.; Lee, Percy P.; Thomas, David H.; Gaudio, Sergio; Jani, Shyam S.; Wu, Xiao; Lamb, James M.

2013-06-01

To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.

Elimination of motion and pulsation artifacts using BLADE sequences in knee MR imaging.

PubMed

Lavdas, Eleftherios; Mavroidis, Panayiotis; Hatzigeorgiou, Vasiliki; Roka, Violeta; Arikidis, Nikos; Oikonomou, Georgia; Andrianopoulos, Konstantinos; Notaras, Ioannis

2012-10-01

The purpose of this study is to evaluate the ability of proton density (PD)-BLADE sequences in reducing or even eliminating motion and pulsatile flow artifacts in knee magnetic resonance imaging examinations. Eighty consecutive patients, who had been routinely scanned for knee examination, participated in the study. The following pairs of sequences with and without BLADE were compared: (a) PD turbo spin echo (TSE) sagittal (SAG) fat saturation (FS) in 35 patients, (b) PD TSE coronal (COR) FS in 19 patients, (c) T2 TSE axial in 13 patients and (d) PD TSE SAG in 13 patients. Both qualitative and quantitative analyses were performed based on the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (ReCon) measures of normal anatomic structures. The qualitative analysis was performed by experienced radiologists. Also, the presence of image motion and pulsation artifacts was evaluated. Based on the results of the SNR, CRN and ReCon for the different sequences and anatomical structures, the BLADE sequences were significantly superior in 19 cases, whereas the corresponding conventional sequences were significantly superior in only 6 cases. BLADE sequences eliminated motion artifacts in all the cases. However, motion artifacts were shown in (a) six PD TSE SAG FS, (b) three PD TSE COR FS, (c) three PD TSE SAG and (d) two T2 TSE axial conventional sequences. In our results, it was found that, in PD FS sequences (sagittal and coronal), the differences between the BLADE and conventional sequences regarding the elimination of motion and pulsatile flow artifacts were statistically significant. In all the comparisons, the PD FS BLADE sequences (coronal and sagittal) were significantly superior to the corresponding conventional sequences regarding the classification of their image quality. In conclusion, this technique appears to be capable to potentially eliminate motion and pulsatile flow artifacts in MR images. Copyright © 2012 Elsevier Inc. All rights reserved.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

PubMed

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

2013-04-01

Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a lung cancer patient by comparing the synthesized images and the original images at different phases. The synthesized images matched well with the original images. The motion model was used to reduce irregular motion artifacts in the 4D CT images of three lung cancer patients. Visual assessment indicated that the proposed approach could reduce severe image artifacts. The shape distortions around the diaphragm and tumor regions were mitigated in the synthesized 4D CT images. The authors have derived a mathematical model to represent the regular respiratory motion from a patient-specific 4D CT set and have demonstrated its application in reducing irregular motion artifacts in 4D CT images. The authors' approach can mitigate shape distortions of anatomy caused by irregular breathing motion during 4D CT acquisition.

Miscellaneous artifacts relating to experiments with talking motion pictures about ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Miscellaneous artifacts relating to experiments with talking motion pictures about 1912 and to loudspeaking phonographs in the 1920s, third floor. - Thomas A. Edison Laboratories, Building No. 5, Main Street & Lakeside Avenue, West Orange, Essex County, NJ

Recent progress and outstanding issues in motion correction in resting state fMRI

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Petersen, Steven E

2014-01-01

The purpose of this review is to communicate and synthesize recent findings related to motion artifact in resting state fMRI. In 2011, three groups reported that small head movements produced spurious but structured noise in brain scans, causing distance-dependent changes in signal correlations. This finding has prompted both methods development and the re-examination of prior findings with more stringent motion correction. Since 2011, over a dozen papers have been published specifically on motion artifact in resting state fMRI. We will attempt to distill these papers to their most essential content. We will point out some aspects of motion artifact that are easily or often overlooked. Throughout the review, we will highlight gaps in current knowledge and avenues for future research. PMID:25462692

Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

PubMed

Sai, Chong Yeh; Mokhtar, Norrima; Arof, Hamzah; Cumming, Paul; Iwahashi, Masahiro

2018-05-01

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applications. In recent years, a combination of independent component analysis (ICA) and discrete wavelet transform has been introduced as standard technique for EEG artifact removal. However, in performing the wavelet-ICA procedure, visual inspection or arbitrary thresholding may be required for identifying artifactual components in the EEG signal. We now propose a novel approach for identifying artifactual components separated by wavelet-ICA using a pretrained support vector machine (SVM). Our method presents a robust and extendable system that enables fully automated identification and removal of artifacts from EEG signals, without applying any arbitrary thresholding. Using test data contaminated by eye blink artifacts, we show that our method performed better in identifying artifactual components than did existing thresholding methods. Furthermore, wavelet-ICA in conjunction with SVM successfully removed target artifacts, while largely retaining the EEG source signals of interest. We propose a set of features including kurtosis, variance, Shannon's entropy, and range of amplitude as training and test data of SVM to identify eye blink artifacts in EEG signals. This combinatorial method is also extendable to accommodate multiple types of artifacts present in multichannel EEG. We envision future research to explore other descriptive features corresponding to other types of artifactual components.

Removal of ring artifacts in microtomography by characterization of scintillator variations.

PubMed

Vågberg, William; Larsson, Jakob C; Hertz, Hans M

2017-09-18

Ring artifacts reduce image quality in tomography, and arise from faulty detector calibration. In microtomography, we have identified that ring artifacts can arise due to high-spatial frequency variations in the scintillator thickness. Such variations are normally removed by a flat-field correction. However, as the spectrum changes, e.g. due to beam hardening, the detector response varies non-uniformly introducing ring artifacts that persist after flat-field correction. In this paper, we present a method to correct for ring artifacts from variations in scintillator thickness by using a simple method to characterize the local scintillator response. The method addresses the actual physical cause of the ring artifacts, in contrary to many other ring artifact removal methods which rely only on image post-processing. By applying the technique to an experimental phantom tomography, we show that ring artifacts are strongly reduced compared to only making a flat-field correction.

Effect of Non-Alignment/Alignment of Attenuation Map Without/With Emission Motion Correction in Cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Dey, Joyoni; Segars, W. Paul; Pretorius, P. Hendrik; King, Michael A.

2015-08-01

Purpose: We investigate the differences without/with respiratory motion correction in apparent imaging agent localization induced in reconstructed emission images when the attenuation maps used for attenuation correction (from CT) are misaligned with the patient anatomy during emission imaging due to differences in respiratory state. Methods: We investigated use of attenuation maps acquired at different states of a 2 cm amplitude respiratory cycle (at end-expiration, at end-inspiration, the center map, the average transmission map, and a large breath-hold beyond range of respiration during emission imaging) to correct for attenuation in MLEM reconstruction for several anatomical variants of the NCAT phantom which included both with and without non-rigid motion between heart and sub-diaphragmatic regions (such as liver, kidneys etc). We tested these cases with and without emission motion correction and attenuation map alignment/non-alignment. Results: For the NCAT default male anatomy the false count-reduction due to breathing was largely removed upon emission motion correction for the large majority of the cases. Exceptions (for the default male) were for the cases when using the large-breathhold end-inspiration map (TI_EXT), when we used the end-expiration (TE) map, and to a smaller extent, the end-inspiration map (TI). However moving the attenuation maps rigidly to align the heart region, reduced the remaining count-reduction artifacts. For the female patient count-reduction remained post motion correction using rigid map-alignment due to the breast soft-tissue misalignment. Quantitatively, after the transmission (rigid) alignment correction, the polar-map 17-segment RMS error with respect to the reference (motion-less case) reduced by 46.5% on average for the extreme breathhold case. The reductions were 40.8% for end-expiration map and 31.9% for end-inspiration cases on the average, comparable to the semi-ideal case where each state uses its own attenuation map for correction. Conclusions: Two main conclusions are that even rigid emission motion correction to rigidly align the heart region to the attenuation map helps in average cases to reduce the count-reduction artifacts and secondly, within the limits of the study (ex. rigid correction) when there is lung tissue inferior to the heart as with the NCAT phantom employed in this study end-expiration maps (TE) might best be avoided as they may create more artifacts than the end-inspiration (TI) maps.

TH-CD-207B-03: How to Quantify Temporal Resolution in X-Ray MDCT Imaging?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Budde, A; GE Healthcare Technologies, Madison, WI; Li, Y

Purpose: In modern CT scanners, a quantitative metric to assess temporal response, namely, to quantify the temporal resolution (TR), remains elusive. Rough surrogate metrics, such as half of the gantry rotation time for single source CT, a quarter of the gantry rotation time for dual source CT, or measurements of motion artifact’s size, shape, or intensity have previously been used. In this work, a rigorous framework which quantifies TR and a practical measurement method are developed. Methods: A motion phantom was simulated which consisted of a single rod that is in motion except during a static period at the temporalmore » center of the scan, termed the TR window. If the image of the motion scan has negligible motion artifacts compared to an image from a totally static scan, then the system has a TR no worse than the TR window used. By repeating this comparison with varying TR windows, the TR of the system can be accurately determined. Motion artifacts were also visually assessed and the TR was measured across varying rod motion speeds, directions, and locations. Noiseless fan beam acquisitions were simulated and images were reconstructed with a short-scan image reconstruction algorithm. Results: The size, shape, and intensity of motion artifacts varied when the rod speed, direction, or location changed. TR measured using the proposed method, however, was consistent across rod speeds, directions, and locations. Conclusion: Since motion artifacts vary depending upon the motion speed, direction, and location, they are not suitable for measuring TR. In this work, a CT system with a specified TR is defined as having the ability to produce a static image with negligible motion artifacts, no matter what motion occurs outside of a static window of width TR. This framework allows for practical measurement of temporal resolution in clinical CT imaging systems. Funding support: GE Healthcare; Conflict of Interest: Employee, GE Healthcare.« less

Artifact removal in the context of group ICA: a comparison of single-subject and group approaches

PubMed Central

Du, Yuhui; Allen, Elena A.; He, Hao; Sui, Jing; Wu, Lei; Calhoun, Vince D.

2018-01-01

Independent component analysis (ICA) has been widely applied to identify intrinsic brain networks from fMRI data. Group ICA computes group-level components from all data and subsequently estimates individual-level components to recapture inter-subject variability. However, the best approach to handle artifacts, which may vary widely among subjects, is not yet clear. In this work, we study and compare two ICA approaches for artifacts removal. One approach, recommended in recent work by the Human Connectome Project, first performs ICA on individual subject data to remove artifacts, and then applies a group ICA on the cleaned data from all subjects. We refer to this approach as Individual ICA based artifacts Removal Plus Group ICA (IRPG). A second proposed approach, called Group Information Guided ICA (GIG-ICA), performs ICA on group data, then removes the group-level artifact components, and finally performs subject-specific ICAs using the group-level non-artifact components as spatial references. We used simulations to evaluate the two approaches with respect to the effects of data quality, data quantity, variable number of sources among subjects, and spatially unique artifacts. Resting-state test-retest datasets were also employed to investigate the reliability of functional networks. Results from simulations demonstrate GIG-ICA has greater performance compared to IRPG, even in the case when single-subject artifacts removal is perfect and when individual subjects have spatially unique artifacts. Experiments using test-retest data suggest that GIG-ICA provides more reliable functional networks. Based on high estimation accuracy, ease of implementation, and high reliability of functional networks, we find GIG-ICA to be a promising approach. PMID:26859308

Tissue artifact removal from respiratory signals based on empirical mode decomposition.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-05-01

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.

Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

PubMed Central

Mannan, Malik M. Naeem; Kim, Shinjung; Jeong, Myung Yung; Kamran, M. Ahmad

2016-01-01

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI). In this paper, we proposed an automatic framework based on independent component analysis (ICA) and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data. PMID:26907276

A head motion estimation algorithm for motion artifact correction in dental CT imaging

NASA Astrophysics Data System (ADS)

Hernandez, Daniel; Elsayed Eldib, Mohamed; Hegazy, Mohamed A. A.; Hye Cho, Myung; Cho, Min Hyoung; Lee, Soo Yeol

2018-03-01

A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.

Recent progress and outstanding issues in motion correction in resting state fMRI.

PubMed

Power, Jonathan D; Schlaggar, Bradley L; Petersen, Steven E

2015-01-15

The purpose of this review is to communicate and synthesize recent findings related to motion artifact in resting state fMRI. In 2011, three groups reported that small head movements produced spurious but structured noise in brain scans, causing distance-dependent changes in signal correlations. This finding has prompted both methods development and the re-examination of prior findings with more stringent motion correction. Since 2011, over a dozen papers have been published specifically on motion artifact in resting state fMRI. We will attempt to distill these papers to their most essential content. We will point out some aspects of motion artifact that are easily or often overlooked. Throughout the review, we will highlight gaps in current knowledge and avenues for future research. Copyright © 2014 Elsevier Inc. All rights reserved.

Elimination of motion, pulsatile flow and cross-talk artifacts using blade sequences in lumbar spine MR imaging.

PubMed

Lavdas, Eleftherios; Mavroidis, Panayiotis; Kostopoulos, Spiros; Glotsos, Dimitrios; Roka, Violeta; Koutsiaris, Aristotle G; Batsikas, Georgios; Sakkas, Georgios K; Tsagkalis, Antonios; Notaras, Ioannis; Stathakis, Sotirios; Papanikolaou, Nikos; Vassiou, Katerina

2013-07-01

The purpose of this study is to evaluate the ability of T2 turbo spin echo (TSE) axial and sagittal BLADE sequences in reducing or even eliminating motion, pulsatile flow and cross-talk artifacts in lumbar spine MRI examinations. Forty four patients, who had routinely undergone a lumbar spine examination, participated in the study. The following pairs of sequences with and without BLADE were compared: a) T2 TSE Sagittal (SAG) in thirty two cases, and b) T2 TSE Axial (AX) also in thirty two cases. Both quantitative and qualitative analyses were performed based on measurements in different normal anatomical structures and examination of seven characteristics, respectively. The qualitative analysis was performed by experienced radiologists. Also, the presence of image motion, pulsatile flow and cross-talk artifacts was evaluated. Based on the results of the qualitative analysis for the different sequences and anatomical structures, the BLADE sequences were found to be significantly superior to the conventional ones in all the cases. The BLADE sequences eliminated the motion artifacts in all the cases. In our results, it was found that in the examined sequences (sagittal and axial) the differences between the BLADE and conventional sequences regarding the elimination of motion, pulsatile flow and cross-talk artifacts were statistically significant. In all the comparisons, the T2 TSE BLADE sequences were significantly superior to the corresponding conventional sequences regarding the classification of their image quality. In conclusion, this technique appears to be capable of potentially eliminating motion, pulsatile flow and cross-talk artifacts in lumbar spine MR images and producing high quality images in collaborative and non-collaborative patients. Copyright © 2013 Elsevier Inc. All rights reserved.

Correcting for motion artifact in handheld laser speckle images

NASA Astrophysics Data System (ADS)

Lertsakdadet, Ben; Yang, Bruce Y.; Dunn, Cody E.; Ponticorvo, Adrien; Crouzet, Christian; Bernal, Nicole; Durkin, Anthony J.; Choi, Bernard

2018-03-01

Laser speckle imaging (LSI) is a wide-field optical technique that enables superficial blood flow quantification. LSI is normally performed in a mounted configuration to decrease the likelihood of motion artifact. However, mounted LSI systems are cumbersome and difficult to transport quickly in a clinical setting for which portability is essential in providing bedside patient care. To address this issue, we created a handheld LSI device using scientific grade components. To account for motion artifact of the LSI device used in a handheld setup, we incorporated a fiducial marker (FM) into our imaging protocol and determined the difference between highest and lowest speckle contrast values for the FM within each data set (Kbest and Kworst). The difference between Kbest and Kworst in mounted and handheld setups was 8% and 52%, respectively, thereby reinforcing the need for motion artifact quantification. When using a threshold FM speckle contrast value (KFM) to identify a subset of images with an acceptable level of motion artifact, mounted and handheld LSI measurements of speckle contrast of a flow region (KFLOW) in in vitro flow phantom experiments differed by 8%. Without the use of the FM, mounted and handheld KFLOW values differed by 20%. To further validate our handheld LSI device, we compared mounted and handheld data from an in vivo porcine burn model of superficial and full thickness burns. The speckle contrast within the burn region (KBURN) of the mounted and handheld LSI data differed by <4 % when accounting for motion artifact using the FM, which is less than the speckle contrast difference between superficial and full thickness burns. Collectively, our results suggest the potential of handheld LSI with an FM as a suitable alternative to mounted LSI, especially in challenging clinical settings with space limitations such as the intensive care unit.

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in realtime. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan A.

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in real-time. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors.

Iterative image-domain ring artifact removal in cone-beam CT

NASA Astrophysics Data System (ADS)

Liang, Xiaokun; Zhang, Zhicheng; Niu, Tianye; Yu, Shaode; Wu, Shibin; Li, Zhicheng; Zhang, Huailing; Xie, Yaoqin

2017-07-01

Ring artifacts in cone beam computed tomography (CBCT) images are caused by pixel gain variations using flat-panel detectors, and may lead to structured non-uniformities and deterioration of image quality. The purpose of this study is to propose a method of general ring artifact removal in CBCT images. This method is based on the polar coordinate system, where the ring artifacts manifest as stripe artifacts. Using relative total variation, the CBCT images are first smoothed to generate template images with fewer image details and ring artifacts. By subtracting the template images from the CBCT images, residual images with image details and ring artifacts are generated. As the ring artifact manifests as a stripe artifact in a polar coordinate system, the artifact image can be extracted by mean value from the residual image; the image details are generated by subtracting the artifact image from the residual image. Finally, the image details are compensated to the template image to generate the corrected images. The proposed framework is iterated until the differences in the extracted ring artifacts are minimized. We use a 3D Shepp-Logan phantom, Catphan©504 phantom, uniform acrylic cylinder, and images from a head patient to evaluate the proposed method. In the experiments using simulated data, the spatial uniformity is increased by 1.68 times and the structural similarity index is increased from 87.12% to 95.50% using the proposed method. In the experiment using clinical data, our method shows high efficiency in ring artifact removal while preserving the image structure and detail. The iterative approach we propose for ring artifact removal in cone-beam CT is practical and attractive for CBCT guided radiation therapy.

Adaptive Filtration of Physiological Artifacts in EEG Signals in Humans Using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Grubov, V. V.; Runnova, A. E.; Hramov, A. E.

2018-05-01

A new method for adaptive filtration of experimental EEG signals in humans and for removal of different physiological artifacts has been proposed. The algorithm of the method includes empirical mode decomposition of EEG, determination of the number of empirical modes that are considered, analysis of the empirical modes and search for modes that contains artifacts, removal of these modes, and reconstruction of the EEG signal. The method was tested on experimental human EEG signals and demonstrated high efficiency in the removal of different types of physiological EEG artifacts.

SU-E-I-51: Use of Blade Sequences in Cervical Spine MR Imaging for Eliminating Motion, Truncation and Flow Artifacts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavroidis, P; Lavdas, E; Kostopoulos, S

Purpose: To assess the efficacy of the BLADE technique to eliminate motion, truncation, flow and other artifacts in Cervical Spine MRI compared to the conventional technique. To study the ability of the examined sequences to reduce the indetention and wrap artifacts, which have been reported in BLADE sagittal sequences. Methods: Forty consecutive subjects, who had been routinely scanned for cervical spine examination using four different image acquisition techniques, were analyzed. More specifically, the following pairs of sequences were compared: a) T2 TSE SAG vs. T2 TSE SAG BLADE and b) T2 TIRM SAG vs. T2 TIRM SAG BLADE. A quantitativemore » analysis was performed using the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (ReCon) measures. A qualitative analysis was also performed by two radiologists, who graded seven image characteristics on a 5-point scale (0:non-visualization; 1:poor; 2:average; 3:good; 4:excellent). The observers also evaluated the presence of image artifacts (motion, truncation, flow, indentation). Results: Based on the findings of the quantitative analysis, the ReCON values of the CSF (cerebrospinal fluid)/SC (spinal cord) between TIRM SAG and TIRM SAG BLADE were found to present statistical significant differences (p<0.001). Regarding motion and truncation artifacts, the T2 TSE SAG BLADE was superior compared to the T2 TSE SAG and the T2 TIRM SAG BLADE was superior compared to the T2 TIRM SAG. Regarding flow artifacts, T2 TIRM SAG BLADE eliminated more artifacts compared to the T2 TIRM SAG. Conclusion: The use of BLADE sequences in cervical spine MR examinations appears to be capable of potentially eliminating motion, pulsatile flow and trancation artifacts. Furthermore, BLADE sequences are proposed to be used in the standard examination protocols based on the fact that a significantly improved image quality could be achieved.« less

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

PubMed

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

Detection of motion artifact patterns in photoplethysmographic signals based on time and period domain analysis.

PubMed

Couceiro, R; Carvalho, P; Paiva, R P; Henriques, J; Muehlsteff, J

2014-12-01

The presence of motion artifacts in photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection based on the analysis of the variations in the time and the period domain characteristics of the PPG signal. The extracted features are ranked using a normalized mutual information feature selection algorithm and the best features are used in a support vector machine classification model to distinguish between clean and corrupted sections of the PPG signal. The proposed method has been tested in healthy and cardiovascular diseased volunteers, considering 11 different motion artifact sources. The results achieved by the current algorithm (sensitivity--SE: 84.3%, specificity--SP: 91.5% and accuracy--ACC: 88.5%) show that the current methodology is able to identify both corrupted and clean PPG sections with high accuracy in both healthy (ACC: 87.5%) and cardiovascular diseases (ACC: 89.5%) context.

Reduction of thoracic aorta motion artifact with high-pitch 128-slice dual-source computed tomographic angiography: a historical control study.

PubMed

Nakagawa, Junichiro; Tasaki, Osamu; Watanabe, Yoshiyuki; Azuma, Takeo; Ohnishi, Mitsuo; Ukai, Isao; Tahara, Kenichi; Ogura, Hiroshi; Kuwagata, Yasuyuki; Hamasaki, Toshimitsu; Shimazu, Takeshi

2013-01-01

Electrocardiogram-gated imaging combined with multi-detector row computed tomography (MDCT) has reduced cardiac motion artifacts, but it was not practical in the emergency setting. The purpose of this study was to evaluate the ability of a high-pitch, 128-slice dual-source CT (DSCT) scanner to reduce motion artifacts in patients admitted to the emergency room. This study comprised 100 patients suspected of having thoracic aorta lesions. We examined 47 patients with the 128-slice DSCT scanner (DSCT group), and 53 patients were examined with a 64-slice MDCT scanner (MDCT group). Six anatomic areas in the thoracic aorta were evaluated. Computed tomography images in the DSCT group were distinct, and significant differences were observed in images of all areas between the 2 groups except for the descending aorta. The high-pitch DSCT scanner can reduce motion artifacts of the thoracic aorta and enable radiological diagnosis even in patients with tachycardia and without breath hold.

A review of the latest guidelines for NIBP device validation.

PubMed

Alpert, Bruce S; Quinn, David E; Friedman, Bruce A

2013-12-01

The current ISO Standard is accepted as the National Standard in almost every industrialized nation. An overview of the most recently adopted standards is provided. Standards writing groups including the Advancement of Medical Instrumentation Sphygmomanometer Committee and ISO JWG7 are working to expand standardized evaluation methods to include the evaluation of devices intended for use in environments where motion artifact is common. An Association for the Advancement of Medical Instrumentation task group on noninvasive blood pressure measurement in the presence of motion artifact has published a technical information report containing research and standardized methods for the evaluation of blood pressure device performance in the presence of motion artifact.

Automatic motion correction of clinical shoulder MR images

NASA Astrophysics Data System (ADS)

Manduca, Armando; McGee, Kiaran P.; Welch, Edward B.; Felmlee, Joel P.; Ehman, Richard L.

1999-05-01

A technique for the automatic correction of motion artifacts in MR images was developed. The algorithm uses only the raw (complex) data from the MR scanner, and requires no knowledge of the patient motion during the acquisition. It operates by searching over the space of possible patient motions and determining the motion which, when used to correct the image, optimizes the image quality. The performance of this algorithm was tested in coronal images of the rotator cuff in a series of 144 patients. A four observer comparison of the autocorrelated images with the uncorrected images demonstrated that motion artifacts were significantly reduced in 48% of the cases. The improvements in image quality were similar to those achieved with a previously reported navigator echo-based adaptive motion correction. The results demonstrate that autocorrelation is a practical technique for retrospectively reducing motion artifacts in a demanding clinical MRI application. It achieves performance comparable to a navigator based correction technique, which is significant because autocorrection does not require an imaging sequence that has been modified to explicitly track motion during acquisition. The approach is flexible and should be readily extensible to other types of MR acquisitions that are corrupted by global motion.

Adaptive Registration of Varying Contrast-Weighted Images for Improved Tissue Characterization (ARCTIC): Application to T1 Mapping

PubMed Central

Roujol, Sébastien; Foppa, Murilo; Weingartner, Sebastian; Manning, Warren J.; Nezafat, Reza

2014-01-01

Purpose To propose and evaluate a novel non-rigid image registration approach for improved myocardial T1 mapping. Methods Myocardial motion is estimated as global affine motion refined by a novel local non-rigid motion estimation algorithm. A variational framework is proposed, which simultaneously estimates motion field and intensity variations, and uses an additional regularization term to constrain the deformation field using automatic feature tracking. The method was evaluated in 29 patients by measuring the DICE similarity coefficient (DSC) and the myocardial boundary error (MBE) in short axis and four chamber data. Each image series was visually assessed as “no motion” or “with motion”. Overall T1 map quality and motion artifacts were assessed in the 85 T1 maps acquired in short axis view using a 4-point scale (1-non diagnostic/severe motion artifact, 4-excellent/no motion artifact). Results Increased DSC (0.78±0.14 to 0.87±0.03, p<0.001), reduced MBE (1.29±0.72mm to 0.84±0.20mm, p<0.001), improved overall T1 map quality (2.86±1.04 to 3.49±0.77, p<0.001), and reduced T1 map motion artifacts (2.51±0.84 to 3.61±0.64, p<0.001) were obtained after motion correction of “with motion” data (~56% of data). Conclusion The proposed non-rigid registration approach reduces the respiratory-induced motion that occurs during breath-hold T1 mapping, and significantly improves T1 map quality. PMID:24798588

Statistical Feature Extraction for Artifact Removal from Concurrent fMRI-EEG Recordings

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H.

2011-01-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphases are directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use a channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable by the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. PMID:22036675

Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

PubMed

Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H

2012-02-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.

Body MR Imaging: Artifacts, k-Space, and Solutions

PubMed Central

Seethamraju, Ravi T.; Patel, Pritesh; Hahn, Peter F.; Kirsch, John E.; Guimaraes, Alexander R.

2015-01-01

Body magnetic resonance (MR) imaging is challenging because of the complex interaction of multiple factors, including motion arising from respiration and bowel peristalsis, susceptibility effects secondary to bowel gas, and the need to cover a large field of view. The combination of these factors makes body MR imaging more prone to artifacts, compared with imaging of other anatomic regions. Understanding the basic MR physics underlying artifacts is crucial to recognizing the trade-offs involved in mitigating artifacts and improving image quality. Artifacts can be classified into three main groups: (a) artifacts related to magnetic field imperfections, including the static magnetic field, the radiofrequency (RF) field, and gradient fields; (b) artifacts related to motion; and (c) artifacts arising from methods used to sample the MR signal. Static magnetic field homogeneity is essential for many MR techniques, such as fat saturation and balanced steady-state free precession. Susceptibility effects become more pronounced at higher field strengths and can be ameliorated by using spin-echo sequences when possible, increasing the receiver bandwidth, and aligning the phase-encoding gradient with the strongest susceptibility gradients, among other strategies. Nonuniformities in the RF transmit field, including dielectric effects, can be minimized by applying dielectric pads or imaging at lower field strength. Motion artifacts can be overcome through respiratory synchronization, alternative k-space sampling schemes, and parallel imaging. Aliasing and truncation artifacts derive from limitations in digital sampling of the MR signal and can be rectified by adjusting the sampling parameters. Understanding the causes of artifacts and their possible solutions will enable practitioners of body MR imaging to meet the challenges of novel pulse sequence design, parallel imaging, and increasing field strength. ©RSNA, 2015 PMID:26207581

Quantifying and correcting motion artifacts in MRI

NASA Astrophysics Data System (ADS)

Bones, Philip J.; Maclaren, Julian R.; Millane, Rick P.; Watts, Richard

2006-08-01

Patient motion during magnetic resonance imaging (MRI) can produce significant artifacts in a reconstructed image. Since measurements are made in the spatial frequency domain ('k-space'), rigid-body translational motion results in phase errors in the data samples while rotation causes location errors. A method is presented to detect and correct these errors via a modified sampling strategy, thereby achieving more accurate image reconstruction. The strategy involves sampling vertical and horizontal strips alternately in k-space and employs phase correlation within the overlapping segments to estimate translational motion. An extension, also based on correlation, is employed to estimate rotational motion. Results from simulations with computer-generated phantoms suggest that the algorithm is robust up to realistic noise levels. The work is being extended to physical phantoms. Provided that a reference image is available and the object is of limited extent, it is shown that a measure related to the amount of energy outside the support can be used to objectively compare the severity of motion-induced artifacts.

A configurable and low-power mixed signal SoC for portable ECG monitoring applications.

PubMed

Kim, Hyejung; Kim, Sunyoung; Van Helleputte, Nick; Artes, Antonio; Konijnenburg, Mario; Huisken, Jos; Van Hoof, Chris; Yazicioglu, Refet Firat

2014-04-01

This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel electrode-tissue-impedance (ETI) measurement with high signal quality. This can be used to evaluate the quality of the ECG measurement and to filter motion artifacts. A custom digital signal processor consisting of 4-way SIMD processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. A built-in 12-bit analog-to-digital converter (ADC) is capable of adaptive sampling achieving a compression ratio of up to 7, and loop buffer integration reduces the power consumption for on-chip memory access. The SoC is implemented in 0.18 μm CMOS process and consumes 32 μ W from a 1.2 V while heart beat detection application is running, and integrated in a wireless ECG monitoring system with Bluetooth protocol. Thanks to the ECG SoC, the overall system power consumption can be reduced significantly.

A biomechanical modeling guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2017-03-01

Four-dimensional (4D) cone-beam computed tomography (CBCT) enables motion tracking of anatomical structures and removes artifacts introduced by motion. However, the imaging time/dose of 4D-CBCT is substantially longer/higher than traditional 3D-CBCT. We previously developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, to reconstruct high-quality 4D-CBCT from limited number of projections to reduce the imaging time/dose. However, the accuracy of SMEIR is limited in reconstructing low-contrast regions with fine structure details. In this study, we incorporate biomechanical modeling into the SMEIR algorithm (SMEIR-Bio), to improve the reconstruction accuracy at low-contrast regions with fine details. The efficacy of SMEIR-Bio is evaluated using 11 lung patient cases and compared to that of the original SMEIR algorithm. Qualitative and quantitative comparisons showed that SMEIR-Bio greatly enhances the accuracy of reconstructed 4D-CBCT volume in low-contrast regions, which can potentially benefit multiple clinical applications including the treatment outcome analysis.

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

PubMed

Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S

2012-06-01

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data. © 2012 American Association of Physicists in Medicine.

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

PubMed

Cai, Xiaoying; Epstein, Frederick H

2018-04-01

This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T 1 -relaxation echo and blurring. The method identifies phase-cycled spiral interleaves at matched respiratory phases by minimizing the residual signal due to T 1 relaxation after phase-cycling subtraction. Next, the method reconstructs image-based navigators from matched phase-cycled interleaves that are comprised of the stimulated echo (ste-iNAVs). Ste-iNAVs are used for motion estimation and compensation of k-space data. The method was demonstrated in phantoms and compared to diaphragm-based navigator (dNAV) and conventional iNAV (c-iNAV) methods for the reconstruction of free-breathing volunteer data sets (N = 10). Phantom experiments demonstrated that the proposed method removes striping artifacts and blurring due to motion. Volunteer results showed that respiratory motion measured by ste-iNAVs was better correlated than c-iNAVs to dNAV data (R 2  = 0.82 ± 0.03 vs. 0.70 ± 0.05, P < 0.05). Match-making reconstructions of free-breathing data sets achieved lower residual T 1 -relaxation echo energy (1.04 ± 0.01 vs. 1.18 ± 0.04 for dNAV and 1.18 ± 0.03 for c-iNAV, P < 0.05), higher apparent SNR (11.93 ± 1.05 vs. 10.68 ± 1.06 for dNAV and 10.66 ± 0.99 for c-iNAV, P < 0.05), and better phase quality (0.147 ± 0.012 vs. 0.166 ± 0.017 for dNAV, P = 0.06, and 0.168 ± 0.015 for c-iNAV, P < 0.05) than dNAV and c-iNAV methods. For free-breathing cine DENSE, the proposed method addresses both types of breathing-induced artifacts and provides better quality images than conventional dNAV and iNAV methods. © 2018 International Society for Magnetic Resonance in Medicine.

Artifact removal from EEG signals using adaptive filters in cascade

NASA Astrophysics Data System (ADS)

Garcés Correa, A.; Laciar, E.; Patiño, H. D.; Valentinuzzi, M. E.

2007-11-01

Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.

Negligible Motion Artifacts in Scalp Electroencephalography (EEG) During Treadmill Walking.

PubMed

Nathan, Kevin; Contreras-Vidal, Jose L

2015-01-01

Recent mobile brain/body imaging (MoBI) techniques based on active electrode scalp electroencephalogram (EEG) allow the acquisition and real-time analysis of brain dynamics during active unrestrained motor behavior involving whole body movements such as treadmill walking, over-ground walking and other locomotive and non-locomotive tasks. Unfortunately, MoBI protocols are prone to physiological and non-physiological artifacts, including motion artifacts that may contaminate the EEG recordings. A few attempts have been made to quantify these artifacts during locomotion tasks but with inconclusive results due in part to methodological pitfalls. In this paper, we investigate the potential contributions of motion artifacts in scalp EEG during treadmill walking at three different speeds (1.5, 3.0, and 4.5 km/h) using a wireless 64 channel active EEG system and a wireless inertial sensor attached to the subject's head. The experimental setup was designed according to good measurement practices using state-of-the-art commercially available instruments, and the measurements were analyzed using Fourier analysis and wavelet coherence approaches. Contrary to prior claims, the subjects' motion did not significantly affect their EEG during treadmill walking although precaution should be taken when gait speeds approach 4.5 km/h. Overall, these findings suggest how MoBI methods may be safely deployed in neural, cognitive, and rehabilitation engineering applications.

Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

NASA Astrophysics Data System (ADS)

Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

2005-03-01

A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

PubMed

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

Quality evaluation of motion-compensated edge artifacts in compressed video.

PubMed

Leontaris, Athanasios; Cosman, Pamela C; Reibman, Amy R

2007-04-01

Little attention has been paid to an impairment common in motion-compensated video compression: the addition of high-frequency (HF) energy as motion compensation displaces blocking artifacts off block boundaries. In this paper, we employ an energy-based approach to measure this motion-compensated edge artifact, using both compressed bitstream information and decoded pixels. We evaluate the performance of our proposed metric, along with several blocking and blurring metrics, on compressed video in two ways. First, ordinal scales are evaluated through a series of expectations that a good quality metric should satisfy: the objective evaluation. Then, the best performing metrics are subjectively evaluated. The same subjective data set is finally used to obtain interval scales to gain more insight. Experimental results show that we accurately estimate the percentage of the added HF energy in compressed video.

Non-contact and noise tolerant heart rate monitoring using microwave doppler sensor and range imagery.

PubMed

Matsunag, Daichi; Izumi, Shintaro; Okuno, Keisuke; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

2015-01-01

This paper describes a non-contact and noise-tolerant heart beat monitoring system. The proposed system comprises a microwave Doppler sensor and range imagery using Microsoft Kinect™. The possible application of the proposed system is a driver health monitoring. We introduce the sensor fusion approach to minimize the heart beat detection error. The proposed algorithm can subtract a body motion artifact from Doppler sensor output using time-frequency analysis. The body motion artifact is a crucially important problem for biosignal monitoring using microwave Doppler sensor. The body motion speed is obtainable from range imagery, which has 5-mm resolution at 30-cm distance. Measurement results show that the success rate of the heart beat detection is improved about 75% on average when the Doppler wave is degraded by the body motion artifact.

A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

PubMed

Comtois, Gary; Mendelson, Yitzhak; Ramuka, Piyush

2007-01-01

Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC). Since the fingers are generally more vulnerable to motion artifacts, measurements were performed using a custom forehead-mounted wearable pulse oximeter developed for real-time remote physiological monitoring and triage applications. This study revealed that processing motion-corrupted PPG signals by least mean squares (LMS) and recursive least squares (RLS) algorithms can be effective to reduce SpO2 and HR errors during jogging, but the degree of improvement depends on filter order. Although both algorithms produced similar improvements, implementing the adaptive LMS algorithm is advantageous since it requires significantly less operations.

Reducing 4D CT artifacts using optimized sorting based on anatomic similarity.

PubMed

Johnston, Eric; Diehn, Maximilian; Murphy, James D; Loo, Billy W; Maxim, Peter G

2011-05-01

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion artifacts compared to conventional phase or displacement based sorting. This improved sorting algorithm is a straightforward extension of the two most common 4D CT sorting algorithms.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers

PubMed Central

Yücel, Meryem A.; Selb, Juliette; Boas, David A.; Cash, Sydney S.; Cooper, Robert J.

2013-01-01

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90 % and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case. PMID:23796546

Utility of Electrocardiography (ECG)-Gated Computed Tomography (CT) for Preoperative Evaluations of Thymic Epithelial Tumors.

PubMed

Ozawa, Yoshiyuki; Hara, Masaki; Nakagawa, Motoo; Shibamoto, Yuta

2016-01-01

Preoperative evaluation of invasion to the adjacent organs is important for the thymic epithelial tumors on CT. The purpose of our study was to evaluate the utility of electrocardiography (ECG)-gated CT for assessing thymic epithelial tumors with regard to the motion artifacts produced and the preoperative diagnostic accuracy of the technique. Forty thymic epithelial tumors (36 thymomas and 4 thymic carcinomas) were examined with ECG-gated contrast-enhanced CT using a dual source scanner. The scan delay after the contrast media injection was 30 s for the non-ECG-gated CT and 100 s for the ECG-gated CT. Two radiologists blindly evaluated both the non-ECG-gated and ECG-gated CT images for motion artifacts and determined whether the tumors had invaded adjacent structures (mediastinal fat, superior vena cava, brachiocephalic veins, aorta, pulmonary artery, pericardium, or lungs) on each image. Motion artifacts were evaluated using a 3-grade scale. Surgical and pathological findings were used as a reference standard for tumor invasion. Motion artifacts were significantly reduced for all structures by ECG gating ( p =0.0089 for the lungs and p <0.0001 for the other structures). Non-ECG-gated CT and ECG-gated CT demonstrated 79% and 95% accuracy, respectively, during assessments of pericardial invasion ( p =0.03). ECG-gated CT reduced the severity of motion artifacts and might be useful for preoperative assessment whether thymic epithelial tumors have invaded adjacent structures.

Utility of Electrocardiography (ECG)-Gated Computed Tomography (CT) for Preoperative Evaluations of Thymic Epithelial Tumors

PubMed Central

Ozawa, Yoshiyuki; Hara, Masaki; Nakagawa, Motoo; Shibamoto, Yuta

2016-01-01

Summary Background Preoperative evaluation of invasion to the adjacent organs is important for the thymic epithelial tumors on CT. The purpose of our study was to evaluate the utility of electrocardiography (ECG)-gated CT for assessing thymic epithelial tumors with regard to the motion artifacts produced and the preoperative diagnostic accuracy of the technique. Material/Methods Forty thymic epithelial tumors (36 thymomas and 4 thymic carcinomas) were examined with ECG-gated contrast-enhanced CT using a dual source scanner. The scan delay after the contrast media injection was 30 s for the non-ECG-gated CT and 100 s for the ECG-gated CT. Two radiologists blindly evaluated both the non-ECG-gated and ECG-gated CT images for motion artifacts and determined whether the tumors had invaded adjacent structures (mediastinal fat, superior vena cava, brachiocephalic veins, aorta, pulmonary artery, pericardium, or lungs) on each image. Motion artifacts were evaluated using a 3-grade scale. Surgical and pathological findings were used as a reference standard for tumor invasion. Results Motion artifacts were significantly reduced for all structures by ECG gating (p=0.0089 for the lungs and p<0.0001 for the other structures). Non-ECG-gated CT and ECG-gated CT demonstrated 79% and 95% accuracy, respectively, during assessments of pericardial invasion (p=0.03). Conclusions ECG-gated CT reduced the severity of motion artifacts and might be useful for preoperative assessment whether thymic epithelial tumors have invaded adjacent structures. PMID:27920842

Correcting for motion artifact in handheld laser speckle images.

PubMed

Lertsakdadet, Ben; Yang, Bruce Y; Dunn, Cody E; Ponticorvo, Adrien; Crouzet, Christian; Bernal, Nicole; Durkin, Anthony J; Choi, Bernard

2018-03-01

Laser speckle imaging (LSI) is a wide-field optical technique that enables superficial blood flow quantification. LSI is normally performed in a mounted configuration to decrease the likelihood of motion artifact. However, mounted LSI systems are cumbersome and difficult to transport quickly in a clinical setting for which portability is essential in providing bedside patient care. To address this issue, we created a handheld LSI device using scientific grade components. To account for motion artifact of the LSI device used in a handheld setup, we incorporated a fiducial marker (FM) into our imaging protocol and determined the difference between highest and lowest speckle contrast values for the FM within each data set (Kbest and Kworst). The difference between Kbest and Kworst in mounted and handheld setups was 8% and 52%, respectively, thereby reinforcing the need for motion artifact quantification. When using a threshold FM speckle contrast value (KFM) to identify a subset of images with an acceptable level of motion artifact, mounted and handheld LSI measurements of speckle contrast of a flow region (KFLOW) in in vitro flow phantom experiments differed by 8%. Without the use of the FM, mounted and handheld KFLOW values differed by 20%. To further validate our handheld LSI device, we compared mounted and handheld data from an in vivo porcine burn model of superficial and full thickness burns. The speckle contrast within the burn region (KBURN) of the mounted and handheld LSI data differed by <4  %   when accounting for motion artifact using the FM, which is less than the speckle contrast difference between superficial and full thickness burns. Collectively, our results suggest the potential of handheld LSI with an FM as a suitable alternative to mounted LSI, especially in challenging clinical settings with space limitations such as the intensive care unit. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

iPhone 4s Photoplethysmography: Which Light Color Yields the Most Accurate Heart Rate and Normalized Pulse Volume Using the iPhysioMeter Application in the Presence of Motion Artifact?

PubMed Central

Matsumura, Kenta; Rolfe, Peter; Lee, Jihyoung; Yamakoshi, Takehiro

2014-01-01

Recent progress in information and communication technologies has made it possible to measure heart rate (HR) and normalized pulse volume (NPV), which are important physiological indices, using only a smartphone. This has been achieved with reflection mode photoplethysmography (PPG), by using a smartphone’s embedded flash as a light source and the camera as a light sensor. Despite its widespread use, the method of PPG is susceptible to motion artifacts as physical displacements influence photon propagation phenomena and, thereby, the effective optical path length. Further, it is known that the wavelength of light used for PPG influences the photon penetration depth and we therefore hypothesized that influences of motion artifact could be wavelength-dependant. To test this hypothesis, we made measurements in 12 healthy volunteers of HR and NPV derived from reflection mode plethysmograms recorded simultaneously at three different spectral regions (red, green and blue) at the same physical location with a smartphone. We then assessed the accuracy of the HR and NPV measurements under the influence of motion artifacts. The analyses revealed that the accuracy of HR was acceptably high with all three wavelengths (all rs > 0.996, fixed biases: −0.12 to 0.10 beats per minute, proportional biases: r = −0.29 to 0.03), but that of NPV was the best with green light (r = 0.791, fixed biases: −0.01 arbitrary units, proportional bias: r = 0.11). Moreover, the signal-to-noise ratio obtained with green and blue light PPG was higher than that of red light PPG. These findings suggest that green is the most suitable color for measuring HR and NPV from the reflection mode photoplethysmogram under motion artifact conditions. We conclude that the use of green light PPG could be of particular benefit in ambulatory monitoring where motion artifacts are a significant issue. PMID:24618594

Clustering-Constrained ICA for Ballistocardiogram Artifacts Removal in Simultaneous EEG-fMRI

PubMed Central

Wang, Kai; Li, Wenjie; Dong, Li; Zou, Ling; Wang, Changming

2018-01-01

Combination of electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) plays a potential role in neuroimaging due to its high spatial and temporal resolution. However, EEG is easily influenced by ballistocardiogram (BCG) artifacts and may cause false identification of the related EEG features, such as epileptic spikes. There are many related methods to remove them, however, they do not consider the time-varying features of BCG artifacts. In this paper, a novel method using clustering algorithm to catch the BCG artifacts' features and together with the constrained ICA (ccICA) is proposed to remove the BCG artifacts. We first applied this method to the simulated data, which was constructed by adding the BCG artifacts to the EEG signal obtained from the conventional environment. Then, our method was tested to demonstrate the effectiveness during EEG and fMRI experiments on 10 healthy subjects. In simulated data analysis, the value of error in signal amplitude (Er) computed by ccICA method was lower than those from other methods including AAS, OBS, and cICA (p < 0.005). In vivo data analysis, the Improvement of Normalized Power Spectrum (INPS) calculated by ccICA method in all electrodes was much higher than AAS, OBS, and cICA methods (p < 0.005). We also used other evaluation index (e.g., power analysis) to compare our method with other traditional methods. In conclusion, our novel method successfully and effectively removed BCG artifacts in both simulated and vivo EEG data tests, showing the potentials of removing artifacts in EEG-fMRI applications. PMID:29487499

Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging

PubMed Central

Vavadi, Hamed; Zhu, Quing

2016-01-01

Imaging-guided near infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response of breast cancers. However, diffused light measurements are sensitive to artifacts caused by outliers and errors in measurements due to probe-tissue coupling, patient and probe motions, and tissue heterogeneity. In general, pre-processing of the measurements is needed by experienced users to manually remove these outliers and therefore reduce imaging artifacts. An automated method of outlier removal, data selection, and filtering for diffuse optical tomography is introduced in this manuscript. This method consists of multiple steps to first combine several data sets collected from the same patient at contralateral normal breast and form a single robust reference data set using statistical tests and linear fitting of the measurements. The second step improves the perturbation measurements by filtering out outliers from the lesion site measurements using model based analysis. The results of 20 malignant and benign cases show similar performance between manual data processing and automated processing and improvement in tissue characterization of malignant to benign ratio by about 27%. PMID:27867711

Mathematical approach to recover EEG brain signals with artifacts by means of Gram-Schmidt transform

NASA Astrophysics Data System (ADS)

Runnova, A. E.; Zhuravlev, M. O.; Koronovskiy, A. A.; Hramov, A. E.

2017-04-01

A novel method for removing oculomotor artifacts on electroencephalographical signals is proposed and based on the orthogonal Gram-Schmidt transform using electrooculography data. The method has shown high efficiency removal of artifacts caused by spontaneous movements of the eyeballs (about 95-97% correct remote oculomotor artifacts). This method may be recommended for multi-channel electroencephalography data processing in an automatic on-line in a variety of psycho-physiological experiments.

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

PubMed

Feng, Li; Axel, Leon; Chandarana, Hersh; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo

2016-02-01

To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing. Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting undersampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients. XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts. XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value. © 2015 Wiley Periodicals, Inc.

XD-GRASP: Golden-Angle Radial MRI with Reconstruction of Extra Motion-State Dimensions Using Compressed Sensing

PubMed Central

Feng, Li; Axel, Leon; Chandarana, Hersh; Block, Kai Tobias; Sodickson, Daniel K.; Otazo, Ricardo

2015-01-01

Purpose To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing. Methods Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting under-sampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients. Results XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts. Conclusion XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value. PMID:25809847

TH-C-18A-11: Investigating the Minimum Scan Parameters Required to Generate Free-Breathing Fast-Helical CT Scans Without Motion-Artifacts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, D; Neylon, J; Dou, T

Purpose: A recently proposed 4D-CT protocol uses deformable registration of free-breathing fast-helical CT scans to generate a breathing motion model. In order to allow accurate registration, free-breathing images are required to be free of doubling-artifacts, which arise when tissue motion is greater than scan speed. This work identifies the minimum scanner parameters required to successfully generate free-breathing fast-helical scans without doubling-artifacts. Methods: 10 patients were imaged under free breathing conditions 25 times in alternating directions with a 64-slice CT scanner using a low dose fast helical protocol. A high temporal resolution (0.1s) 4D-CT was generated using a patient specific motionmore » model and patient breathing waveforms, and used as the input for a scanner simulation. Forward projections were calculated using helical cone-beam geometry (800 projections per rotation) and a GPU accelerated reconstruction algorithm was implemented. Various CT scanner detector widths and rotation times were simulated, and verified using a motion phantom. Doubling-artifacts were quantified in patient images using structural similarity maps to determine the similarity between axial slices. Results: Increasing amounts of doubling-artifacts were observed with increasing rotation times > 0.2s for 16×1mm slice scan geometry. No significant increase in doubling artifacts was observed for 64×1mm slice scan geometry up to 1.0s rotation time although blurring artifacts were observed >0.6s. Using a 16×1mm slice scan geometry, a rotation time of less than 0.3s (53mm/s scan speed) would be required to produce images of similar quality to a 64×1mm slice scan geometry. Conclusion: The current generation of 16 slice CT scanners, which are present in most Radiation Oncology departments, are not capable of generating free-breathing sorting-artifact-free images in the majority of patients. The next generation of CT scanners should be capable of at least 53mm/s scan speed in order to use a fast-helical 4D-CT protocol to generate a motion-artifact free 4D-CT. NIH R01CA096679.« less

New Imaging Strategies Using a Motion-Resistant Liver Sequence in Uncooperative Patients

PubMed Central

Kim, Bong Soo; Lee, Kyung Ryeol; Goh, Myeng Ju

2014-01-01

MR imaging has unique benefits for evaluating the liver because of its high-resolution capability and ability to permit detailed assessment of anatomic lesions. In uncooperative patients, motion artifacts can impair the image quality and lead to the loss of diagnostic information. In this setting, the recent advances in motion-resistant liver MR techniques, including faster imaging protocols (e.g., dual-echo magnetization-prepared rapid-acquisition gradient echo (MP-RAGE), view-sharing technique), the data under-sampling (e.g., gradient recalled echo (GRE) with controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA), single-shot echo-train spin-echo (SS-ETSE)), and motion-artifact minimization method (e.g., radial GRE with/without k-space-weighted image contrast (KWIC)), can provide consistent, artifact-free images with adequate image quality and can lead to promising diagnostic performance. Understanding of the different motion-resistant options allows radiologists to adopt the most appropriate technique for their clinical practice and thereby significantly improve patient care. PMID:25243115

Artifact removal from EEG data with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Efremova, Tatyana Yu.; Hramov, Alexander E.

2017-03-01

In the paper we propose the novel method for dealing with the physiological artifacts caused by intensive activity of facial and neck muscles and other movements in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We introduce the mathematical algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from movement artifacts and show high efficiency of the method.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers.

PubMed

Yücel, Meryem A; Selb, Juliette; Boas, David A; Cash, Sydney S; Cooper, Robert J

2014-01-15

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90% and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The SNR has also increased by 2 fold during rest conditions without motion with the new probe design because of better light coupling between the fiber and scalp. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case. Copyright © 2013 Elsevier Inc. All rights reserved.

Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics.

PubMed

Chen, Xun; Liu, Aiping; Chen, Qiang; Liu, Yu; Zou, Liang; McKeown, Martin J

2017-09-01

Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS & HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG. In reality, ocular and muscle artifacts do not completely follow the assumptions of strict temporal independence to the EEG nor completely unique autocorrelation characteristics, suggesting that exploiting HOS or SOS alone may be insufficient to remove these artifacts. Here we employ a novel BSS technique, independent vector analysis (IVA), to jointly employ HOS and SOS simultaneously to remove ocular and muscle artifacts. Numerical simulations and application to real EEG recordings were used to explore the utility of the IVA approach. IVA was superior in isolating both ocular and muscle artifacts, especially for raw EEG data with low signal-to-noise ratio, and also integrated usually separate SOS and HOS steps into a single unified step. Copyright © 2017 Elsevier Ltd. All rights reserved.

Landsat TM memory effect characterization and correction

USGS Publications Warehouse

Helder, D.; Boncyk, W.; Morfitt, R.

1997-01-01

Before radiometric calibration of Landsat Thematic Mapper (TM) data can be done accurately, it is necessary to minimize the effects of artifacts present in the data that originate in the instrument's signal processing path. These artifacts have been observed in downlinked image data since shortly after launch of Landsat 4 and 5. However, no comprehensive work has been done to characterize all the artifacts and develop methods for their correction. In this paper, the most problematic artifact is discussed: memory effect (ME). Characterization of this artifact is presented, including the parameters necessary for its correction. In addition, a correction algorithm is described that removes the artifact from TM imagery. It will be shown that this artifact causes significant radiometry errors, but the effect can be removed in a straightforward manner.

Efficiency test of filtering methods for the removal of transcranial magnetic stimulation artifacts on human electroencephalography with artificially transcranial magnetic stimulation-corrupted signals

NASA Astrophysics Data System (ADS)

Zilber, Nicolas A.; Katayama, Yoshinori; Iramina, Keiji; Erich, Wintermantel

2010-05-01

A new approach is proposed to test the efficiency of methods, such as the Kalman filter and the independent component analysis (ICA), when applied to remove the artifacts induced by transcranial magnetic stimulation (TMS) from electroencephalography (EEG). By using EEG recordings corrupted by TMS induction, the shape of the artifacts is approximately described with a model based on an equivalent circuit simulation. These modeled artifacts are subsequently added to other EEG signals—this time not influenced by TMS. The resulting signals prove of interest since we also know their form without the pseudo-TMS artifacts. Therefore, they enable us to use a fit test to compare the signals we obtain after removing the artifacts with the original signals. This efficiency test turned out very useful in comparing the methods between them, as well as in determining the parameters of the filtering that give satisfactory results with the automatic ICA.

Haptic fMRI: using classification to quantify task-correlated noise during goal-directed reaching motions.

PubMed

Menon, Samir; Quigley, Paul; Yu, Michelle; Khatib, Oussama

2014-01-01

Neuroimaging artifacts in haptic functional magnetic resonance imaging (Haptic fMRI) experiments have the potential to induce spurious fMRI activation where there is none, or to make neural activation measurements appear correlated across brain regions when they are actually not. Here, we demonstrate that performing three-dimensional goal-directed reaching motions while operating Haptic fMRI Interface (HFI) does not create confounding motion artifacts. To test for artifacts, we simultaneously scanned a subject's brain with a customized soft phantom placed a few centimeters away from the subject's left motor cortex. The phantom captured task-related motion and haptic noise, but did not contain associated neural activation measurements. We quantified the task-related information present in fMRI measurements taken from the brain and the phantom by using a linear max-margin classifier to predict whether raw time series data could differentiate between motion planning or reaching. fMRI measurements in the phantom were uninformative (2σ, 45-73%; chance=50%), while those in primary motor, visual, and somatosensory cortex accurately classified task-conditions (2σ, 90-96%). We also localized artifacts due to the haptic interface alone by scanning a stand-alone fBIRN phantom, while an operator performed haptic tasks outside the scanner's bore with the interface at the same location. The stand-alone phantom had lower temporal noise and had similar mean classification but a tighter distribution (bootstrap Gaussian fit) than the brain phantom. Our results suggest that any fMRI measurement artifacts for Haptic fMRI reaching experiments are dominated by actual neural responses.

Methods for artifact detection and removal from scalp EEG: A review.

PubMed

Islam, Md Kafiul; Rastegarnia, Amir; Yang, Zhi

2016-11-01

Electroencephalography (EEG) is the most popular brain activity recording technique used in wide range of applications. One of the commonly faced problems in EEG recordings is the presence of artifacts that come from sources other than brain and contaminate the acquired signals significantly. Therefore, much research over the past 15 years has focused on identifying ways for handling such artifacts in the preprocessing stage. However, this is still an active area of research as no single existing artifact detection/removal method is complete or universal. This article presents an extensive review of the existing state-of-the-art artifact detection and removal methods from scalp EEG for all potential EEG-based applications and analyses the pros and cons of each method. First, a general overview of the different artifact types that are found in scalp EEG and their effect on particular applications are presented. In addition, the methods are compared based on their ability to remove certain types of artifacts and their suitability in relevant applications (only functional comparison is provided not performance evaluation of methods). Finally, the future direction and expected challenges of current research is discussed. Therefore, this review is expected to be helpful for interested researchers who will develop and/or apply artifact handling algorithm/technique in future for their applications as well as for those willing to improve the existing algorithms or propose a new solution in this particular area of research. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

X-PROP: a fast and robust diffusion-weighted propeller technique.

PubMed

Li, Zhiqiang; Pipe, James G; Lee, Chu-Yu; Debbins, Josef P; Karis, John P; Huo, Donglai

2011-08-01

Diffusion-weighted imaging (DWI) has shown great benefits in clinical MR exams. However, current DWI techniques have shortcomings of sensitivity to distortion or long scan times or combinations of the two. Diffusion-weighted echo-planar imaging (EPI) is fast but suffers from severe geometric distortion. Periodically rotated overlapping parallel lines with enhanced reconstruction diffusion-weighted imaging (PROPELLER DWI) is free of geometric distortion, but the scan time is usually long and imposes high Specific Absorption Rate (SAR) especially at high fields. TurboPROP was proposed to accelerate the scan by combining signal from gradient echoes, but the off-resonance artifacts from gradient echoes can still degrade the image quality. In this study, a new method called X-PROP is presented. Similar to TurboPROP, it uses gradient echoes to reduce the scan time. By separating the gradient and spin echoes into individual blades and removing the off-resonance phase, the off-resonance artifacts in X-PROP are minimized. Special reconstruction processes are applied on these blades to correct for the motion artifacts. In vivo results show its advantages over EPI, PROPELLER DWI, and TurboPROP techniques. Copyright © 2011 Wiley-Liss, Inc.

A Novel Fast Helical 4D-CT Acquisition Technique to Generate Low-Noise Sorting Artifact–Free Images at User-Selected Breathing Phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, David, E-mail: dhthomas@mednet.ucla.edu; Lamb, James; White, Benjamin

2014-05-01

Purpose: To develop a novel 4-dimensional computed tomography (4D-CT) technique that exploits standard fast helical acquisition, a simultaneous breathing surrogate measurement, deformable image registration, and a breathing motion model to remove sorting artifacts. Methods and Materials: Ten patients were imaged under free-breathing conditions 25 successive times in alternating directions with a 64-slice CT scanner using a low-dose fast helical protocol. An abdominal bellows was used as a breathing surrogate. Deformable registration was used to register the first image (defined as the reference image) to the subsequent 24 segmented images. Voxel-specific motion model parameters were determined using a breathing motion model. Themore » tissue locations predicted by the motion model in the 25 images were compared against the deformably registered tissue locations, allowing a model prediction error to be evaluated. A low-noise image was created by averaging the 25 images deformed to the first image geometry, reducing statistical image noise by a factor of 5. The motion model was used to deform the low-noise reference image to any user-selected breathing phase. A voxel-specific correction was applied to correct the Hounsfield units for lung parenchyma density as a function of lung air filling. Results: Images produced using the model at user-selected breathing phases did not suffer from sorting artifacts common to conventional 4D-CT protocols. The mean prediction error across all patients between the breathing motion model predictions and the measured lung tissue positions was determined to be 1.19 ± 0.37 mm. Conclusions: The proposed technique can be used as a clinical 4D-CT technique. It is robust in the presence of irregular breathing and allows the entire imaging dose to contribute to the resulting image quality, providing sorting artifact–free images at a patient dose similar to or less than current 4D-CT techniques.« less

EEG Artifact Removal Using a Wavelet Neural Network

NASA Technical Reports Server (NTRS)

Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

!n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

Shoulder MR arthrography: intraarticular anesthetic reduces periprocedural pain and major motion artifacts but does not decrease imaging time.

PubMed

Fox, Michael G; Petrey, W Banks; Alford, Bennett; Huynh, Bang H; Patrie, James T; Anderson, Mark W

2012-02-01

To prospectively determine whether the addition of an intraarticular anesthetic to the magnetic resonance (MR) arthrography solution has an effect on periprocedural pain, motion artifacts, and imaging time. This study was approved by the institutional review board, and written informed consent was obtained from all patients. From September 2009 to March 2010, 127 patients, most imaged for shoulder pain, were randomized into two groups. The first group (group A, 63 patients) received intraarticular injection of gadopentetate dimeglumine, ropivacaine 0.5%, and normal saline in a ratio of 1:100:100. The second group (group B, 64 patients) received intraarticular injection of gadopentetate dimeglumine and normal saline in a ratio of 1:200. Pain was assessed before and after injection and immediately after 1.5-T MR imaging and rated on a scale of 0 to 10. Motion artifact was assessed by two musculoskeletal radiologists and two fellows by using a scale of 0 to 3 (0=no artifact, 1=artifact present but not affecting diagnostic image quality, 2=artifact present and diminishing diagnostic image quality, and 3=artifact present and rendering image nondiagnostic). MR imaging time and examinations with repeated sequences were recorded. Wilcoxon rank sum, analysis of covariance, and permutation data analyses were performed. The mean pain levels before injection, after injection, and after MR imaging were 3.5, 2.3, and 2.5, respectively, for group A and 3.6, 3.1, and 3.2 for group B. After adjusting for age, sex, and preinjection pain level, the mean differences in pre- and postinjection pain and preinjection pain and post-MR imaging pain between the two groups were -0.9 (P=.017) and -0.8 (P=.056), respectively. No significant difference in mean total MR imaging time or number of patients with repeat sequences was noted. Radiologists 1 and 2 recorded grade 2 or 3 motion in six and five patients, respectively, in group A and 15 and 14 patients, respectively, in group B (P=.047 and .048, respectively). Radiologists 3 and 4 recorded grade 2 or 3 motion in 13 and 23 patients, respectively, in group A and 23 and 33 patients, respectively, in group B (P=.093 and .110, respectively). The use of an intraarticular anesthetic significantly reduces periprocedural pain and major motion artifacts associated with MR shoulder arthrography; however, total MR imaging time is not reduced. © RSNA, 2011

Transient Severe Motion Artifact Related to Gadoxetate Disodium-Enhanced Liver MRI: Frequency and Risk Evaluation at a German Institution.

PubMed

Well, Lennart; Rausch, Vanessa Hanna; Adam, Gerhard; Henes, Frank Oliver; Bannas, Peter

2017-07-01

Purpose  Varying frequencies (5 - 18 %) of contrast-related transient severe motion (TSM) imaging artifacts during gadoxetate disodium-enhanced arterial phase liver MRI have been reported. Since previous reports originated from the United States and Japan, we aimed to determine the frequency of TSM at a German institution and to correlate it with potential risk factors and previously published results. Materials and Methods  Two age- and sex-matched groups were retrospectively selected (gadoxetate disodium n = 89; gadobenate dimeglumine n = 89) from dynamic contrast-enhanced MRI examinations in a single center. Respiratory motion-related artifacts in non-enhanced and dynamic phases were assessed independently by two readers blinded to contrast agents on a 4-point scale. Scores of ≥ 3 were considered as severe motion artifacts. Severe motion artifacts in arterial phases were considered as TSM if scores in all other phases were < 3. Potential risk factors for TSM were evaluated via logistic regression analysis. Results  For gadoxetate disodium, the mean score for respiratory motion artifacts was significantly higher in the arterial phase (2.2 ± 0.9) compared to all other phases (1.6 ± 0.7) (p < 0.05). The frequency of TSM was significantly higher with gadoxetate disodium (n = 19; 21.1 %) than with gadobenate dimeglumine (n = 1; 1.1 %) (p < 0.001). The frequency of TSM at our institution is similar to some, but not all previously published findings. Logistic regression analysis did not show any significant correlation between TSM and risk factors (all p > 0.05). Conclusion  We revealed a high frequency of TSM after injection of gadoxetate disodium at a German institution, substantiating the importance of a diagnosis-limiting phenomenon that so far has only been reported from the United States and Japan. In accordance with previous studies, we did not identify associated risk factors for TSM. Key Points:   · Gadoxetate disodium causes TSM in a relevant number of patients.. · The frequency of TSM is similar between the USA, Japan and Germany.. · To date, no validated risk factors for TSM could be identified.. Citation Format · Well L, Rausch VH, Adam G et al. Transient Severe Motion Artifact Related to Gadoxetate Disodium-Enhanced Liver MRI: Frequency and Risk Evaluation at a German Institution. Fortschr Röntgenstr 2017; 189: 651 - 660. © Georg Thieme Verlag KG Stuttgart · New York.

Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI.

PubMed

Johansson, Adam; Balter, James; Cao, Yue

2018-03-01

Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast-enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra-image motion blur remains after alignment and can alter the shape of contrast-agent uptake curves. We introduce a method to correct for inter- and intra-image motion during image reconstruction. Sixteen liver dynamic contrast-enhanced MRI examinations of nine subjects were performed using a golden-angle stack-of-stars sequence. For each examination, an image time series with high temporal resolution but severe streak artifacts was reconstructed. Images were aligned using region-limited rigid image registration within a region of interest covering the liver. The transformations resulting from alignment were used to correct raw data for motion by modulating and rotating acquired lines in k-space. The corrected data were then reconstructed using view sharing. Portal-venous input functions extracted from motion-corrected images had significantly greater peak signal enhancements (mean increase: 16%, t-test, P <  0.001) than those from images aligned using image registration after reconstruction. In addition, portal-venous perfusion maps estimated from motion-corrected images showed fewer artifacts close to the edge of the liver. Motion-corrected image reconstruction restores uptake curves distorted by motion. Motion correction also reduces motion artifacts in estimated perfusion parameter maps. Magn Reson Med 79:1345-1353, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Motion compensation for cone-beam CT using Fourier consistency conditions

NASA Astrophysics Data System (ADS)

Berger, M.; Xia, Y.; Aichinger, W.; Mentl, K.; Unberath, M.; Aichert, A.; Riess, C.; Hornegger, J.; Fahrig, R.; Maier, A.

2017-09-01

In cone-beam CT, involuntary patient motion and inaccurate or irreproducible scanner motion substantially degrades image quality. To avoid artifacts this motion needs to be estimated and compensated during image reconstruction. In previous work we showed that Fourier consistency conditions (FCC) can be used in fan-beam CT to estimate motion in the sinogram domain. This work extends the FCC to 3\\text{D} cone-beam CT. We derive an efficient cost function to compensate for 3\\text{D} motion using 2\\text{D} detector translations. The extended FCC method have been tested with five translational motion patterns, using a challenging numerical phantom. We evaluated the root-mean-square-error and the structural-similarity-index between motion corrected and motion-free reconstructions. Additionally, we computed the mean-absolute-difference (MAD) between the estimated and the ground-truth motion. The practical applicability of the method is demonstrated by application to respiratory motion estimation in rotational angiography, but also to motion correction for weight-bearing imaging of knees. Where the latter makes use of a specifically modified FCC version which is robust to axial truncation. The results show a great reduction of motion artifacts. Accurate estimation results were achieved with a maximum MAD value of 708 μm and 1184 μm for motion along the vertical and horizontal detector direction, respectively. The image quality of reconstructions obtained with the proposed method is close to that of motion corrected reconstructions based on the ground-truth motion. Simulations using noise-free and noisy data demonstrate that FCC are robust to noise. Even high-frequency motion was accurately estimated leading to a considerable reduction of streaking artifacts. The method is purely image-based and therefore independent of any auxiliary data.

Sensor fusion using a hybrid median filter for artifact removal in intraoperative heart rate monitoring.

PubMed

Yang, Ping; Dumont, Guy A; Ansermino, J Mark

2009-04-01

Intraoperative heart rate is routinely measured independently from the ECG monitor, pulse oximeter, and the invasive blood pressure monitor if available. The presence of artifacts, in one or more of theses signals, especially sustained artifacts, represents a critical challenge for physiological monitoring. When temporal filters are used to suppress sustained artifacts, unwanted delays or signal distortion are often introduced. The aim of this study was to remove artifacts and derive accurate estimates for the heart rate signal by using measurement redundancy. Heart rate measurements from multiple sensors and previous estimates that fall in a short moving window were treated as samples of the same heart rate. A hybrid median filter was used to align these samples into one ordinal series and to select the median as the fused estimate. This method can successfully remove artifacts that are sustained for shorter than half the length of the filter window, or artifacts that are sustained for a longer duration but presented in no more than half of the sensors. The method was tested on both simulated and clinical cases. The performance of the hybrid median filter in the simulated study was compared with that of a two-step estimation process, comprising a threshold-controlled artifact-removal module and a Kalman filter. The estimation accuracy of the hybrid median filter is better than that of the Kalman filter in the presence of artifacts. The hybrid median filter combines the structural and temporal information from two or more sensors and generates a robust estimate of heart rate without requiring strict assumptions about the signal's characteristics. This method is intuitive, computationally simple, and the performance can be easily adjusted. These considerable benefits make this method highly suitable for clinical use.

Diagnostic Performance of a Novel Coronary CT Angiography Algorithm: Prospective Multicenter Validation of an Intracycle CT Motion Correction Algorithm for Diagnostic Accuracy.

PubMed

Andreini, Daniele; Lin, Fay Y; Rizvi, Asim; Cho, Iksung; Heo, Ran; Pontone, Gianluca; Bartorelli, Antonio L; Mushtaq, Saima; Villines, Todd C; Carrascosa, Patricia; Choi, Byoung Wook; Bloom, Stephen; Wei, Han; Xing, Yan; Gebow, Dan; Gransar, Heidi; Chang, Hyuk-Jae; Leipsic, Jonathon; Min, James K

2018-06-01

Motion artifact can reduce the diagnostic accuracy of coronary CT angiography (CCTA) for coronary artery disease (CAD). The purpose of this study was to compare the diagnostic performance of an algorithm dedicated to correcting coronary motion artifact with the performance of standard reconstruction methods in a prospective international multicenter study. Patients referred for clinically indicated invasive coronary angiography (ICA) for suspected CAD prospectively underwent an investigational CCTA examination free from heart rate-lowering medications before they underwent ICA. Blinded core laboratory interpretations of motion-corrected and standard reconstructions for obstructive CAD (≥ 50% stenosis) were compared with ICA findings. Segments unevaluable owing to artifact were considered obstructive. The primary endpoint was per-subject diagnostic accuracy of the intracycle motion correction algorithm for obstructive CAD found at ICA. Among 230 patients who underwent CCTA with the motion correction algorithm and standard reconstruction, 92 (40.0%) had obstructive CAD on the basis of ICA findings. At a mean heart rate of 68.0 ± 11.7 beats/min, the motion correction algorithm reduced the number of nondiagnostic scans compared with standard reconstruction (20.4% vs 34.8%; p < 0.001). Diagnostic accuracy for obstructive CAD with the motion correction algorithm (62%; 95% CI, 56-68%) was not significantly different from that of standard reconstruction on a per-subject basis (59%; 95% CI, 53-66%; p = 0.28) but was superior on a per-vessel basis: 77% (95% CI, 74-80%) versus 72% (95% CI, 69-75%) (p = 0.02). The motion correction algorithm was superior in subgroups of patients with severely obstructive (≥ 70%) stenosis, heart rate ≥ 70 beats/min, and vessels in the atrioventricular groove. The motion correction algorithm studied reduces artifacts and improves diagnostic performance for obstructive CAD on a per-vessel basis and in selected subgroups on a per-subject basis.

SU-D-17A-07: Development and Evaluation of a Prototype Ultrasonography Respiratory Monitoring System for 4DCT Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, P; Cheng, S; Chao, C

Purpose: Respiratory motion artifacts are commonly seen in the abdominal and thoracic CT images. A Real-time Position Management (RPM) system is integrated with CT simulator using abdominal surface as a surrogate for tracking the patient respiratory motion. The respiratory-correlated four-dimensional computed tomography (4DCT) is then reconstructed by GE advantage software. However, there are still artifacts due to inaccurate respiratory motion detecting and sorting methods. We developed an Ultrasonography Respiration Monitoring (URM) system which can directly monitor diaphragm motion to detect respiratory cycles. We also developed a new 4DCT sorting and motion estimation method to reduce the respiratory motion artifacts. Themore » new 4DCT system was compared with RPM and the GE 4DCT system. Methods: Imaging from a GE CT scanner was simultaneously correlated with both the RPM and URM to detect respiratory motion. A radiation detector, Blackcat GM-10, recorded the X-ray on/off and synchronized with URM. The diaphragm images were acquired with Ultrasonix RP system. The respiratory wave was derived from diaphragm images and synchronized with CT scanner. A more precise peaks and valleys detection tool was developed and compared with RPM. The motion is estimated for the slices which are not in the predefined respiratory phases by using block matching and optical flow method. The CT slices were then sorted into different phases and reconstructed, compared with the images reconstructed from GE Advantage software using respiratory wave produced from RPM system. Results: The 4DCT images were reconstructed for eight patients. The discontinuity at the diaphragm level due to an inaccurate identification of phases by the RPM was significantly improved by URM system. Conclusion: Our URM 4DCT system was evaluated and compared with RPM and GE 4DCT system. The new system is user friendly and able to reduce motion artifacts. It also has the potential to monitor organ motion during therapy.« less

Free-breathing high-pitch 80kVp dual-source computed tomography of the pediatric chest: Image quality, presence of motion artifacts and radiation dose.

PubMed

Bodelle, Boris; Fischbach, Constanze; Booz, Christian; Yel, Ibrahim; Frellesen, Claudia; Beeres, Martin; Vogl, Thomas J; Scholtz, Jan-Erik

2017-04-01

To investigate image quality, presence of motion artifacts and effects on radiation dose of 80kVp high-pitch dual-source CT (DSCT) in combination with an advanced modeled iterative reconstruction algorithm (ADMIRE) of the pediatric chest compared to single-source CT (SSCT). The study was approved by the institutional review board. Eighty-seven consecutive pediatric patients (mean age 9.1±4.9years) received either free-breathing high-pitch (pitch 3.2) chest 192-slice DSCT (group 1, n=31) or standard-pitch (pitch 1.2) 128-slice SSCT (group 2, n=56) with breathing-instructions by random assignment. Tube settings were similar in both groups with 80 kVp and 74 ref. mAs. Images were reconstructed using FBP for both groups. Additionally, ADMIRE was used in group 1. Effective thorax diameter, image noise, and signal-to-noise ratio (SNR) of the pectoralis major muscle and the thoracic aorta were calculated. Motion artifacts were measured as doubling boarders of the diaphragm and the heart. Images were rated by two blinded readers for overall image quality and presence of motion artifacts on 5-point-scales. Size specific dose estimates (SSDE, mGy) and effective dose (ED, mSv) were calculated. Age and effective thorax diameter showed no statistically significant differences in both groups. Image noise and SNR were comparable (p>0.64) for SSCT and DSCT with ADMIRE, while DSCT with FBP showed inferior results (p<0.01). Motion artifacts were reduced significantly (p=0.001) with DSCT. DSCT with ADMIRE showed the highest overall IQ (p<0.0001). Radiation dose was lower for DSCT compared to SSCT (median SSDE: 0.82mGy vs. 0.92mGy, p<0.02; median ED: 0.4 mSv vs. 0.48mSv, p=0.02). High-pitch 80kVp chest DSCT in combination with ADMIRE reduces motion artifacts and increases image quality while lowering radiation exposure in free-breathing pediatric patients without sedation. Copyright © 2017 Elsevier B.V. All rights reserved.

Prospective motion correction of high-resolution magnetic resonance imaging data in children.

PubMed

Brown, Timothy T; Kuperman, Joshua M; Erhart, Matthew; White, Nathan S; Roddey, J Cooper; Shankaranarayanan, Ajit; Han, Eric T; Rettmann, Dan; Dale, Anders M

2010-10-15

Motion artifacts pose significant problems for the acquisition and analysis of high-resolution magnetic resonance imaging data. These artifacts can be particularly severe when studying pediatric populations, where greater patient movement reduces the ability to clearly view and reliably measure anatomy. In this study, we tested the effectiveness of a new prospective motion correction technique, called PROMO, as applied to making neuroanatomical measures in typically developing school-age children. This method attempts to address the problem of motion at its source by keeping the measurement coordinate system fixed with respect to the subject throughout image acquisition. The technique also performs automatic rescanning of images that were acquired during intervals of particularly severe motion. Unlike many previous techniques, this approach adjusts for both in-plane and through-plane movement, greatly reducing image artifacts without the need for additional equipment. Results show that the use of PROMO notably enhances subjective image quality, reduces errors in Freesurfer cortical surface reconstructions, and significantly improves the subcortical volumetric segmentation of brain structures. Further applications of PROMO for clinical and cognitive neuroscience are discussed. Copyright 2010 Elsevier Inc. All rights reserved.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Significant Artifact Reduction at 1.5T and 3T MRI by the Use of a Cochlear Implant with Removable Magnet: An Experimental Human Cadaver Study

PubMed Central

Wagner, Franca; Wimmer, Wilhelm; Leidolt, Lars; Vischer, Mattheus; Weder, Stefan; Wiest, Roland; Mantokoudis, Georgios; Caversaccio, Marco D.

2015-01-01

Objective Cochlear implants (CIs) are standard treatment for postlingually deafened individuals and prelingually deafened children. This human cadaver study evaluated diagnostic usefulness, image quality and artifacts in 1.5T and 3T magnetic resonance (MR) brain scans after CI with a removable magnet. Methods Three criteria (diagnostic usefulness, image quality, artifacts) were assessed at 1.5T and 3T in five cadaver heads with CI. The brain magnetic resonance scans were performed with and without the magnet in situ. The criteria were analyzed by two blinded neuroradiologists, with focus on image distortion and limitation of the diagnostic value of the acquired MR images. Results MR images with the magnet in situ were all compromised by artifacts caused by the CI. After removal of the magnet, MR scans showed an unequivocal artifact reduction with significant improvement of the image quality and diagnostic usefulness, both at 1.5T and 3T. Visibility of the brain stem, cerebellopontine angle, and parieto-occipital lobe ipsilateral to the CI increased significantly after magnet removal. Conclusions The results indicate the possible advantages for 1.5T and 3T MR scanning of the brain in CI carriers with removable magnets. Our findings support use of CIs with removable magnets, especially in patients with chronic intracranial pathologies. PMID:26200775

Significant Artifact Reduction at 1.5T and 3T MRI by the Use of a Cochlear Implant with Removable Magnet: An Experimental Human Cadaver Study.

PubMed

Wagner, Franca; Wimmer, Wilhelm; Leidolt, Lars; Vischer, Mattheus; Weder, Stefan; Wiest, Roland; Mantokoudis, Georgios; Caversaccio, Marco D

2015-01-01

Cochlear implants (CIs) are standard treatment for postlingually deafened individuals and prelingually deafened children. This human cadaver study evaluated diagnostic usefulness, image quality and artifacts in 1.5T and 3T magnetic resonance (MR) brain scans after CI with a removable magnet. Three criteria (diagnostic usefulness, image quality, artifacts) were assessed at 1.5T and 3T in five cadaver heads with CI. The brain magnetic resonance scans were performed with and without the magnet in situ. The criteria were analyzed by two blinded neuroradiologists, with focus on image distortion and limitation of the diagnostic value of the acquired MR images. MR images with the magnet in situ were all compromised by artifacts caused by the CI. After removal of the magnet, MR scans showed an unequivocal artifact reduction with significant improvement of the image quality and diagnostic usefulness, both at 1.5T and 3T. Visibility of the brain stem, cerebellopontine angle, and parieto-occipital lobe ipsilateral to the CI increased significantly after magnet removal. The results indicate the possible advantages for 1.5T and 3T MR scanning of the brain in CI carriers with removable magnets. Our findings support use of CIs with removable magnets, especially in patients with chronic intracranial pathologies.

Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

PubMed

Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

2017-12-25

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

NASA Astrophysics Data System (ADS)

Deprez, Hanne; Gransier, Robin; Hofmann, Michael; van Wieringen, Astrid; Wouters, Jan; Moonen, Marc

2018-02-01

Objective. Electrically evoked auditory steady-state responses (EASSRs) are potentially useful for objective cochlear implant (CI) fitting and follow-up of the auditory maturation in infants and children with a CI. EASSRs are recorded in the electro-encephalogram (EEG) in response to electrical stimulation with continuous pulse trains, and are distorted by significant CI artifacts related to this electrical stimulation. The aim of this study is to evaluate a CI artifacts attenuation method based on independent component analysis (ICA) for three EASSR datasets. Approach. ICA has often been used to remove CI artifacts from the EEG to record transient auditory responses, such as cortical evoked auditory potentials. Independent components (ICs) corresponding to CI artifacts are then often manually identified. In this study, an ICA based CI artifacts attenuation method was developed and evaluated for EASSR measurements with varying CI artifacts and EASSR characteristics. Artifactual ICs were automatically identified based on their spectrum. Main results. For 40 Hz amplitude modulation (AM) stimulation at comfort level, in high SNR recordings, ICA succeeded in removing CI artifacts from all recording channels, without distorting the EASSR. For lower SNR recordings, with 40 Hz AM stimulation at lower levels, or 90 Hz AM stimulation, ICA either distorted the EASSR or could not remove all CI artifacts in most subjects, except for two of the seven subjects tested with low level 40 Hz AM stimulation. Noise levels were reduced after ICA was applied, and up to 29 ICs were rejected, suggesting poor ICA separation quality. Significance. We hypothesize that ICA is capable of separating CI artifacts and EASSR in case the contralateral hemisphere is EASSR dominated. For small EASSRs or large CI artifact amplitudes, ICA separation quality is insufficient to ensure complete CI artifacts attenuation without EASSR distortion.

Effects of eye artifact removal methods on single trial P300 detection, a comparative study.

PubMed

Ghaderi, Foad; Kim, Su Kyoung; Kirchner, Elsa Andrea

2014-01-15

Electroencephalographic signals are commonly contaminated by eye artifacts, even if recorded under controlled conditions. The objective of this work was to quantitatively compare standard artifact removal methods (regression, filtered regression, Infomax, and second order blind identification (SOBI)) and two artifact identification approaches for independent component analysis (ICA) methods, i.e. ADJUST and correlation. To this end, eye artifacts were removed and the cleaned datasets were used for single trial classification of P300 (a type of event related potentials elicited using the oddball paradigm). Statistical analysis of the results confirms that the combination of Infomax and ADJUST provides a relatively better performance (0.6% improvement on average of all subject) while the combination of SOBI and correlation performs the worst. Low-pass filtering the data at lower cutoffs (here 4 Hz) can also improve the classification accuracy. Without requiring any artifact reference channel, the combination of Infomax and ADJUST improves the classification performance more than the other methods for both examined filtering cutoffs, i.e., 4 Hz and 25 Hz. Copyright © 2013 Elsevier B.V. All rights reserved.

Definition of Hydrologic Response Units in Depression Plagued Digital Elevation Models

NASA Astrophysics Data System (ADS)

Lindsay, J. B.; Creed, I. F.

2002-12-01

Definition of hydrologic response units using digital elevation models (DEMs) is sensitive to the occurrence of topographic depressions. Real depressions can be important to the hydrology and biogeochemistry a catchment, often coinciding with areas of surface saturation. Artifact depressions, in contrast, result in digital "black holes", artificially truncating the hydrologic flow lengths and altering hydrologic flow directions, parameters that are often used in defining hydrologic response units. Artifact depressions must be removed from DEMs prior to definition of hydrologic response units. Depression filling or depression trenching techniques can be used to remove these artifacts. Depression trenching methods are often considered more appropriate because they preserve the topographic variability within a depression thus avoiding the creation of spurious flat areas. Current trenching algorithms are relatively slow and unable to process very large or noisy DEMs. A new trenching algorithm that overcomes these limitations is described. The algorithm does not require finding depression catchments or outlets, nor does it need special handling for nested depressions. Therefore, artifacts can be removed from large or noisy DEMs efficiently, while minimizing the number of grid elevations requiring modification. The resulting trench is a monotonically descending path starting from the lowest point in a depression, passing through the depression's outlet, and ending at a point of lower elevation outside the depression. The importance of removing artifact depressions is demonstrated by showing hydrologic response units both before and after the removal of artifact depressions from the DEM.

15 CFR 922.166 - Permits other than for access to the Tortugas Ecological Reserve-application procedures and...

Code of Federal Regulations, 2014 CFR

2014-01-01

... activity will involve test excavations or removal of artifacts or materials for evaluative purposes, a... of the seabed and/or the removal of artifacts or other material necessary for evaluative purposes and...

15 CFR 922.166 - Permits other than for access to the Tortugas Ecological Reserve-application procedures and...

Code of Federal Regulations, 2011 CFR

2011-01-01

... activity will involve test excavations or removal of artifacts or materials for evaluative purposes, a... of the seabed and/or the removal of artifacts or other material necessary for evaluative purposes and...

15 CFR 922.166 - Permits other than for access to the Tortugas Ecological Reserve-application procedures and...

Code of Federal Regulations, 2013 CFR

2013-01-01

... activity will involve test excavations or removal of artifacts or materials for evaluative purposes, a... of the seabed and/or the removal of artifacts or other material necessary for evaluative purposes and...

15 CFR 922.166 - Permits other than for access to the Tortugas Ecological Reserve-application procedures and...

Code of Federal Regulations, 2012 CFR

2012-01-01

... activity will involve test excavations or removal of artifacts or materials for evaluative purposes, a... of the seabed and/or the removal of artifacts or other material necessary for evaluative purposes and...

15 CFR 922.166 - Permits other than for access to the Tortugas Ecological Reserve-application procedures and...

Code of Federal Regulations, 2010 CFR

2010-01-01

... activity will involve test excavations or removal of artifacts or materials for evaluative purposes, a... of the seabed and/or the removal of artifacts or other material necessary for evaluative purposes and...

EEG artifact removal-state-of-the-art and guidelines.

PubMed

Urigüen, Jose Antonio; Garcia-Zapirain, Begoña

2015-06-01

This paper presents an extensive review on the artifact removal algorithms used to remove the main sources of interference encountered in the electroencephalogram (EEG), specifically ocular, muscular and cardiac artifacts. We first introduce background knowledge on the characteristics of EEG activity, of the artifacts and of the EEG measurement model. Then, we present algorithms commonly employed in the literature and describe their key features. Lastly, principally on the basis of the results provided by various researchers, but also supported by our own experience, we compare the state-of-the-art methods in terms of reported performance, and provide guidelines on how to choose a suitable artifact removal algorithm for a given scenario. With this review we have concluded that, without prior knowledge of the recorded EEG signal or the contaminants, the safest approach is to correct the measured EEG using independent component analysis-to be precise, an algorithm based on second-order statistics such as second-order blind identification (SOBI). Other effective alternatives include extended information maximization (InfoMax) and an adaptive mixture of independent component analyzers (AMICA), based on higher order statistics. All of these algorithms have proved particularly effective with simulations and, more importantly, with data collected in controlled recording conditions. Moreover, whenever prior knowledge is available, then a constrained form of the chosen method should be used in order to incorporate such additional information. Finally, since which algorithm is the best performing is highly dependent on the type of the EEG signal, the artifacts and the signal to contaminant ratio, we believe that the optimal method for removing artifacts from the EEG consists in combining more than one algorithm to correct the signal using multiple processing stages, even though this is an option largely unexplored by researchers in the area.

An efficient multiple exposure image fusion in JPEG domain

NASA Astrophysics Data System (ADS)

Hebbalaguppe, Ramya; Kakarala, Ramakrishna

2012-01-01

In this paper, we describe a method to fuse multiple images taken with varying exposure times in the JPEG domain. The proposed algorithm finds its application in HDR image acquisition and image stabilization for hand-held devices like mobile phones, music players with cameras, digital cameras etc. Image acquisition at low light typically results in blurry and noisy images for hand-held camera's. Altering camera settings like ISO sensitivity, exposure times and aperture for low light image capture results in noise amplification, motion blur and reduction of depth-of-field respectively. The purpose of fusing multiple exposures is to combine the sharp details of the shorter exposure images with high signal-to-noise-ratio (SNR) of the longer exposure images. The algorithm requires only a single pass over all images, making it efficient. It comprises of - sigmoidal boosting of shorter exposed images, image fusion, artifact removal and saturation detection. Algorithm does not need more memory than a single JPEG macro block to be kept in memory making it feasible to be implemented as the part of a digital cameras hardware image processing engine. The Artifact removal step reuses the JPEGs built-in frequency analysis and hence benefits from the considerable optimization and design experience that is available for JPEG.

SU-E-J-38: Improved DRR Image Quality Using Polyetheretherketone (PEEK) Fiducial in Image Guided Radiotherapy (IGRT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, S; Jacob, R; Popple, R

Purpose Fiducial-based imaging is often used in IGRT. Traditional gold fiducial marker often has substantial reconstruction artifacts. These artifacts Result in poor image quality of DRR for online kV-to-DRR matching. This study evaluated the image quality of PEEK in DRR in static and moving phantom. Methods CT scan of the Gold and PEEK fiducial (both 1×3 mm) was acquired in a 22 cm cylindrical phantom filled with water. Image artifacts was evaluated with maximum CT value deviated from water due to artifacts; volume of artifacts in 10×10 cm in the center slice; maximum length of streak artifacts from the fiducial.more » DRR resolution were measured using FWHM and FWTM. 4DCT of PEEK fiducial was acquired with the phantom moving sinusoidally in superior-inferior direction. Motion artifacts were assessed for various 4D phase angles. Results The maximum CT value deviation was −174 for Gold and −24 for PEEK. The volume of artifacts in a 10x10 cm 3 mm slice was 0.369 for Gold and 0.074 cm3 for PEEK. The maximum length of streak artifact was 80mm for Gold and 7 mm for PEEK. PEEK in DRR, FWHM was close to actual (1.0 mm for Gold and 1.1 mm for PEEK). FWTM was 1.8 mm for Gold and 1.3 mm for PEEK in DRR. Barrel motion artifact of PEEK fiducial was noticeable for free-breathing scan. The apparent PEEK length due to residual motion was in close agreement with the calculated length (13 mm for 30–70 phase, 10 mm in 40–60 phase). Conclusion Streak artifacts on planning CT associated with use of gold fiducial can be significantly reduced by PEEK fiducial, while having adequate kV image contrast. DRR image resolution at FWTM was improved from 1.8 mm to 1.3 mm. Because of this improvement, we have been routinely use PEEK for liver IGRT.« less

Effect of respiratory gating on reducing lung motion artifacts in PET imaging of lung cancer.

PubMed

Nehmeh, S A; Erdi, Y E; Ling, C C; Rosenzweig, K E; Squire, O D; Braban, L E; Ford, E; Sidhu, K; Mageras, G S; Larson, S M; Humm, J L

2002-03-01

Positron emission tomography (PET) has shown an increase in both sensitivity and specificity over computed tomography (CT) in lung cancer. However, motion artifacts in the 18F fluorodioxydoglucose (FDG) PET images caused by respiration persists to be an important factor in degrading PET image quality and quantification. Motion artifacts lead to two major effects: First, it affects the accuracy of quantitation, producing a reduction of the measured standard uptake value (SUV). Second, the apparent lesion volume is overestimated. Both impact upon the usage of PET images for radiation treatment planning. The first affects the visibility, or contrast, of the lesion. The second results in an increase in the planning target volume, and consequently a greater radiation dose to the normal tissues. One way to compensate for this effect is by applying a multiple-frame capture technique. The PET data are then acquired in synchronization with the respiratory motion. Reduction in smearing due to gating was investigated in both phantoms and patient studies. Phantom studies showed a dependence of the reduction in smearing on the lesion size, the motion amplitude, and the number of bins used for data acquisition. These studies also showed an improvement in the target-to-background ratio, and a more accurate measurement of the SUV. When applied to one patient, respiratory gating showed a 28% reduction in the total lesion volume, and a 56.5% increase in the SUV. This study was conducted as a proof of principle that a gating technique can effectively reduce motion artifacts in PET image acquisition.

Physiological processes non-linearly affect electrophysiological recordings during transcranial electric stimulation.

PubMed

Noury, Nima; Hipp, Joerg F; Siegel, Markus

2016-10-15

Transcranial electric stimulation (tES) is a promising tool to non-invasively manipulate neuronal activity in the human brain. Several studies have shown behavioral effects of tES, but stimulation artifacts complicate the simultaneous investigation of neural activity with EEG or MEG. Here, we first show for EEG and MEG, that contrary to previous assumptions, artifacts do not simply reflect stimulation currents, but that heartbeat and respiration non-linearly modulate stimulation artifacts. These modulations occur irrespective of the stimulation frequency, i.e. during both transcranial alternating and direct current stimulations (tACS and tDCS). Second, we show that, although at first sight previously employed artifact rejection methods may seem to remove artifacts, data are still contaminated by non-linear stimulation artifacts. Because of their complex nature and dependence on the subjects' physiological state, these artifacts are prone to be mistaken as neural entrainment. In sum, our results uncover non-linear tES artifacts, show that current techniques fail to fully remove them, and pave the way for new artifact rejection methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data.

PubMed

Kim, Hyun-Chul; Yoo, Seung-Schik; Lee, Jong-Hwan

2015-01-01

Electroencephalography (EEG) data simultaneously acquired with functional magnetic resonance imaging (fMRI) data are preprocessed to remove gradient artifacts (GAs) and ballistocardiographic artifacts (BCAs). Nonetheless, these data, especially in the gamma frequency range, can be contaminated by residual artifacts produced by mechanical vibrations in the MRI system, in particular the cryogenic pump that compresses and transports the helium that chills the magnet (the helium-pump). However, few options are available for the removal of helium-pump artifacts. In this study, we propose a recursive approach of EEG-segment-based principal component analysis (rsPCA) that enables the removal of these helium-pump artifacts. Using the rsPCA method, feature vectors representing helium-pump artifacts were successfully extracted as eigenvectors, and the reconstructed signals of the feature vectors were subsequently removed. A test using simultaneous EEG-fMRI data acquired from left-hand (LH) and right-hand (RH) clenching tasks performed by volunteers found that the proposed rsPCA method substantially reduced helium-pump artifacts in the EEG data and significantly enhanced task-related gamma band activity levels (p=0.0038 and 0.0363 for LH and RH tasks, respectively) in EEG data that have had GAs and BCAs removed. The spatial patterns of the fMRI data were estimated using a hemodynamic response function (HRF) modeled from the estimated gamma band activity in a general linear model (GLM) framework. Active voxel clusters were identified in the post-/pre-central gyri of motor area, only from the rsPCA method (uncorrected p<0.001 for both LH/RH tasks). In addition, the superior temporal pole areas were consistently observed (uncorrected p<0.001 for the LH task and uncorrected p<0.05 for the RH task) in the spatial patterns of the HRF model for gamma band activity when the task paradigm and movement were also included in the GLM. Copyright © 2014 Elsevier Inc. All rights reserved.

Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

PubMed

Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

2013-09-13

Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram.

PubMed

Selvaraj, Nandakumar; Mendelson, Yitzhak; Shelley, Kirk H; Silverman, David G; Chon, Ki H

2011-01-01

Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings. The accuracy of the fusion of kurtosis and SE metrics for the artifact detection was 99.0%, 94.8% and 93.3% in simultaneously recorded ear, finger and forehead PPGs obtained in a clinical setting, respectively. For laboratory PPG data recorded from a finger with contrived artifacts, the accuracy was 88.8%. It was identified that the measurements from the forehead PPG sensor contained the most artifacts followed by finger and ear. The proposed MNA algorithm can be implemented in real-time as the computation time was 0.14 seconds using Matlab®.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

Optimization of Spiral-Based Pulse Sequences for First Pass Myocardial Perfusion Imaging

PubMed Central

Salerno, Michael; Sica, Christopher T.; Kramer, Christopher M.; Meyer, Craig H.

2010-01-01

While spiral trajectories have multiple attractive features such as their isotropic resolution, acquisition efficiency, and robustness to motion, there has been limited application of these techniques to first pass perfusion imaging because of potential off-resonance and inconsistent data artifacts. Spiral trajectories may also be less sensitive to dark-rim artifacts (DRA) that are caused, at least in part, by cardiac motion. By careful consideration of the spiral trajectory readout duration, flip angle strategy, and image reconstruction strategy, spiral artifacts can be abated to create high quality first pass myocardial perfusion images with high SNR. The goal of this paper was to design interleaved spiral pulse sequences for first-pass myocardial perfusion imaging, and to evaluate them clinically for image quality and the presence of dark-rim, blurring, and dropout artifacts. PMID:21590802

Muscle and eye movement artifact removal prior to EEG source localization.

PubMed

Hallez, Hans; Vergult, Anneleen; Phlypo, Ronald; Van Hese, Peter; De Clercq, Wim; D'Asseler, Yves; Van de Walle, Rik; Vanrumste, Bart; Van Paesschen, Wim; Van Huffel, Sabine; Lemahieu, Ignace

2006-01-01

Muscle and eye movement artifacts are very prominent in the ictal EEG of patients suffering from epilepsy, thus making the dipole localization of ictal activity very unreliable. Recently, two techniques (BSS-CCA and pSVD) were developed to remove those artifacts. The purpose of this study is to assess whether the removal of muscle and eye movement artifacts improves the EEG dipole source localization. We used a total of 8 EEG fragments, each from another patient, first unfiltered, then filtered by the BSS-CCA and pSVD. In both the filtered and unfiltered EEG fragments we estimated multiple dipoles using RAP-MUSIC. The resulting dipoles were subjected to a K-means clustering algorithm, to extract the most prominent cluster. We found that the removal of muscle and eye artifact results to tighter and more clear dipole clusters. Furthermore, we found that localization of the filtered EEG corresponded with the localization derived from the ictal SPECT in 7 of the 8 patients. Therefore, we can conclude that the BSS-CCA and pSVD improve localization of ictal activity, thus making the localization more reliable for the presurgical evaluation of the patient.

Motion-compensated detection of heart rate based on the time registration adaptive filter

NASA Astrophysics Data System (ADS)

Yang, Lei; Zhou, Jinsong; Jing, Juanjuan; Li, Yacan; Wei, Lidong; Feng, Lei; He, Xiaoying; Bu, Meixia; Fu, Xilu

2018-01-01

A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

PubMed Central

Adib, Mani; Cretu, Edmond

2013-01-01

We present a new method for removing artifacts in electroencephalography (EEG) records during Galvanic Vestibular Stimulation (GVS). The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters. PMID:23956786

Effect of high-pitch dual-source CT to compensate motion artifacts: a phantom study.

PubMed

Farshad-Amacker, Nadja A; Alkadhi, Hatem; Leschka, Sebastian; Frauenfelder, Thomas

2013-10-01

To evaluate the potential of high-pitch, dual-source computed tomography (DSCT) for compensation of motion artifacts. Motion artifacts were created using a moving chest/cardiac phantom with integrated stents at different velocities (from 0 to 4-6 cm/s) parallel (z direction), transverse (x direction), and diagonal (x and z direction combined) to the scanning direction using standard-pitch (SP) (pitch = 1) and high-pitch (HP) (pitch = 3.2) 128-detector DSCT (Siemens, Healthcare, Forchheim, Germany). The scanning parameters were (SP/HP): tube voltage, 120 kV/120 kV; effective tube current time product, 300 mAs/500 mAs; and a pitch of 1/3.2. Motion artifacts were analyzed in terms of subjective image quality and object distortion. Image quality was rated by two blinded, independent observers using a 4-point scoring system (1, excellent; 2, good with minor object distortion or blurring; 3, diagnostically partially not acceptable; and 4, diagnostically not acceptable image quality). Object distortion was assessed by the measured changes of the object's outer diameter (x) and length (z) and a corresponding calculated distortion vector (d) (d = √(x(2) + z(2))). The interobserver agreement was excellent (k = 0.91). Image quality using SP was diagnostically not acceptable with any motion in x direction (scores 3 and 4), in contrast to HP DSCT where it remained diagnostic up to 2 cm/s (scores 1 and 2). For motion in the z direction only, image quality remained diagnostic for SP and HP DSCT (scores 1 and 2). Changes of the object's diameter (x), length (z), and distortion vectors (d) were significantly greater with SP (overall: x = 1.9 cm ± 1.7 cm, z = 0.6 cm ± 0.8 cm, and d = 1.4 cm ± 1.5 cm) compared to HP DSCT (overall: x = 0.1 cm ± 0.1 cm, z = 0.0 cm ± 0.1 cm, and d = 0.1 cm ± 0.1 cm; each P < .05). High-pitch DSCT significantly decreases motion artifacts in various directions and improves image quality. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification.

PubMed

LeVan, P; Urrestarazu, E; Gotman, J

2006-04-01

To devise an automated system to remove artifacts from ictal scalp EEG, using independent component analysis (ICA). A Bayesian classifier was used to determine the probability that 2s epochs of seizure segments decomposed by ICA represented EEG activity, as opposed to artifact. The classifier was trained using numerous statistical, spectral, and spatial features. The system's performance was then assessed using separate validation data. The classifier identified epochs representing EEG activity in the validation dataset with a sensitivity of 82.4% and a specificity of 83.3%. An ICA component was considered to represent EEG activity if the sum of the probabilities that its epochs represented EEG exceeded a threshold predetermined using the training data. Otherwise, the component represented artifact. Using this threshold on the validation set, the identification of EEG components was performed with a sensitivity of 87.6% and a specificity of 70.2%. Most misclassified components were a mixture of EEG and artifactual activity. The automated system successfully rejected a good proportion of artifactual components extracted by ICA, while preserving almost all EEG components. The misclassification rate was comparable to the variability observed in human classification. Current ICA methods of artifact removal require a tedious visual classification of the components. The proposed system automates this process and removes simultaneously multiple types of artifacts.

Comparison of air-charged and water-filled urodynamic pressure measurement catheters.

PubMed

Cooper, M A; Fletter, P C; Zaszczurynski, P J; Damaser, M S

2011-03-01

Catheter systems are utilized to measure pressure for diagnosis of voiding dysfunction. In a clinical setting, patient movement and urodynamic pumps introduce hydrostatic and motion artifacts into measurements. Therefore, complete characterization of a catheter system includes its response to artifacts as well its frequency response. The objective of this study was to compare the response of two disposable clinical catheter systems: water-filled and air-charged, to controlled pressure signals to assess their similarities and differences in pressure transduction. We characterized frequency response using a transient step test, which exposed the catheters to a sudden change in pressure; and a sinusoidal frequency sweep test, which exposed the catheters to a sinusoidal pressure wave from 1 to 30 Hz. The response of the catheters to motion artifacts was tested using a vortex and the response to hydrostatic pressure changes was tested by moving the catheter tips to calibrated heights. Water-filled catheters acted as an underdamped system, resonating at 10.13 ± 1.03 Hz and attenuating signals at frequencies higher than 19 Hz. They demonstrated significant motion and hydrostatic artifacts. Air-charged catheters acted as an overdamped system and attenuated signals at frequencies higher than 3.02 ± 0.13 Hz. They demonstrated significantly less motion and hydrostatic artifacts than water-filled catheters. The transient step and frequency sweep tests gave comparable results. Air-charged and water-filled catheters respond to pressure changes in dramatically different ways. Knowledge of the characteristics of the pressure-measuring system is essential to finding the best match for a specific application. Copyright © 2011 Wiley-Liss, Inc.

Fourier removal of stripe artifacts in IRAS images

NASA Technical Reports Server (NTRS)

Van Buren, Dave

1987-01-01

By working in the Fourier plane, approximate removal of stripe artifacts in IRAS images can be effected. The image of interest is smoothed and subtracted from the original, giving the high-spatial-frequency part. This 'filtered' image is then clipped to remove point sources and then Fourier transformed. Subtracting the Fourier components contributing to the stripes in this image from the Fourier transform of the original and transforming back to the image plane yields substantial removal of the stripes.

Temporal presentation protocols in stereoscopic displays: Flicker visibility, perceived motion, and perceived depth

PubMed Central

Hoffman, David M.; Karasev, Vasiliy I.; Banks, Martin S.

2011-01-01

Most stereoscopic displays rely on field-sequential presentation to present different images to the left and right eyes. With sequential presentation, images are delivered to each eye in alternation with dark intervals, and each eye receives its images in counter phase with the other eye. This type of presentation can exacerbate image artifacts including flicker, and the appearance of unsmooth motion. To address the flicker problem, some methods repeat images multiple times before updating to new ones. This greatly reduces flicker visibility, but makes motion appear less smooth. This paper describes an investigation of how different presentation methods affect the visibility of flicker, motion artifacts, and distortions in perceived depth. It begins with an examination of these methods in the spatio-temporal frequency domain. From this examination, it describes a series of predictions for how presentation rate, object speed, simultaneity of image delivery to the two eyes, and other properties ought to affect flicker, motion artifacts, and depth distortions, and reports a series of experiments that tested these predictions. The results confirmed essentially all of the predictions. The paper concludes with a summary and series of recommendations for the best approach to minimize these undesirable effects. PMID:21572544

Motion compensation in digital subtraction angiography using graphics hardware.

PubMed

Deuerling-Zheng, Yu; Lell, Michael; Galant, Adam; Hornegger, Joachim

2006-07-01

An inherent disadvantage of digital subtraction angiography (DSA) is its sensitivity to patient motion which causes artifacts in the subtraction images. These artifacts could often reduce the diagnostic value of this technique. Automated, fast and accurate motion compensation is therefore required. To cope with this requirement, we first examine a method explicitly designed to detect local motions in DSA. Then, we implement a motion compensation algorithm by means of block matching on modern graphics hardware. Both methods search for maximal local similarity by evaluating a histogram-based measure. In this context, we are the first who have mapped an optimizing search strategy on graphics hardware while paralleling block matching. Moreover, we provide an innovative method for creating histograms on graphics hardware with vertex texturing and frame buffer blending. It turns out that both methods can effectively correct the artifacts in most case, as the hardware implementation of block matching performs much faster: the displacements of two 1024 x 1024 images can be calculated at 3 frames/s with integer precision or 2 frames/s with sub-pixel precision. Preliminary clinical evaluation indicates that the computation with integer precision could already be sufficient.

PROPELLER technique to improve image quality of MRI of the shoulder.

PubMed

Dietrich, Tobias J; Ulbrich, Erika J; Zanetti, Marco; Fucentese, Sandro F; Pfirrmann, Christian W A

2011-12-01

The purpose of this article is to evaluate the use of the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) technique for artifact reduction and overall image quality improvement for intermediate-weighted and T2-weighted MRI of the shoulder. One hundred eleven patients undergoing MR arthrography of the shoulder were included. A coronal oblique intermediate-weighted turbo spin-echo (TSE) sequence with fat suppression and a sagittal oblique T2-weighted TSE sequence with fat suppression were obtained without (standard) and with the PROPELLER technique. Scanning time increased from 3 minutes 17 seconds to 4 minutes 17 seconds (coronal oblique plane) and from 2 minutes 52 seconds to 4 minutes 10 seconds (sagittal oblique) using PROPELLER. Two radiologists graded image artifacts, overall image quality, and delineation of several anatomic structures on a 5-point scale (5, no artifact, optimal diagnostic quality; and 1, severe artifacts, diagnostically not usable). The Wilcoxon signed rank test was used to compare the data of the standard and PROPELLER images. Motion artifacts were significantly reduced in PROPELLER images (p < 0.001). Observer 1 rated motion artifacts with diagnostic impairment in one patient on coronal oblique PROPELLER images compared with 33 patients on standard images. Ratings for the sequences with PROPELLER were significantly better for overall image quality (p < 0.001). Observer 1 noted an overall image quality with diagnostic impairment in nine patients on sagittal oblique PROPELLER images compared with 23 patients on standard MRI. The PROPELLER technique for MRI of the shoulder reduces the number of sequences with diagnostic impairment as a result of motion artifacts and increases image quality compared with standard TSE sequences. PROPELLER sequences increase the acquisition time.

Artifact Removal from Biosignal using Fixed Point ICA Algorithm for Pre-processing in Biometric Recognition

NASA Astrophysics Data System (ADS)

Mishra, Puneet; Singla, Sunil Kumar

2013-01-01

In the modern world of automation, biological signals, especially Electroencephalogram (EEG) and Electrocardiogram (ECG), are gaining wide attention as a source of biometric information. Earlier studies have shown that EEG and ECG show versatility with individuals and every individual has distinct EEG and ECG spectrum. EEG (which can be recorded from the scalp due to the effect of millions of neurons) may contain noise signals such as eye blink, eye movement, muscular movement, line noise, etc. Similarly, ECG may contain artifact like line noise, tremor artifacts, baseline wandering, etc. These noise signals are required to be separated from the EEG and ECG signals to obtain the accurate results. This paper proposes a technique for the removal of eye blink artifact from EEG and ECG signal using fixed point or FastICA algorithm of Independent Component Analysis (ICA). For validation, FastICA algorithm has been applied to synthetic signal prepared by adding random noise to the Electrocardiogram (ECG) signal. FastICA algorithm separates the signal into two independent components, i.e. ECG pure and artifact signal. Similarly, the same algorithm has been applied to remove the artifacts (Electrooculogram or eye blink) from the EEG signal.

Blind retrospective motion correction of MR images.

PubMed

Loktyushin, Alexander; Nickisch, Hannes; Pohmann, Rolf; Schölkopf, Bernhard

2013-12-01

Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee. The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume. The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data. Copyright © 2013 Wiley Periodicals, Inc., a Wiley company.

Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution

PubMed Central

Yan, Yong-sheng; Poon, Carmen CY; Zhang, Yuan-ting

2005-01-01

Background The pulse oximeter, a medical device capable of measuring blood oxygen saturation (SpO2), has been shown to be a valuable device for monitoring patients in critical conditions. In order to incorporate the technique into a wearable device which can be used in ambulatory settings, the influence of motion artifacts on the estimated SpO2 must be reduced. This study investigates the use of the smoothed psuedo Wigner-Ville distribution (SPWVD) for the reduction of motion artifacts affecting pulse oximetry. Methods The SPWVD approach is compared with two techniques currently used in this field, i.e. the weighted moving average (WMA) and the fast Fourier transform (FFT) approaches. SpO2 and pulse rate were estimated from a photoplethysmographic (PPG) signal recorded when subject is in a resting position as well as in the act of performing four types of motions: horizontal and vertical movements of the hand, and bending and pressing motions of the finger. For each condition, 24 sets of PPG signals collected from 6 subjects, each of 30 seconds, were studied with reference to the PPG signal recorded simultaneously from the subject's other hand, which was stationary at all times. Results and Discussion The SPWVD approach shows significant improvement (p < 0.05), as compared to traditional approaches, when subjects bend their finger or press their finger against the sensor. In addition, the SPWVD approach also reduces the mean absolute pulse rate error significantly (p < 0.05) from 16.4 bpm and 11.2 bpm for the WMA and FFT approaches, respectively, to 5.62 bpm. Conclusion The results suggested that the SPWVD approach could potentially be used to reduce motion artifact on wearable pulse oximeters. PMID:15737241

Intelligent artifact classification for ambulatory physiological signals.

PubMed

Sweeney, Kevin T; Leamy, Darren J; Ward, Tomas E; McLoone, Sean

2010-01-01

Connected health represents an increasingly important model for health-care delivery. The concept is heavily reliant on technology and in particular remote physiological monitoring. One of the principal challenges is the maintenance of high quality data streams which must be collected with minimally intrusive, inexpensive sensor systems operating in difficult conditions. Ambulatory monitoring represents one of the most challenging signal acquisition challenges of all in that data is collected as the patient engages in normal activities of everyday living. Data thus collected suffers from considerable corruption as a result of artifact, much of it induced by motion and this has a bearing on its utility for diagnostic purposes. We propose a model for ambulatory signal recording in which the data collected is accompanied by labeling indicating the quality of the collected signal. As motion is such an important source of artifact we demonstrate the concept in this case with a quality of signal measure derived from motion sensing technology viz. accelerometers. We further demonstrate how different types of artifact might be tagged to inform artifact reduction signal processing elements during subsequent signal analysis. This is demonstrated through the use of multiple accelerometers which allow the algorithm to distinguish between disturbance of the sensor relative to the underlying tissue and movement of this tissue. A brain monitoring experiment utilizing EEG and fNIRS is used to illustrate the concept.

SU-E-I-67: Arachnoid Cysts: The Role of the BLADE Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavroidis, P; Vlachopoulou, A; Kostopoulos, S

2015-06-15

Purpose: The purpose of this study is first to show the extent by which BLADE sequences can reduce all the image artifacts and second to verify that the usefulness of this technique in certain pathological conditions is significant. Methods: In this study, fourteen consecutive patients (5 females, 9 males), who routinely underwent MRI brain examination, between 2010–2014, were selected. The applied routine protocols for brain MR examination included the following sequences: 1) T2-W FLAIR axial; 2) T2-W TSE axial; 3) T2*-W axial, 4) T1-W TSE sagittal; 5) DWI-W axial; 6) T1-W TSE axial; 7) T1-W TSE axial+contrast. In cases ofmore » cystic tumors, the T2-W FLAIR BLADE sequence was added to the protocol. All the images were evaluated independently at two separate settings with 3 weeks interval by two radiologists. The radiologists also evaluated the presence of image artifacts (motion, flow, chemical shift, Gibbs ringing). To evaluate the size of the cyst, the two radiologists compared the two techniques (conventional and BLADE) by assessing the extent of the divergence in the measurements of the cysts. Results: Regarding the extent of the cyst size, BLADE measurements were found to be more reliable than the conventional ones with the differences being statistically significant (p<0.01). The qualitative measurements indicated that the T2 FLAIR BLADE sequences were superior to the conventional T2 FLAIR with statistically significant differences (p<0.001) in the following characteristics: 1) overall image quality, 2) CSF nulling; 3) contrast at the pathology and its surrounding; 4) limits of the pathology; 5) motion artifacts; 6) flow artifacts; 7) chemical shift artifacts and 8) Gibbs ringing artifacts. Conclusion: BLADE sequence was found to decrease both flow artifacts in the temporal lobes and motion artifacts from the orbits and it is proposed for clinical use.« less

An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography

PubMed Central

Hu, Hai; Guo, Shengxin; Liu, Ran

2017-01-01

Artifacts removal and rhythms extraction from electroencephalography (EEG) signals are important for portable and wearable EEG recording devices. Incorporating a novel grouping rule, we proposed an adaptive singular spectrum analysis (SSA) method for artifacts removal and rhythms extraction. Based on the EEG signal amplitude, the grouping rule determines adaptively the first one or two SSA reconstructed components as artifacts and removes them. The remaining reconstructed components are then grouped based on their peak frequencies in the Fourier transform to extract the desired rhythms. The grouping rule thus enables SSA to be adaptive to EEG signals containing different levels of artifacts and rhythms. The simulated EEG data based on the Markov Process Amplitude (MPA) EEG model and the experimental EEG data in the eyes-open and eyes-closed states were used to verify the adaptive SSA method. Results showed a better performance in artifacts removal and rhythms extraction, compared with the wavelet decomposition (WDec) and another two recently reported SSA methods. Features of the extracted alpha rhythms using adaptive SSA were calculated to distinguish between the eyes-open and eyes-closed states. Results showed a higher accuracy (95.8%) than those of the WDec method (79.2%) and the infinite impulse response (IIR) filtering method (83.3%). PMID:28674650

Analysing concurrent transcranial magnetic stimulation and electroencephalographic data: A review and introduction to the open-source TESA software.

PubMed

Rogasch, Nigel C; Sullivan, Caley; Thomson, Richard H; Rose, Nathan S; Bailey, Neil W; Fitzgerald, Paul B; Farzan, Faranak; Hernandez-Pavon, Julio C

2017-02-15

The concurrent use of transcranial magnetic stimulation with electroencephalography (TMS-EEG) is growing in popularity as a method for assessing various cortical properties such as excitability, oscillations and connectivity. However, this combination of methods is technically challenging, resulting in artifacts both during recording and following typical EEG analysis methods, which can distort the underlying neural signal. In this article, we review the causes of artifacts in EEG recordings resulting from TMS, as well as artifacts introduced during analysis (e.g. as the result of filtering over high-frequency, large amplitude artifacts). We then discuss methods for removing artifacts, and ways of designing pipelines to minimise analysis-related artifacts. Finally, we introduce the TMS-EEG signal analyser (TESA), an open-source extension for EEGLAB, which includes functions that are specific for TMS-EEG analysis, such as removing and interpolating the TMS pulse artifact, removing and minimising TMS-evoked muscle activity, and analysing TMS-evoked potentials. The aims of TESA are to provide users with easy access to current TMS-EEG analysis methods and to encourage direct comparisons of these methods and pipelines. It is hoped that providing open-source functions will aid in both improving and standardising analysis across the field of TMS-EEG research. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Online EEG artifact removal for BCI applications by adaptive spatial filtering.

PubMed

Guarnieri, Roberto; Marino, Marco; Barban, Federico; Ganzetti, Marco; Mantini, Dante

2018-06-28

The performance of brain computer interfaces (BCIs) based on electroencephalography (EEG) data strongly depends on the effective attenuation of artifacts that are mixed in the recordings. To address this problem, we have developed a novel online EEG artifact removal method for BCI applications, which combines blind source separation (BSS) and regression (REG) analysis. The BSS-REG method relies on the availability of a calibration dataset of limited duration for the initialization of a spatial filter using BSS. Online artifact removal is implemented by dynamically adjusting the spatial filter in the actual experiment, based on a linear regression technique. Our results showed that the BSS-REG method is capable of attenuating different kinds of artifacts, including ocular and muscular, while preserving true neural activity. Thanks to its low computational requirements, BSS-REG can be applied to low-density as well as high-density EEG data. We argue that BSS-REG may enable the development of novel BCI applications requiring high-density recordings, such as source-based neurofeedback and closed-loop neuromodulation. © 2018 IOP Publishing Ltd.

SU-F-J-76: Evaluation of the Performance of Different Deformable Image Registration Algorithms in Helical, Axial and Cone-Beam CT Images of a Mobile Phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate quantitatively the performance of different deformable-image-registration algorithms (DIR) with helical (HCT), axial (ACT) and cone-beam CT (CBCT) by evaluating the variations in the CT-numbers and lengths of targets moving with controlled motion-patterns. Methods: Four DIR-algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from the DIRART-software are used to register CT-images of a mobile-phantom. A mobile-phantom is scanned with different imaging techniques that include helical, axial and cone-beam CT. The phantom includes three targets with different lengths that are made from water-equivalent material and inserted in low-density-foam which is moved with adjustable motion-amplitudes and frequencies. Results: Most of themore » DIR-algorithms are able to produce the lengths of the stationary-targets, however, they do not produce the CT-number values in CBCT. The image-artifacts induced by motion are more regular in CBCT imaging where the mobile-target elongation increases linearly with motion-amplitude. In ACT and HCT, the motion-artifacts are irregular where some mobile -targets are elongated or shrunk depending on the motion-phase during imaging. The DIR-algorithms are successful in deforming the images of the mobile-targets to the images of the stationary-targets producing the CT-number values and length of the target for motion-amplitudes < 20 mm. Similarly in ACT, all DIR-algorithms produced the actual CT-number and length of the stationary-targets for motion-amplitudes < 15 mm. As stronger motion-artifacts are induced in HCT and ACT, DIR-algorithms fail to produce CT-values and shape of the stationary-targets and fast-demons-algorithm has worst performance. Conclusion: Most of DIR-algorithms produce the CT-number values and lengths of the stationary-targets in HCT and ACT images that has motion-artifacts induced by small motion-amplitudes. As motion-amplitudes increase, the DIR-algorithms fail to deform mobile-target images to the stationary-images in HCT and ACT. In CBCT, DIR-algorithms are successful in producing length and shape of the stationary-targets, however, they fail to produce the accurate CT-number level.« less

Removal of BCG artifacts using a non-Kirchhoffian overcomplete representation.

PubMed

Dyrholm, Mads; Goldman, Robin; Sajda, Paul; Brown, Truman R

2009-02-01

We present a nonlinear unmixing approach for extracting the ballistocardiogram (BCG) from EEG recorded in an MR scanner during simultaneous acquisition of functional MRI (fMRI). First, an overcomplete basis is identified in the EEG based on a custom multipath EEG electrode cap. Next, the overcomplete basis is used to infer non-Kirchhoffian latent variables that are not consistent with a conservative electric field. Neural activity is strictly Kirchhoffian while the BCG artifact is not, and the representation can hence be used to remove the artifacts from the data in a way that does not attenuate the neural signals needed for optimal single-trial classification performance. We compare our method to more standard methods for BCG removal, namely independent component analysis and optimal basis sets, by looking at single-trial classification performance for an auditory oddball experiment. We show that our overcomplete representation method for removing BCG artifacts results in better single-trial classification performance compared to the conventional approaches, indicating that the derived neural activity in this representation retains the complex information in the trial-to-trial variability.

Stripe artifact elimination based on nonsubsampled contourlet transform for light sheet fluorescence microscopy

NASA Astrophysics Data System (ADS)

Liang, Xiao; Zang, Yali; Dong, Di; Zhang, Liwen; Fang, Mengjie; Yang, Xin; Arranz, Alicia; Ripoll, Jorge; Hui, Hui; Tian, Jie

2016-10-01

Stripe artifacts, caused by high-absorption or high-scattering structures in the illumination light path, are a common drawback in both unidirectional and multidirectional light sheet fluorescence microscopy (LSFM), significantly deteriorating image quality. To circumvent this problem, we present an effective multidirectional stripe remover (MDSR) method based on nonsubsampled contourlet transform (NSCT), which can be used for both unidirectional and multidirectional LSFM. In MDSR, a fast Fourier transform (FFT) filter is designed in the NSCT domain to shrink the stripe components and eliminate the noise. Benefiting from the properties of being multiscale and multidirectional, MDSR succeeds in eliminating stripe artifacts in both unidirectional and multidirectional LSFM. To validate the method, MDSR has been tested on images from a custom-made unidirectional LSFM system and a commercial multidirectional LSFM system, clearly demonstrating that MDSR effectively removes most of the stripe artifacts. Moreover, we performed a comparative experiment with the variational stationary noise remover and the wavelet-FFT methods and quantitatively analyzed the results with a peak signal-to-noise ratio, showing an improved noise removal when using the MDSR method.

Robust detrending, rereferencing, outlier detection, and inpainting for multichannel data.

PubMed

de Cheveigné, Alain; Arzounian, Dorothée

2018-05-15

Electroencephalography (EEG), magnetoencephalography (MEG) and related techniques are prone to glitches, slow drift, steps, etc., that contaminate the data and interfere with the analysis and interpretation. These artifacts are usually addressed in a preprocessing phase that attempts to remove them or minimize their impact. This paper offers a set of useful techniques for this purpose: robust detrending, robust rereferencing, outlier detection, data interpolation (inpainting), step removal, and filter ringing artifact removal. These techniques provide a less wasteful alternative to discarding corrupted trials or channels, and they are relatively immune to artifacts that disrupt alternative approaches such as filtering. Robust detrending allows slow drifts and common mode signals to be factored out while avoiding the deleterious effects of glitches. Robust rereferencing reduces the impact of artifacts on the reference. Inpainting allows corrupt data to be interpolated from intact parts based on the correlation structure estimated over the intact parts. Outlier detection allows the corrupt parts to be identified. Step removal fixes the high-amplitude flux jump artifacts that are common with some MEG systems. Ringing removal allows the ringing response of the antialiasing filter to glitches (steps, pulses) to be suppressed. The performance of the methods is illustrated and evaluated using synthetic data and data from real EEG and MEG systems. These methods, which are mainly automatic and require little tuning, can greatly improve the quality of the data. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Fitting Handled Objects into Apertures by 17- to 36-Month-Old Children: The Dynamics of Spatial Coordination

ERIC Educational Resources Information Center

Jung, Wendy P.; Kahrs, Björn A.; Lockman, Jeffrey J.

2018-01-01

Handled artifacts are ubiquitous in human technology, but how young children engage in spatially coordinated behaviors with these artifacts is not well understood. To address this issue, children (N = 30) from 17-36 months were studied with motion tracking technology as they fit the distal segment of a handled artifact into a slot. The handle was…

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr

2015-05-15

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogrammore » with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of two conjugate PAR images. To evaluate the proposed algorithm, digital XCAT and physical dynamic cardiac phantom datasets are used. The XCAT phantom datasets were generated with heart rates of 70 and 100 bpm, respectively, by assuming a system rotation time of 300 ms. A physical dynamic cardiac phantom was scanned using a slowly rotating XCT system so that the effective heart rate will be 70 bpm for a system rotation speed of 300 ms. Results: In the XCAT phantom experiment, motion-compensated 3D images obtained from the proposed algorithm show coronary arteries with fewer motion artifacts for all phases. Moreover, object boundaries contaminated by motion are well restored. Even though object positions and boundary shapes are still somewhat different from the ground truth in some cases, the authors see that visibilities of coronary arteries are improved noticeably and motion artifacts are reduced considerably. The physical phantom study also shows that the visual quality of motion-compensated images is greatly improved. Conclusions: The authors propose a novel PAR image-based cardiac motion estimation and compensation algorithm. The algorithm requires an angular scan range of less than 360°. The excellent performance of the proposed algorithm is illustrated by using digital XCAT and physical dynamic cardiac phantom datasets.« less

Number of fragments, margin status and thermal artifacts of conized specimens from LLETZ surgery to treat cervical intraepithelial neoplasia.

PubMed

Bittencourt, Dulcimary Dias; Zanine, Rita Maira; Sebastião, Ana Martins; Taha, Nabiha Saadi; Speck, Neila Góis; Ribalta, Julisa Chamorro Lascasas

2012-01-01

Large loop excision of the transformation zone (LLETZ) is a nontraumatic cut and coagulation method with several advantages, but it induces thermal artifacts in the cut region. The aim here was to assess the correlations of age, number of fragments, lesion grade and degree of thermal artifacts with margin quality in conized specimens from LLETZ for cervical intraepithelial neoplasia (CIN). Cross-sectional study at Universidade Federal de São Paulo (Unifesp). The records and histopathology findings of 118 women who underwent LLETZ between 1999 and 2007 were reviewed. Age, number of fragments, lesion grade, degree of thermal artifacts and margin quality were assessed. The patients' mean age was 27.14 years; 63.6% had been diagnosed with CIN II and 36.4% with CIN III. The lesion was removed as a single fragment in 79.6% of the cases. The margins were free from intraepithelial neoplasia in 85.6% and compromised in the endocervical margin in 6.8%. Fragment damage due to artifacts occurred in 2.5%. Severe artifacts occurred in 22.8%. Women aged 30 years or over presented more cases of CIN III (P < 0.0004). Neoplastic compromising of surgical margins and severe artifacts occurred more often in cases in which two or more fragments were removed, and in patients aged 30 years or over. CIN III in women aged 30 or over, when removed in two or more fragments during LLETZ, presented a greater number of compromised margins and greater severity of thermal artifacts.

MRI artifact reduction and quality improvement in the upper abdomen with PROPELLER and prospective acquisition correction (PACE) technique.

PubMed

Hirokawa, Yuusuke; Isoda, Hiroyoshi; Maetani, Yoji S; Arizono, Shigeki; Shimada, Kotaro; Togashi, Kaori

2008-10-01

The purpose of this study was to evaluate the effectiveness of the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER [BLADE in the MR systems from Siemens Medical Solutions]) with a respiratory compensation technique for motion correction, image noise reduction, improved sharpness of liver edge, and image quality of the upper abdomen. Twenty healthy adult volunteers with a mean age of 28 years (age range, 23-42 years) underwent upper abdominal MRI with a 1.5-T scanner. For each subject, fat-saturated T2-weighted turbo spin-echo (TSE) sequences with respiratory compensation (prospective acquisition correction [PACE]) were performed with and without the BLADE technique. Ghosting artifact, artifacts except ghosting artifact such as respiratory motion and bowel movement, sharpness of liver edge, image noise, and overall image quality were evaluated visually by three radiologists using a 5-point scale for qualitative analysis. The Wilcoxon's signed rank test was used to determine whether a significant difference existed between images with and without BLADE. A p value less than 0.05 was considered to be statistically significant. In the BLADE images, image artifacts, sharpness of liver edge, image noise, and overall image quality were significantly improved (p < 0.001). With the BLADE technique, T2-weighted TSE images of the upper abdomen could provide reduced image artifacts including ghosting artifact and image noise and provide better image quality.

A 160 μA biopotential acquisition IC with fully integrated IA and motion artifact suppression.

PubMed

Van Helleputte, Nick; Kim, Sunyoung; Kim, Hyejung; Kim, Jong Pal; Van Hoof, Chris; Yazicioglu, Refet Firat

2012-12-01

This paper proposes a 3-channel biopotential monitoring ASIC with simultaneous electrode-tissue impedance measurements which allows real-time estimation of motion artifacts on each channel using an an external μC. The ASIC features a high performance instrumentation amplifier with fully integrated sub-Hz HPF rejecting rail-to-rail electrode-offset voltages. Each readout channel further has a programmable gain amplifier and programmable 4th order low-pass filter. Time-multiplexed 12 b SAR-ADCs are used to convert all the analog data to digital. The ASIC achieves >; 115 dB of CMRR (at 50/60 Hz), a high input impedance of >; 1 GΩ and low noise (1.3 μVrms in 100 Hz). Unlike traditional methods, the ASIC is capable of actual motion artifact suppression in the analog domain before final amplification. The complete ASIC core operates from 1.2 V with 2 V digital IOs and consumes 200 μW when all 3 channels are active.

Articulation Artifacts During Overt Language Production in Event-Related Brain Potentials: Description and Correction.

PubMed

Ouyang, Guang; Sommer, Werner; Zhou, Changsong; Aristei, Sabrina; Pinkpank, Thomas; Abdel Rahman, Rasha

2016-11-01

Overt articulation produces strong artifacts in the electroencephalogram and in event-related potentials (ERPs), posing a serious problem for investigating language production with these variables. Here we describe the properties of articulation-related artifacts and propose a novel correction procedure. Experiment 1 co-recorded ERPs and trajectories of the articulators with an electromagnetic articulograph from a single participant. The generalization of the findings from the single participant to standard picture naming was investigated in Experiment 2. Both experiments provided evidence that articulation-induced artifacts may start up to 300 ms or more prior to voice onset or voice key onset-depending on the specific measure; they are highly similar in topography across many different phoneme patterns and differ mainly in their time course and amplitude. ERPs were separated from articulation-related artifacts with residue iteration decomposition (RIDE). After obtaining the artifact-free ERPs, their correlations with the articulatory trajectories dropped near to zero. Artifact removal with independent component analysis was less successful; while correlations with the articulatory movements remained substantial, early components prior to voice onset were attenuated in reconstructed ERPs. These findings offer new insights into the nature of articulation artifacts; together with RIDE as method for artifact removal the present report offers a fresh perspective for ERP studies requiring overt articulation.

Non-rigid Motion Correction in 3D Using Autofocusing with Localized Linear Translations

PubMed Central

Cheng, Joseph Y.; Alley, Marcus T.; Cunningham, Charles H.; Vasanawala, Shreyas S.; Pauly, John M.; Lustig, Michael

2012-01-01

MR scans are sensitive to motion effects due to the scan duration. To properly suppress artifacts from non-rigid body motion, complex models with elements such as translation, rotation, shear, and scaling have been incorporated into the reconstruction pipeline. However, these techniques are computationally intensive and difficult to implement for online reconstruction. On a sufficiently small spatial scale, the different types of motion can be well-approximated as simple linear translations. This formulation allows for a practical autofocusing algorithm that locally minimizes a given motion metric – more specifically, the proposed localized gradient-entropy metric. To reduce the vast search space for an optimal solution, possible motion paths are limited to the motion measured from multi-channel navigator data. The novel navigation strategy is based on the so-called “Butterfly” navigators which are modifications to the spin-warp sequence that provide intrinsic translational motion information with negligible overhead. With a 32-channel abdominal coil, sufficient number of motion measurements were found to approximate possible linear motion paths for every image voxel. The correction scheme was applied to free-breathing abdominal patient studies. In these scans, a reduction in artifacts from complex, non-rigid motion was observed. PMID:22307933

Automated content and quality assessment of full-motion-video for the generation of meta data

NASA Astrophysics Data System (ADS)

Harguess, Josh

2015-05-01

Virtually all of the video data (and full-motion-video (FMV)) that is currently collected and stored in support of missions has been corrupted to various extents by image acquisition and compression artifacts. Additionally, video collected by wide-area motion imagery (WAMI) surveillance systems and unmanned aerial vehicles (UAVs) and similar sources is often of low quality or in other ways corrupted so that it is not worth storing or analyzing. In order to make progress in the problem of automatic video analysis, the first problem that should be solved is deciding whether the content of the video is even worth analyzing to begin with. We present a work in progress to address three types of scenes which are typically found in real-world data stored in support of Department of Defense (DoD) missions: no or very little motion in the scene, large occlusions in the scene, and fast camera motion. Each of these produce video that is generally not usable to an analyst or automated algorithm for mission support and therefore should be removed or flagged to the user as such. We utilize recent computer vision advances in motion detection and optical flow to automatically assess FMV for the identification and generation of meta-data (or tagging) of video segments which exhibit unwanted scenarios as described above. Results are shown on representative real-world video data.

Thematic knowledge, artifact concepts, and the left posterior temporal lobe: Where action and object semantics converge

PubMed Central

Kalénine, Solène; Buxbaum, Laurel J.

2016-01-01

Converging evidence supports the existence of functionally and neuroanatomically distinct taxonomic (similarity-based; e.g., hammer-screwdriver) and thematic (event-based; e.g., hammer-nail) semantic systems. Processing of thematic relations between objects has been shown to selectively recruit the left posterior temporoparietal cortex. Similar posterior regions have been also been shown to be critical for knowledge of relationships between actions and manipulable human-made objects (artifacts). Based on the hypothesis that thematic relationships for artifacts are based, at least in part, on action relationships, we assessed the prediction that the same regions of the left posterior temporoparietal cortex would be critical for conceptual processing of artifact-related actions and thematic relations for artifacts. To test this hypothesis, we evaluated processing of taxonomic and thematic relations for artifact and natural objects as well as artifact action knowledge (gesture recognition) abilities in a large sample of 48 stroke patients with a range of lesion foci in the left hemisphere. Like control participants, patients identified thematic relations faster than taxonomic relations for artifacts, whereas they identified taxonomic relations faster than thematic relations for natural objects. Moreover, response times for identifying thematic relations for artifacts selectively predicted performance in gesture recognition. Whole brain Voxel Based Lesion-Symptom Mapping (VLSM) analyses and Region of Interest (ROI) regression analyses further demonstrated that lesions to the left posterior temporal cortex, overlapping with LTO and visual motion area hMT+, were associated both with relatively slower response times in identifying thematic relations for artifacts and poorer artifact action knowledge in patients. These findings provide novel insights into the functional role of left posterior temporal cortex in thematic knowledge, and suggest that the close association between thematic relations for artifacts and action representations may reflect their common dependence on visual motion and manipulation information. PMID:27389801

Involuntary eye motion correction in retinal optical coherence tomography: Hardware or software solution?

PubMed

Baghaie, Ahmadreza; Yu, Zeyun; D'Souza, Roshan M

2017-04-01

In this paper, we review state-of-the-art techniques to correct eye motion artifacts in Optical Coherence Tomography (OCT) imaging. The methods for eye motion artifact reduction can be categorized into two major classes: (1) hardware-based techniques and (2) software-based techniques. In the first class, additional hardware is mounted onto the OCT scanner to gather information about the eye motion patterns during OCT data acquisition. This information is later processed and applied to the OCT data for creating an anatomically correct representation of the retina, either in an offline or online manner. In software based techniques, the motion patterns are approximated either by comparing the acquired data to a reference image, or by considering some prior assumptions about the nature of the eye motion. Careful investigations done on the most common methods in the field provides invaluable insight regarding future directions of the research in this area. The challenge in hardware-based techniques lies in the implementation aspects of particular devices. However, the results of these techniques are superior to those obtained from software-based techniques because they are capable of capturing secondary data related to eye motion during OCT acquisition. Software-based techniques on the other hand, achieve moderate success and their performance is highly dependent on the quality of the OCT data in terms of the amount of motion artifacts contained in them. However, they are still relevant to the field since they are the sole class of techniques with the ability to be applied to legacy data acquired using systems that do not have extra hardware to track eye motion. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

PubMed Central

Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

PubMed

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Joint correction of respiratory motion artifact and partial volume effect in lung/thoracic PET/CT imaging.

PubMed

Chang, Guoping; Chang, Tingting; Pan, Tinsu; Clark, John W; Mawlawi, Osama R

2010-12-01

Respiratory motion artifacts and partial volume effects (PVEs) are two degrading factors that affect the accuracy of image quantification in PET/CT imaging. In this article, the authors propose a joint motion and PVE correction approach (JMPC) to improve PET quantification by simultaneously correcting for respiratory motion artifacts and PVE in patients with lung/thoracic cancer. The objective of this article is to describe this approach and evaluate its performance using phantom and patient studies. The proposed joint correction approach incorporates a model of motion blurring, PVE, and object size/shape. A motion blurring kernel (MBK) is then estimated from the deconvolution of the joint model, while the activity concentration (AC) of the tumor is estimated from the normalization of the derived MBK. To evaluate the performance of this approach, two phantom studies and eight patient studies were performed. In the phantom studies, two motion waveforms-a linear sinusoidal and a circular motion-were used to control the motion of a sphere, while in the patient studies, all participants were instructed to breathe regularly. For the phantom studies, the resultant MBK was compared to the true MBK by measuring a correlation coefficient between the two kernels. The measured sphere AC derived from the proposed method was compared to the true AC as well as the ACs in images exhibiting PVE only and images exhibiting both PVE and motion blurring. For the patient studies, the resultant MBK was compared to the motion extent derived from a 4D-CT study, while the measured tumor AC was compared to the AC in images exhibiting both PVE and motion blurring. For the phantom studies, the estimated MBK approximated the true MBK with an average correlation coefficient of 0.91. The tumor ACs following the joint correction technique were similar to the true AC with an average difference of 2%. Furthermore, the tumor ACs on the PVE only images and images with both motion blur and PVE effects were, on average, 75% and 47.5% (10%) of the true AC, respectively, for the linear (circular) motion phantom study. For the patient studies, the maximum and mean AC/SUV on the PET images following the joint correction are, on average, increased by 125.9% and 371.6%, respectively, when compared to the PET images with both PVE and motion. The motion extents measured from the derived MBK and 4D-CT exhibited an average difference of 1.9 mm. The proposed joint correction approach can improve the accuracy of PET quantification by simultaneously compensating for the respiratory motion artifacts and PVE in lung/thoracic PET/CT imaging.

Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.

PubMed

Mannan, Malik M Naeem; Jeong, Myung Y; Kamran, Muhammad A

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG.

Hybrid ICA—Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals

PubMed Central

Mannan, Malik M. Naeem; Jeong, Myung Y.; Kamran, Muhammad A.

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG. PMID:27199714

Deep learning approaches for detection and removal of ghosting artifacts in MR spectroscopy.

PubMed

Kyathanahally, Sreenath P; Döring, André; Kreis, Roland

2018-09-01

To make use of deep learning (DL) methods to detect and remove ghosting artifacts in clinical magnetic resonance spectra of human brain. Deep learning algorithms, including fully connected neural networks, deep-convolutional neural networks, and stacked what-where auto encoders, were implemented to detect and correct MR spectra containing spurious echo ghost signals. The DL methods were trained on a huge database of simulated spectra with and without ghosting artifacts that represent complex variations of ghost-ridden spectra, transformed to time-frequency spectrograms. The trained model was tested on simulated and in vivo spectra. The preliminary results for ghost detection are very promising, reaching almost 100% accuracy, and the DL ghost removal methods show potential in simulated and in vivo spectra, but need further refinement and quantitative testing. Ghosting artifacts in spectroscopy are problematic, as they superimpose with metabolites and lead to inaccurate quantification. Detection and removal of ghosting artifacts using traditional machine learning approaches with feature extraction/selection is difficult, as ghosts appear at different frequencies. Here, we show that DL methods perform extremely well for ghost detection if the spectra are treated as images in the form of time-frequency representations. Further optimization for in vivo spectra will hopefully confirm their "ghostbusting" capacity. Magn Reson Med 80:851-863, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, H; Kong, V; Jin, J

Purpose: A synchronized moving grid (SMOG) has been proposed to reduce scatter and lag artifacts in cone beam computed tomography (CBCT). However, information is missing in each projection because certain areas are blocked by the grid. A previous solution to this issue is acquiring 2 complimentary projections at each position, which increases scanning time. This study reports our first Result using an inter-projection sensor fusion (IPSF) method to estimate missing projection in our prototype SMOG-based CBCT system. Methods: An in-house SMOG assembling with a 1:1 grid of 3 mm gap has been installed in a CBCT benchtop. The grid movesmore » back and forth in a 3-mm amplitude and up-to 20-Hz frequency. A control program in LabView synchronizes the grid motion with the platform rotation and x-ray firing so that the grid patterns for any two neighboring projections are complimentary. A Catphan was scanned with 360 projections. After scatter correction, the IPSF algorithm was applied to estimate missing signal for each projection using the information from the 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct CBCT images. The CBCTs were compared to those reconstructed using normal projections without applying the SMOG system. Results: The SMOG-IPSF method may reduce image dose by half due to the blocked radiation by the grid. The method almost completely removed scatter related artifacts, such as the cupping artifacts. The evaluation of line pair patterns in the CatPhan suggested that the spatial resolution degradation was minimal. Conclusion: The SMOG-IPSF is promising in reducing scatter artifacts and improving image quality while reducing radiation dose.« less

Artifacts and noise removal in electrocardiograms using independent component analysis.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-26

Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove artifacts and noise in ECG segments of either an individual ECG CSE data base file or all files. The reconstructed ECGs are compared with the original ECG signal. For the four special cases discussed, the R-Peak magnitudes of the CSE data base ECG waveforms before and after applying ICA are also found. In the results, it is shown that in most of the cases, the percentage error in reconstruction is very small. The results show that there is a significant improvement in signal quality, i.e. SNR. All the ECG recording cases dealt showed an improved ECG appearance after the use of ICA. This establishes the efficacy of ICA in elimination of noise and artifacts in electrocardiograms.

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

NASA Astrophysics Data System (ADS)

Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

2012-03-01

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Correction of patient motion in cone-beam CT using 3D-2D registration

NASA Astrophysics Data System (ADS)

Ouadah, S.; Jacobson, M.; Stayman, J. W.; Ehtiati, T.; Weiss, C.; Siewerdsen, J. H.

2017-12-01

Cone-beam CT (CBCT) is increasingly common in guidance of interventional procedures, but can be subject to artifacts arising from patient motion during fairly long (~5-60 s) scan times. We present a fiducial-free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in the intrinsic and extrinsic parameters of geometric calibration. The 3D-2D registration process registers each projection to a prior 3D image by maximizing gradient orientation using the covariance matrix adaptation-evolution strategy optimizer. The resulting rigid transforms are applied to the system projection matrices, and a 3D image is reconstructed via model-based iterative reconstruction. Phantom experiments were conducted using a Zeego robotic C-arm to image a head phantom undergoing 5-15 cm translations and 5-15° rotations. To further test the algorithm, clinical images were acquired with a CBCT head scanner in which long scan times were susceptible to significant patient motion. CBCT images were reconstructed using a penalized likelihood objective function. For phantom studies the structural similarity (SSIM) between motion-free and motion-corrected images was  >0.995, with significant improvement (p  <  0.001) compared to the SSIM values of uncorrected images. Additionally, motion-corrected images exhibited a point-spread function with full-width at half maximum comparable to that of the motion-free reference image. Qualitative comparison of the motion-corrupted and motion-corrected clinical images demonstrated a significant improvement in image quality after motion correction. This indicates that the 3D-2D registration method could provide a useful approach to motion artifact correction under assumptions of local rigidity, as in the head, pelvis, and extremities. The method is highly parallelizable, and the automatic correction of residual geometric calibration errors provides added benefit that could be valuable in routine use.

Image Corruption Detection in Diffusion Tensor Imaging for Post-Processing and Real-Time Monitoring

PubMed Central

Li, Yue; Shea, Steven M.; Lorenz, Christine H.; Jiang, Hangyi; Chou, Ming-Chung; Mori, Susumu

2013-01-01

Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called “corrected Inter-Slice Intensity Discontinuity” (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies. PMID:24204551

In vivo high-resolution structural imaging of large arteries in small rodents using two-photon laser scanning microscopy

NASA Astrophysics Data System (ADS)

Megens, Remco T. A.; Reitsma, Sietze; Prinzen, Lenneke; Oude Egbrink, Mirjam G. A.; Engels, Wim; Leenders, Peter J. A.; Brunenberg, Ellen J. L.; Reesink, Koen D.; Janssen, Ben J. A.; Ter Haar Romeny, Bart M.; Slaaf, Dick W.; van Zandvoort, Marc A. M. J.

2010-01-01

In vivo (molecular) imaging of the vessel wall of large arteries at subcellular resolution is crucial for unraveling vascular pathophysiology. We previously showed the applicability of two-photon laser scanning microscopy (TPLSM) in mounted arteries ex vivo. However, in vivo TPLSM has thus far suffered from in-frame and between-frame motion artifacts due to arterial movement with cardiac and respiratory activity. Now, motion artifacts are suppressed by accelerated image acquisition triggered on cardiac and respiratory activity. In vivo TPLSM is performed on rat renal and mouse carotid arteries, both surgically exposed and labeled fluorescently (cell nuclei, elastin, and collagen). The use of short acquisition times consistently limit in-frame motion artifacts. Additionally, triggered imaging reduces between-frame artifacts. Indeed, structures in the vessel wall (cell nuclei, elastic laminae) can be imaged at subcellular resolution. In mechanically damaged carotid arteries, even the subendothelial collagen sheet (~1 μm) is visualized using collagen-targeted quantum dots. We demonstrate stable in vivo imaging of large arteries at subcellular resolution using TPLSM triggered on cardiac and respiratory cycles. This creates great opportunities for studying (diseased) arteries in vivo or immediate validation of in vivo molecular imaging techniques such as magnetic resonance imaging (MRI), ultrasound, and positron emission tomography (PET).

Transient arterial phase respiratory motion-related artifact in MR imaging of the liver: an analysis of four different gadolinium-based contrast agents.

PubMed

Shah, Mansi R; Flusberg, Milana; Paroder, Viktoriya; Rozenblit, Alla M; Chernyak, Victoria

The purpose was to compare hepatic arterial phase (HAP) respiratory motion artifact (RMA) between gadoxetate, gadobutrol, gadopentetate, and gadobenate. Two hundred cases of each gadolinium agent were included. RMA was assigned using 5-point Likert scale (1=no motion, 5=extreme motion) on precontrast and HAP. RMA increase (increase ≥1 on HAP from precontrast) was the outcome in logistic regression. Odds of RMA increase for gadoxetate were 5.5 (P<.001), 3.6 (P=.034), and 9.5 (P<.001) times higher than gadobutrol, gadopentetate, and gadobenate, respectively. Gadolinium volume and dose were not independent predictors of RMA increase. Gadoxetate has increased odds of RMA compared with other gadolinium agents; tight contrast bolus is not a contributor. Copyright © 2016 Elsevier Inc. All rights reserved.

Classification of coronary artery calcifications according to motion artifacts in chest CT using a convolutional neural network

NASA Astrophysics Data System (ADS)

Šprem, Jurica; de Vos, Bob D.; de Jong, Pim A.; Viergever, Max A.; Išgum, Ivana

2017-02-01

Coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular events (CVEs). CAC can be quantified in chest CT scans acquired in lung screening. However, in these images the reproducibility of CAC quantification is compromised by cardiac motion that occurs during scanning, thereby limiting the reproducibility of CVE risk assessment. We present a system for the identification of CACs strongly affected by cardiac motion artifacts by using a convolutional neural network (CNN). This study included 125 chest CT scans from the National Lung Screening Trial (NLST). Images were acquired with CT scanners from four different vendors (GE, Siemens, Philips, Toshiba) with varying tube voltage, image resolution settings, and without ECG synchronization. To define the reference standard, an observer manually identified CAC lesions and labeled each according to the presence of cardiac motion: strongly affected (positive), mildly affected/not affected (negative). A CNN was designed to automatically label the identified CAC lesions according to the presence of cardiac motion by analyzing a patch from the axial CT slice around each lesion. From 125 CT scans, 9201 CAC lesions were analyzed. 8001 lesions were used for training (19% positive) and the remaining 1200 (50% positive) were used for testing. The proposed CNN achieved a classification accuracy of 85% (86% sensitivity, 84% specificity). The obtained results demonstrate that the proposed algorithm can identify CAC lesions that are strongly affected by cardiac motion. This could facilitate further investigation into the relation of CAC scoring reproducibility and the presence of cardiac motion artifacts.

Removing Contamination-Induced Reconstruction Artifacts from Cryo-electron Tomograms

PubMed Central

Fernandez, Jose-Jesus; Laugks, Ulrike; Schaffer, Miroslava; Bäuerlein, Felix J.B.; Khoshouei, Maryam; Baumeister, Wolfgang; Lucic, Vladan

2016-01-01

Imaging of fully hydrated, vitrified biological samples by electron tomography yields structural information about cellular protein complexes in situ. Here we present a computational procedure that removes artifacts of three-dimensional reconstruction caused by contamination present in samples during imaging by electron microscopy. Applying the procedure to phantom data and electron tomograms of cellular samples significantly improved the resolution and the interpretability of tomograms. Artifacts caused by surface contamination associated with thinning by focused ion beam, as well as those arising from gold fiducial markers and from common, lower contrast contamination, could be removed. Our procedure is widely applicable and is especially suited for applications that strive to reach a higher resolution and involve the use of recently developed, state-of-the-art instrumentation. PMID:26743046

Exploring the effects of transducer models when training convolutional neural networks to eliminate reflection artifacts in experimental photoacoustic images

NASA Astrophysics Data System (ADS)

Allman, Derek; Reiter, Austin; Bell, Muyinatu

2018-02-01

We previously proposed a method of removing reflection artifacts in photoacoustic images that uses deep learning. Our approach generally relies on using simulated photoacoustic channel data to train a convolutional neural network (CNN) that is capable of distinguishing sources from artifacts based on unique differences in their spatial impulse responses (manifested as depth-based differences in wavefront shapes). In this paper, we directly compare a CNN trained with our previous continuous transducer model to a CNN trained with an updated discrete acoustic receiver model that more closely matches an experimental ultrasound transducer. These two CNNs were trained with simulated data and tested on experimental data. The CNN trained using the continuous receiver model correctly classified 100% of sources and 70.3% of artifacts in the experimental data. In contrast, the CNN trained using the discrete receiver model correctly classified 100% of sources and 89.7% of artifacts in the experimental images. The 19.4% increase in artifact classification accuracy indicates that an acoustic receiver model that closely mimics the experimental transducer plays an important role in improving the classification of artifacts in experimental photoacoustic data. Results are promising for developing a method to display CNN-based images that remove artifacts in addition to only displaying network-identified sources as previously proposed.

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections.

PubMed

Gillman, Ashley; Smith, Jye; Thomas, Paul; Rose, Stephen; Dowson, Nicholas

2017-12-01

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment. © 2017 American Association of Physicists in Medicine.

Three‐dimensional motion corrected sensitivity encoding reconstruction for multi‐shot multi‐slice MRI: Application to neonatal brain imaging

PubMed Central

Hughes, Emer J.; Hutter, Jana; Price, Anthony N.; Hajnal, Joseph V.

2017-01-01

Purpose To introduce a methodology for the reconstruction of multi‐shot, multi‐slice magnetic resonance imaging able to cope with both within‐plane and through‐plane rigid motion and to describe its application in structural brain imaging. Theory and Methods The method alternates between motion estimation and reconstruction using a common objective function for both. Estimates of three‐dimensional motion states for each shot and slice are gradually refined by improving on the fit of current reconstructions to the partial k‐space information from multiple coils. Overlapped slices and super‐resolution allow recovery of through‐plane motion and outlier rejection discards artifacted shots. The method is applied to T 2 and T 1 brain scans acquired in different views. Results The procedure has greatly diminished artifacts in a database of 1883 neonatal image volumes, as assessed by image quality metrics and visual inspection. Examples showing the ability to correct for motion and robustness against damaged shots are provided. Combination of motion corrected reconstructions for different views has shown further artifact suppression and resolution recovery. Conclusion The proposed method addresses the problem of rigid motion in multi‐shot multi‐slice anatomical brain scans. Tests on a large collection of potentially corrupted datasets have shown a remarkable image quality improvement. Magn Reson Med 79:1365–1376, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:28626962

Artifacts in Sonography - Part 3.

PubMed

Bönhof, Jörg A; McLaughlin, Glen

2018-06-01

As a continuation of parts 1 1 and 2 2, this article discusses artifacts as caused by insufficient temporal resolution, artifacts in color and spectral Doppler sonography, and information regarding artifacts in sonography with contrast agents. There are artifacts that occur in B-mode sonography as well as in Doppler imaging methods and sonography with contrast agents, such as slice thickness artifacts and bow artifacts, shadows, mirroring, and artifacts due to refraction that appear, for example, as double images, because they are based on the same formation mechanisms. In addition, there are artifacts specific to Doppler sonography, such as the twinkling artifact, and method-based motion artifacts, such as aliasing, the ureteric jet, and due to tissue vibration. The artifacts specific to contrast mode include echoes from usually highly reflective structures that are not contrast bubbles ("leakage"). Contrast agent can also change the transmitting signal so that even structures not containing contrast agent are echogenic ("pseudoenhancement"). While artifacts can cause problems regarding differential diagnosis, they can also be useful for determining the diagnosis. Therefore, effective use of sonography requires both profound knowledge and skilled interpretation of artifacts. © Georg Thieme Verlag KG Stuttgart · New York.

[Tolerance of magnetic resonance imaging in children and adolescents performed in a 1.5 Tesla MR scanner with an open design].

PubMed

Adamietz, B; Cavallaro, A; Radkow, T; Alibek, S; Holter, W; Bautz, W A; Staatz, G

2007-08-01

To investigate the tolerance of MR examinations in children and adolescents performed in a 1.5 Tesla MR scanner with an expanded bore diameter. 163 patients, ages 4 to 25, underwent MR examinations in a 1.5 Tesla MR scanner with an open design (MAGNETOM Espree, Siemens, Erlangen, Germany), characterized by a compact length of 125 cm and an expanded 70 cm bore diameter. MR imaging of the brain was carried out in most cases (78.5 %), followed by examinations of the spinal canal (9.8 %), the extremities (9.2 %) and the neck (2.5 %). The patients were divided into four age groups and the success rate, motion artifacts and diagnostic quality of the MR examinations were assessed using a 3-grade scale. In 119 of 163 patients (73.0 %), MR examination was possible without any motion artifacts. With respect to the different age groups, 41.7 % of the 4 - 7-year-old children, 67.6 % of the 8 - 10-year-old children, 84.1 % of the 11 - 16-year-old children and 95.8 % of the patients older than 17 showed tolerance grade I without motion artifacts and excellent diagnostic image quality. In 39 of 163 children (23.9 %), the MR images showed moderate motion artifacts but had sufficient diagnostic quality. With regard to the different age groups, 52.8 % of the 4 - 7-year-old children, 26.5 % of the 8 - 10-year-old children, 15.9 % of the 11 - 16-year-old children and none of the patients older than 17 showed tolerance grade II with moderate motion artifacts and sufficient diagnostic image quality. In only 4 of 124 children < 10 years old and 1 child > 10 years old, the MR examination was not feasible and had to be repeated under sedation. Pediatric MR imaging using a 1.5 Tesla MR scanner with an open design can be conducted in children and adolescents with excellent acceptance. The failure rate of 3.0 % of cases for pediatric MR imaging is comparable to that of a conventional low-field open MR scanner.

Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury

PubMed Central

Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel’farb, Georgy; Ovechkin, Alexander

2013-01-01

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals. PMID:24307920

Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury.

PubMed

Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel'farb, Georgy; El-Baz, Ayman; Ovechkin, Alexander

2013-07-18

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals.

Pacemaker-induced Metallic Artifacts in Coronary Computed Tomography Angiography: Clinical Feasibility of Single Energy Metal Artifact Reduction Technique.

PubMed

Takayanagi, Tomoya; Arai, Takehiro; Amanuma, Makoto; Sano, Tomonari; Ichiba, Masato; Ishizaka, Kazumasa; Sekine, Takako; Matsutani, Hideyuki; Morita, Hitomi; Takase, Shinichi

2017-01-01

Coronary computed tomography angiography (CCTA) in patients with pacemaker suffers from metallic lead-induced artifacts, which often interfere with accurate assessment of coronary luminal stenosis. The purpose of this study was to assess a frequency of the lead-induced artifacts and artifact-suppression effect by the single energy metal artifact reduction (SEMAR) technique. Forty-one patients with a dual-chamber pacemaker were evaluated using a 320 multi-detector row CT (MDCT). Among them, 22 patients with motion-free full data reconstruction images were the final candidates. Images with and without the SMEAR technique were subjectively compared, and the degree of metallic artifacts was compared. On images without SEMAR, severe metallic artifacts were often observed in the right coronary artery (#1, #2, #3) and distal anterior descending branch (#8). These artifacts were effectively suppressed by SEMAR, and the luminal accessibility was significantly improved in #3 and #8. While pacemaker leads often cause metallic-induced artifacts, SEMAR technique reduced the artifacts and significantly improved the accessibility of coronary lumen in #3 and #8.

Correcting bulk in-plane motion artifacts in MRI using the point spread function.

PubMed

Lin, Wei; Wehrli, Felix W; Song, Hee Kwon

2005-09-01

A technique is proposed for correcting both translational and rotational motion artifacts in magnetic resonance imaging without the need to collect additional navigator data or to perform intensive postprocessing. The method is based on measuring the point spread function (PSF) by attaching one or two point-sized markers to the main imaging object. Following the isolation of a PSF marker from the acquired image, translational motion could be corrected directly from the modulation transfer function, without the need to determine the object's positions during the scan, although the shifts could be extracted if desired. Rotation is detected by analyzing the relative displacements of two such markers. The technique was evaluated with simulations, phantom and in vivo experiments.

Regularly incremented phase encoding - MR fingerprinting (RIPE-MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting.

PubMed

Anderson, Christian E; Wang, Charlie Y; Gu, Yuning; Darrah, Rebecca; Griswold, Mark A; Yu, Xin; Flask, Chris A

2018-04-01

The regularly incremented phase encoding-magnetic resonance fingerprinting (RIPE-MRF) method is introduced to limit the sensitivity of preclinical MRF assessments to pulsatile and respiratory motion artifacts. As compared to previously reported standard Cartesian-MRF methods (SC-MRF), the proposed RIPE-MRF method uses a modified Cartesian trajectory that varies the acquired phase-encoding line within each dynamic MRF dataset. Phantoms and mice were scanned without gating or triggering on a 7T preclinical MRI scanner using the RIPE-MRF and SC-MRF methods. In vitro phantom longitudinal relaxation time (T 1 ) and transverse relaxation time (T 2 ) measurements, as well as in vivo liver assessments of artifact-to-noise ratio (ANR) and MRF-based T 1 and T 2 mean and standard deviation, were compared between the two methods (n = 5). RIPE-MRF showed significant ANR reductions in regions of pulsatility (P < 0.005) and respiratory motion (P < 0.0005). RIPE-MRF also exhibited improved precision in T 1 and T 2 measurements in comparison to the SC-MRF method (P <  0.05). The RIPE-MRF and SC-MRF methods displayed similar mean T 1 and T 2 estimates (difference in mean values < 10%). These results show that the RIPE-MRF method can provide effective motion artifact suppression with minimal impact on T 1 and T 2 accuracy for in vivo small animal MRI studies. Magn Reson Med 79:2176-2182, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

PubMed

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

A Study on the Optimal Positions of ECG Electrodes in a Garment for the Design of ECG-Monitoring Clothing for Male.

PubMed

Cho, Hakyung; Lee, Joo Hyeon

2015-09-01

Smart clothing is a sort of wearable device used for ubiquitous health monitoring. It provides comfort and efficiency in vital sign measurements and has been studied and developed in various types of monitoring platforms such as T-shirt and sports bra. However, despite these previous approaches, smart clothing for electrocardiography (ECG) monitoring has encountered a serious shortcoming relevant to motion artifacts caused by wearer movement. In effect, motion artifacts are one of the major problems in practical implementation of most wearable health-monitoring devices. In the ECG measurements collected by a garment, motion artifacts are usually caused by improper location of the electrode, leading to lack of contact between the electrode and skin with body motion. The aim of this study was to suggest a design for ECG-monitoring clothing contributing to reduction of motion artifacts. Based on the clothing science theory, it was assumed in this study that the stability of the electrode in a dynamic state differed depending on the electrode location in an ECG-monitoring garment. Founded on this assumption, effects of 56 electrode positions were determined by sectioning the surface of the garment into grids with 6 cm intervals in the front and back of the bodice. In order to determine the optimal locations of the ECG electrodes from the 56 positions, ECG measurements were collected from 10 participants at every electrode position in the garment while the wearer was in motion. The electrode locations indicating both an ECG measurement rate higher than 80.0 % and a large amplitude during motion were selected as the optimal electrode locations. The results of this analysis show four electrode locations with consistently higher ECG measurement rates and larger amplitudes amongst the 56 locations. These four locations were abstracted to be least affected by wearer movement in this research. Based on this result, a design of the garment-formed ECG monitoring platform reflecting the optimal positions of the electrode was suggested.

Clinical Feasibility of Free-Breathing Dynamic T1-Weighted Imaging With Gadoxetic Acid-Enhanced Liver Magnetic Resonance Imaging Using a Combination of Variable Density Sampling and Compressed Sensing.

PubMed

Yoon, Jeong Hee; Yu, Mi Hye; Chang, Won; Park, Jin-Young; Nickel, Marcel Dominik; Son, Yohan; Kiefer, Berthold; Lee, Jeong Min

2017-10-01

The purpose of the study was to investigate the clinical feasibility of free-breathing dynamic T1-weighted imaging (T1WI) using Cartesian sampling, compressed sensing, and iterative reconstruction in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI). This retrospective study was approved by our institutional review board, and the requirement for informed consent was waived. A total of 51 patients at high risk of breath-holding failure underwent dynamic T1WI in a free-breathing manner using volumetric interpolated breath-hold (BH) examination with compressed sensing reconstruction (CS-VIBE) and hard gating. Timing, motion artifacts, and image quality were evaluated by 4 radiologists on a 4-point scale. For patients with low image quality scores (<3) on the late arterial phase, respiratory motion-resolved (extradimension [XD]) reconstruction was additionally performed and reviewed in the same manner. In addition, in 68.6% (35/51) patients who had previously undergone liver MRI, image quality and motion artifacts on dynamic phases using CS-VIBE were compared with previous BH-T1WIs. In all patients, adequate arterial-phase timing was obtained at least once. Overall image quality of free-breathing T1WI was 3.30 ± 0.59 on precontrast and 2.68 ± 0.70, 2.93 ± 0.65, and 3.30 ± 0.49 on early arterial, late arterial, and portal venous phases, respectively. In 13 patients with lower than average image quality (<3) on the late arterial phase, motion-resolved reconstructed T1WI (XD-reconstructed CS-VIBE) significantly reduced motion artifacts (P < 0.002-0.021) and improved image quality (P < 0.0001-0.002). In comparison with previous BH-T1WI, CS-VIBE with hard gating or XD reconstruction showed less motion artifacts and better image quality on precontrast, arterial, and portal venous phases (P < 0.0001-0.013). Volumetric interpolated breath-hold examination with compressed sensing has the potential to provide consistent, motion-corrected free-breathing dynamic T1WI for liver MRI in patients at high risk of breath-holding failure.

High-Resolution Multi-Shot Spiral Diffusion Tensor Imaging with Inherent Correction of Motion-Induced Phase Errors

PubMed Central

Truong, Trong-Kha; Guidon, Arnaud

2014-01-01

Purpose To develop and compare three novel reconstruction methods designed to inherently correct for motion-induced phase errors in multi-shot spiral diffusion tensor imaging (DTI) without requiring a variable-density spiral trajectory or a navigator echo. Theory and Methods The first method simply averages magnitude images reconstructed with sensitivity encoding (SENSE) from each shot, whereas the second and third methods rely on SENSE to estimate the motion-induced phase error for each shot, and subsequently use either a direct phase subtraction or an iterative conjugate gradient (CG) algorithm, respectively, to correct for the resulting artifacts. Numerical simulations and in vivo experiments on healthy volunteers were performed to assess the performance of these methods. Results The first two methods suffer from a low signal-to-noise ratio (SNR) or from residual artifacts in the reconstructed diffusion-weighted images and fractional anisotropy maps. In contrast, the third method provides high-quality, high-resolution DTI results, revealing fine anatomical details such as a radial diffusion anisotropy in cortical gray matter. Conclusion The proposed SENSE+CG method can inherently and effectively correct for phase errors, signal loss, and aliasing artifacts caused by both rigid and nonrigid motion in multi-shot spiral DTI, without increasing the scan time or reducing the SNR. PMID:23450457

An improved ring removal procedure for in-line x-ray phase contrast tomography

NASA Astrophysics Data System (ADS)

Massimi, Lorenzo; Brun, Francesco; Fratini, Michela; Bukreeva, Inna; Cedola, Alessia

2018-02-01

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

An improved ring removal procedure for in-line x-ray phase contrast tomography.

PubMed

Massimi, Lorenzo; Brun, Francesco; Fratini, Michela; Bukreeva, Inna; Cedola, Alessia

2018-02-12

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

Automatic motion and noise artifact detection in Holter ECG data using empirical mode decomposition and statistical approaches.

PubMed

Lee, Jinseok; McManus, David D; Merchant, Sneh; Chon, Ki H

2012-06-01

We present a real-time method for the detection of motion and noise (MN) artifacts, which frequently interferes with accurate rhythm assessment when ECG signals are collected from Holter monitors. Our MN artifact detection approach involves two stages. The first stage involves the use of the first-order intrinsic mode function (F-IMF) from the empirical mode decomposition to isolate the artifacts' dynamics as they are largely concentrated in the higher frequencies. The second stage of our approach uses three statistical measures on the F-IMF time series to look for characteristics of randomness and variability, which are hallmark signatures of MN artifacts: the Shannon entropy, mean, and variance. We then use the receiver-operator characteristics curve on Holter data from 15 healthy subjects to derive threshold values associated with these statistical measures to separate between the clean and MN artifacts' data segments. With threshold values derived from 15 training data sets, we tested our algorithms on 30 additional healthy subjects. Our results show that our algorithms are able to detect the presence of MN artifacts with sensitivity and specificity of 96.63% and 94.73%, respectively. In addition, when we applied our previously developed algorithm for atrial fibrillation (AF) detection on those segments that have been labeled to be free from MN artifacts, the specificity increased from 73.66% to 85.04% without loss of sensitivity (74.48%-74.62%) on six subjects diagnosed with AF. Finally, the computation time was less than 0.2 s using a MATLAB code, indicating that real-time application of the algorithms is possible for Holter monitoring.

Real-time motion artifacts compensation of ToF sensors data on GPU

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Hoegg, Thomas; Kolb, Andreas

2013-05-01

Over the last decade, ToF sensors attracted many computer vision and graphics researchers. Nevertheless, ToF devices suffer from severe motion artifacts for dynamic scenes as well as low-resolution depth data which strongly justifies the importance of a valid correction. To counterbalance this effect, a pre-processing approach is introduced to greatly improve range image data on dynamic scenes. We first demonstrate the robustness of our approach using simulated data to finally validate our method using sensor range data. Our GPU-based processing pipeline enhances range data reliability in real-time.

Rejection of false saturation data in optical pulse-oximeter

NASA Astrophysics Data System (ADS)

Scalise, Lorenzo; Marchionni, Paolo; Carnielli, Virgilio

2010-04-01

Pulse oximetry (PO) is a non-invasive medical device used for monitoring of the arterial oxygen saturation (SaO2) and in particular of haemoglobin oxygenation in blood. Oxygen saturation is commonly used in any setting where the patient blood oxygen saturation is unstable, including Neonatal Intensive Care Unit (NICU). The main factor affecting PO's output data is the presence of voluntary or involuntary motion artifacts or imperfect skin-sensor contact. Various methods have been employed to reject motion artifact but have met with little success. The aim of the present work is to propose a novel measurement procedure for real-time monitoring and validation of the oxygen saturation data as measured in standard pulse oxymeter. The procedure should be able to individuate and reject erroneous saturation data due to incorrect transducer-skin contact or motion artifact. In the case of short sequences of rejected SpO2 data (time duration< 8s), we report on an algorithm able to substitute the sequence of rejected data with the "most-probable" (rescued) SpO2 data. In total we have analyzed 14 patient for a total of 310 hr, 43 min and 15s, equivalent to a total number of samples of 1118595. For our study, we were interested to download heart rate measured with the ECG (HRECG), the heart rate as measured by the pulse oximeter (HRSAT) and the SpO2 value. In order to remove the erroneous SpO2 values reported in the rough data in coincidence of motion artifact (top, right), we have implemented a specific algorithm which provides at the output a new sequence of SpO2 data (validated SpO2 data). With the aim to "rescue" SpO2 value rejected by the previously presented algorithm, we have implemented an algorithm able to provide the "most-probable" SpO2 values in the case of single rejected values or in the case of short sequences of invalidated data (< 8 s). From these data it is possible to observe how in the 6.8% of the observation time the SpO2 data measured by the pulse oximeter are not validated by the use of our method (corresponding to a total time of 16 hr, 8min and 40s). The use of the proposed algorithm aiming to "rescue" data from short sequences of rejected data (< 8s) allows to increase the validated data of the 2.5%t(equivalent to 8hr, 40 min and 16s), allowing a percent of usable data of the 95.7%. Once implemented in clinic, it could be used to identify the period of the day in which the percent of rejected data increase or correlate this data to clinical procedure in order to intensify clinicians and nurses attention.

Motion artifacts in kidney stone imaging using single-source and dual-source dual-energy CT scanners: a phantom study.

PubMed

Ibrahim, El-Sayed H; Cernigliaro, Joseph G; Pooley, Robert A; Williams, James C; Haley, William E

2015-10-01

Dual-energy computed tomography (DECT) has shown the capability of differentiating uric acid (UA) from non-UA stones with 90-100% accuracy. With the invention of dual-source (DS) scanners, both low- and high-energy images are acquired simultaneously. However, DECT can also be performed by sequential acquisition of both images on single-source (SS) scanners. The objective of this study is to investigate the effects of motion artifacts on stone classification using both SS-DECT and DS-DECT. 114 kidney stones of different types and sizes were imaged on both DS-DECT and SS-DECT scanners with tube voltages of 80 and 140 kVp with and without induced motion. Postprocessing was conducted to create material-specific images from corresponding low- and high-energy images. The dual-energy ratio (DER) and stone material were determined and compared among different scans. For the motionless scans, all stones were correctly classified with SS-DECT, while two cystine stones were misclassified with DS-DECT. When motion was induced, 94% of the stones were misclassified with SS-DECT versus 11% with DS-DECT (P < 0.0001). Stone size was not a factor in stone misclassification under motion. Stone type was not a factor in stone misclassification under motion with SS-DECT, although with DS-DECT, cystine showed higher number of stone misclassification. Motion artifacts could result in stone misclassification in DECT. This effect is more pronounced in SS-DECT versus DS-DECT, especially if stones of different types lie in close proximity to each other. Further, possible misinterpretation of the number of stones (i.e., missing one, or thinking that there are two) in DS-DECT could be a potentially significant problem.

Evaluating motion processing algorithms for use with functional near-infrared spectroscopy data from young children.

PubMed

Delgado Reyes, Lourdes M; Bohache, Kevin; Wijeakumar, Sobanawartiny; Spencer, John P

2018-04-01

Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal components analysis (PCA), correlation-based signal improvement (CBSI), wavelet filtering, and spline interpolation. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Brigadoi et al. compared motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Given that fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. This study addresses that problem by evaluating motion correction algorithms implemented in HomER2. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response. Results showed that targeted PCA (tPCA), spline, and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using quantitative metrics. The CBSI method corrected many of the artifacts present in our data; however, this approach produced sometimes unstable HRFs. The targeted PCA and spline methods proved to be the most robust, performing well across all comparison metrics. When compared head to head, tPCA consistently outperformed spline. We conclude, therefore, that tPCA is an effective technique for correcting motion artifacts in fNIRS data from young children.

NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data.

PubMed

Pnevmatikakis, Eftychios A; Giovannucci, Andrea

2017-11-01

Motion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium. We introduce an algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view (FOV) into overlapping spatial patches along all directions. The patches are registered at a sub-pixel resolution for rigid translation against a regularly updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid artifacts in a piecewise-rigid manner. Existing approaches either do not scale well in terms of computational performance or are targeted to non-rigid artifacts arising just from the finite speed of raster scanning, and thus cannot correct for non-rigid motion observable in datasets from a large FOV. NoRMCorre can be run in an online mode resulting in comparable to or even faster than real time motion registration of streaming data. We evaluate its performance with simple yet intuitive metrics and compare against other non-rigid registration methods on simulated data and in vivo two-photon calcium imaging datasets. Open source Matlab and Python code is also made available. The proposed method and accompanying code can be useful for solving large scale image registration problems in calcium imaging, especially in the presence of non-rigid deformations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

PROMO – Real-time Prospective Motion Correction in MRI using Image-based Tracking

PubMed Central

White, Nathan; Roddey, Cooper; Shankaranarayanan, Ajit; Han, Eric; Rettmann, Dan; Santos, Juan; Kuperman, Josh; Dale, Anders

2010-01-01

Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image-based approach for prospective motion correction is described, which utilizes three orthogonal 2D spiral navigator acquisitions (SP-Navs) along with a flexible image-based tracking method based on the Extended Kalman Filter (EKF) algorithm for online motion measurement. The SP-Nav/EKF framework offers the advantages of image-domain tracking within patient-specific regions-of-interest and reduced sensitivity to off-resonance-induced corruption of rigid-body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady-state error of the SP-Nav/EKF motion estimates of less than 10 % of the motion magnitude, even for large compound motions that included rotations over 15 degrees. A preliminary in vivo application in 3D inversion recovery spoiled gradient echo (IR-SPGR) and 3D fast spin echo (FSE) sequences demonstrates the effectiveness of the SP-Nav/EKF framework for correcting 3D rigid-body head motion artifacts prospectively in high-resolution 3D MRI scans. PMID:20027635

WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ouadah, S; Jacobson, M; Stayman, JW

2016-06-15

Purpose: Intraoperative C-arm cone-beam CT (CBCT) is subject to artifacts arising from patient motion during the fairly long (∼5–20 s) scan times. We present a fiducial free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in geometric calibration. Methods: A 3D-2D registration process was used to register each projection to DRRs computed from the 3D image by maximizing gradient orientation (GO) using the CMA-ES optimizer. The resulting rigid 6 DOF transforms were applied to the system projection matrices, and a 3D image was reconstructed via model-based image reconstruction (MBIR, which accommodates the resulting noncircularmore » orbit). Experiments were conducted using a Zeego robotic C-arm (20 s, 200°, 496 projections) to image a head phantom undergoing various types of motion: 1) 5° lateral motion; 2) 15° lateral motion; and 3) 5° lateral motion with 10 mm periodic inferior-superior motion. Images were reconstructed using a penalized likelihood (PL) objective function, and structural similarity (SSIM) was measured for axial slices of the reconstructed images. A motion-free image was acquired using the same protocol for comparison. Results: There was significant improvement (p < 0.001) in the SSIM of the motion-corrected (MC) images compared to uncorrected images. The SSIM in MC-PL images was >0.99, indicating near identity to the motion-free reference. The point spread function (PSF) measured from a wire in the phantom was restored to that of the reference in each case. Conclusion: The 3D-2D registration method provides a robust framework for mitigation of motion artifacts and is expected to hold for applications in the head, pelvis, and extremities with reasonably constrained operative setup. Further improvement can be achieved by incorporating multiple rigid components and non-rigid deformation within the framework. The method is highly parallelizable and could in principle be run with every acquisition. Research supported by National Institutes of Health Grant No. R01-EB-017226 and academic-industry partnership with Siemens Healthcare (AX Division, Forcheim, Germany).« less

Video compression of coronary angiograms based on discrete wavelet transform with block classification.

PubMed

Ho, B T; Tsai, M J; Wei, J; Ma, M; Saipetch, P

1996-01-01

A new method of video compression for angiographic images has been developed to achieve high compression ratio (~20:1) while eliminating block artifacts which leads to loss of diagnostic accuracy. This method adopts motion picture experts group's (MPEGs) motion compensated prediction to takes advantage of frame to frame correlation. However, in contrast to MPEG, the error images arising from mismatches in the motion estimation are encoded by discrete wavelet transform (DWT) rather than block discrete cosine transform (DCT). Furthermore, the authors developed a classification scheme which label each block in an image as intra, error, or background type and encode it accordingly. This hybrid coding can significantly improve the compression efficiency in certain eases. This method can be generalized for any dynamic image sequences applications sensitive to block artifacts.

Cardiac gating with a pulse oximeter for dual-energy imaging

NASA Astrophysics Data System (ADS)

Shkumat, N. A.; Siewerdsen, J. H.; Dhanantwari, A. C.; Williams, D. B.; Paul, N. S.; Yorkston, J.; Van Metter, R.

2008-11-01

The development and evaluation of a prototype cardiac gating system for double-shot dual-energy (DE) imaging is described. By acquiring both low- and high-kVp images during the resting phase of the cardiac cycle (diastole), heart misalignment between images can be reduced, thereby decreasing the magnitude of cardiac motion artifacts. For this initial implementation, a fingertip pulse oximeter was employed to measure the peripheral pulse waveform ('plethysmogram'), offering potential logistic, cost and workflow advantages compared to an electrocardiogram. A gating method was developed that accommodates temporal delays due to physiological pulse propagation, oximeter waveform processing and the imaging system (software, filter-wheel, anti-scatter Bucky-grid and flat-panel detector). Modeling the diastolic period allowed the calculation of an implemented delay, timp, required to trigger correctly during diastole at any patient heart rate (HR). The model suggests a triggering scheme characterized by two HR regimes, separated by a threshold, HRthresh. For rates at or below HRthresh, sufficient time exists to expose on the same heartbeat as the plethysmogram pulse [timp(HR) = 0]. Above HRthresh, a characteristic timp(HR) delays exposure to the subsequent heartbeat, accounting for all fixed and variable system delays. Performance was evaluated in terms of accuracy and precision of diastole-trigger coincidence and quantitative evaluation of artifact severity in gated and ungated DE images. Initial implementation indicated 85% accuracy in diastole-trigger coincidence. Through the identification of an improved HR estimation method (modified temporal smoothing of the oximeter waveform), trigger accuracy of 100% could be achieved with improved precision. To quantify the effect of the gating system on DE image quality, human observer tests were conducted to measure the magnitude of cardiac artifact under conditions of successful and unsuccessful diastolic gating. Six observers independently measured the artifact in 111 patient DE images. The data indicate that successful diastolic gating results in a statistically significant reduction (p < 0.001) in the magnitude of cardiac motion artifact, with residual artifact attributed primarily to gross patient motion.

Classification and simulation of stereoscopic artifacts in mobile 3DTV content

NASA Astrophysics Data System (ADS)

Boev, Atanas; Hollosi, Danilo; Gotchev, Atanas; Egiazarian, Karen

2009-02-01

We identify, categorize and simulate artifacts which might occur during delivery stereoscopic video to mobile devices. We consider the stages of 3D video delivery dataflow: content creation, conversion to the desired format (multiview or source-plus-depth), coding/decoding, transmission, and visualization on 3D display. Human 3D vision works by assessing various depth cues - accommodation, binocular depth cues, pictorial cues and motion parallax. As a consequence any artifact which modifies these cues impairs the quality of a 3D scene. The perceptibility of each artifact can be estimated through subjective tests. The material for such tests needs to contain various artifacts with different amounts of impairment. We present a system for simulation of these artifacts. The artifacts are organized in groups with similar origins, and each group is simulated by a block in a simulation channel. The channel introduces the following groups of artifacts: sensor limitations, geometric distortions caused by camera optics, spatial and temporal misalignments between video channels, spatial and temporal artifacts caused by coding, transmission losses, and visualization artifacts. For the case of source-plus-depth representation, artifacts caused by format conversion are added as well.

Recovering TMS-evoked EEG responses masked by muscle artifacts.

PubMed

Mutanen, Tuomas P; Kukkonen, Matleena; Nieminen, Jaakko O; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J

2016-10-01

Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) often suffers from large muscle artifacts. Muscle artifacts can be removed using signal-space projection (SSP), but this can make the visual interpretation of the remaining EEG data difficult. We suggest to use an additional step after SSP that we call source-informed reconstruction (SIR). SSP-SIR improves substantially the signal quality of artifactual TMS-EEG data, causing minimal distortion in the neuronal signal components. In the SSP-SIR approach, we first project out the muscle artifact using SSP. Utilizing an anatomical model and the remaining signal, we estimate an equivalent source distribution in the brain. Finally, we map the obtained source estimate onto the original signal space, again using anatomical information. This approach restores the neuronal signals in the sensor space and interpolates EEG traces onto the completely rejected channels. The introduced algorithm efficiently suppresses TMS-related muscle artifacts in EEG while retaining well the neuronal EEG topographies and signals. With the presented method, we can remove muscle artifacts from TMS-EEG data and recover the underlying brain responses without compromising the readability of the signals of interest. Copyright © 2016 Elsevier Inc. All rights reserved.

Monitoring of haemoglobin oxygen saturation in healthy infants using a new generation pulse oximeter which takes motion artifacts into account.

PubMed

Meyts, Isabelle; Reempts, Patrick Van; Boeck, Kris De

2002-12-01

The aim of this study was to establish normal values for overnight oxygen saturation (SpO2) in healthy term infants using an oximeter which takes into account motion artifacts and to compare these to normal values collected with a previous generation oximeter not correcting for motion artifacts. We recorded overnight SpO2 in 26 term, healthy infants (median age 136 days, range 6-364 days) in the home environment using the Nellcor Symphony N 3000 pulse oximeter with an averaging time of 3 s. A sample rate of 5 s was chosen. Motion artifacts were excluded from the analysis. Data were compared with those from a previous study, using the same inclusion and exclusion criteria with the Oxford Medilog. Median (quartiles) SpO2 was 98% (97%-99%). Median percentage of study time below SpO2 94% was 0.2% (0.1%-0.7%); median percentage of study time below SpO2 90% was 0.0% (0.0%-0.01%). Median SpO2with the Oxford oximeter was 97% (96%-98%); percentage of study time below SpO2 94% was 8% (2%-14%); percentage of study time below SpO2 90% was 2% (0%-4%). These data were compared with the Nellcor Symphony data: differences in median SpO2 were significant ( P<0.05); differences in percentage of time below SpO2 94% and 90% were also statistically significant ( P<0.001). we established normal values of oxygen saturation in healthy term infants using the Nellcor Symphony 3000 pulse oximeter. Care should be taken in interpreting values obtained with different types of pulse oximeters.

Segmentation of ECG from Surface EMG Using DWT and EMD: A Comparison Study

NASA Astrophysics Data System (ADS)

Shahbakhti, Mohammad; Heydari, Elnaz; Luu, Gia Thien

2014-10-01

The electrocardiographic (ECG) signal is a major artifact during recording the surface electromyography (SEMG). Removal of this artifact is one of the important tasks before SEMG analysis for biomedical goals. In this paper, the application of discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for elimination of ECG artifact from SEMG is investigated. The focus of this research is to reach the optimized number of decomposed levels using mean power frequency (MPF) by both techniques. In order to implement the proposed methods, ten simulated and three real ECG contaminated SEMG signals have been tested. Signal-to-noise ratio (SNR) and mean square error (MSE) between the filtered and the pure signals are applied as the performance indexes of this research. The obtained results suggest both techniques could remove ECG artifact from SEMG signals fair enough, however, DWT performs much better and faster in real data.

National Elevation Dataset

USGS Publications Warehouse

,

2002-01-01

The National Elevation Dataset (NED) is a new raster product assembled by the U.S. Geological Survey. NED is designed to provide National elevation data in a seamless form with a consistent datum, elevation unit, and projection. Data corrections were made in the NED assembly process to minimize artifacts, perform edge matching, and fill sliver areas of missing data. NED has a resolution of one arc-second (approximately 30 meters) for the conterminous United States, Hawaii, Puerto Rico and the island territories and a resolution of two arc-seconds for Alaska. NED data sources have a variety of elevation units, horizontal datums, and map projections. In the NED assembly process the elevation values are converted to decimal meters as a consistent unit of measure, NAD83 is consistently used as horizontal datum, and all the data are recast in a geographic projection. Older DEM's produced by methods that are now obsolete have been filtered during the NED assembly process to minimize artifacts that are commonly found in data produced by these methods. Artifact removal greatly improves the quality of the slope, shaded-relief, and synthetic drainage information that can be derived from the elevation data. Figure 2 illustrates the results of this artifact removal filtering. NED processing also includes steps to adjust values where adjacent DEM's do not match well, and to fill sliver areas of missing data between DEM's. These processing steps ensure that NED has no void areas and artificial discontinuities have been minimized. The artifact removal filtering process does not eliminate all of the artifacts. In areas where the only available DEM is produced by older methods, then "striping" may still occur.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy.

PubMed

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-10-01

Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4-6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3-8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy

PubMed Central

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-01-01

Purpose: Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4–6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. Methods: The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Results: Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3–8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. Conclusions: 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts. PMID:21992381

Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise

NASA Astrophysics Data System (ADS)

Sun, Yu; Hu, Sijung; Azorin-Peris, Vicente; Greenwald, Stephen; Chambers, Jonathon; Zhu, Yisheng

2011-07-01

With the advance of computer and photonics technology, imaging photoplethysmography [(PPG), iPPG] can provide comfortable and comprehensive assessment over a wide range of anatomical locations. However, motion artifact is a major drawback in current iPPG systems, particularly in the context of clinical assessment. To overcome this issue, a new artifact-reduction method consisting of planar motion compensation and blind source separation is introduced in this study. The performance of the iPPG system was evaluated through the measurement of cardiac pulse in the hand from 12 subjects before and after 5 min of cycling exercise. Also, a 12-min continuous recording protocol consisting of repeated exercises was taken from a single volunteer. The physiological parameters (i.e., heart rate, respiration rate), derived from the images captured by the iPPG system, exhibit functional characteristics comparable to conventional contact PPG sensors. Continuous recordings from the iPPG system reveal that heart and respiration rates can be successfully tracked with the artifact reduction method even in high-intensity physical exercise situations. The outcome from this study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, with clear applications in triage and sports training.

Suppression of stimulus artifact contaminating electrically evoked electromyography.

PubMed

Liu, Jie; Li, Sheng; Li, Xiaoyan; Klein, Cliff; Rymer, William Z; Zhou, Ping

2014-01-01

Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves. The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals. The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using Savitzky-Golay filtering, estimation of the artifact contaminated region with Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them. The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel's M wave recording using a linear electrode array. The developed method can suppress stimulus artifacts contaminating M wave recordings.

Removal of EOG Artifacts from EEG Recordings Using Stationary Subspace Analysis

PubMed Central

Zeng, Hong; Song, Aiguo

2014-01-01

An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. The proposed approach first conducts the blind source separation on the raw EEG recording by the stationary subspace analysis (SSA) algorithm. Unlike the classic blind source separation algorithms, SSA is explicitly tailored to the understanding of distribution changes, where both the mean and the covariance matrix are taken into account. In addition, neither independency nor uncorrelation is required among the sources by SSA. Thereby, it can concentrate artifacts in fewer components than the representative blind source separation methods. Next, the components that are determined to be related to the ocular artifacts are projected back to be subtracted from EEG signals, producing the clean EEG data eventually. The experimental results on both the artificially contaminated EEG data and real EEG data have demonstrated the effectiveness of the proposed method, in particular for the cases where limited number of electrodes are used for the recording, as well as when the artifact contaminated signal is highly nonstationary and the underlying sources cannot be assumed to be independent or uncorrelated. PMID:24550696

Optimizing T2-weighted magnetic resonance sequences for surface coil microimaging of the eye with regard to lid, eyeball and head moving artifacts.

PubMed

Obata, Takayuki; Uemura, Koji; Nonaka, Hiroi; Tamura, Mitsuru; Tanada, Shuji; Ikehira, Hiroo

2006-01-01

To acquire high-resolution magnetic resonance (MR) images, we developed a new blinking artifact reduced pulse (BARP) sequence with a surface coil specialized for microscopic imaging (47 mm in diameter). To reduce eye movement, we ascertained that the subjects' eyes were kept open and fixated to the target in the 1.5-T MR gantry. To reduce motion artifacts from blinking, we inserted rest periods for blinking (1.5 s within every 5 s) during MR scanning (T2-weighted fast spin echo; repetition time, 5 s; echo time, 100 ms; echo train, 11; matrix, 256 x 128; field of view, 5 cm; 1-mm thickness x 30 slices). Three scans (100 s x 3) were performed for each normal subject, and they were added together after automatic adjustment for location to reduce quality loss caused by head motion. T2-weighted MR images were acquired with a high resolution and a high signal-to-noise ratio. Motion artifacts were reduced with BARP, as compared with those with random blinking. Intraocular structures such as the iris and ciliary muscles were clearly visualized. Because the whole eye can be covered with a 1-mm thickness by this method, three-dimensional maps can easily be generated from the obtained images. The application of BARP with a surface coil of the human eye might become a useful and widely adopted procedure for MR microimaging.

Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI.

PubMed

Spisák, Tamás; Jakab, András; Kis, Sándor A; Opposits, Gábor; Aranyi, Csaba; Berényi, Ervin; Emri, Miklós

2014-01-01

Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that "resting-state" fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Fast 3D shape measurements with reduced motion artifacts

NASA Astrophysics Data System (ADS)

Feng, Shijie; Zuo, Chao; Chen, Qian; Gu, Guohua

2017-10-01

Fringe projection is an extensively used technique for high speed three-dimensional (3D) measurements of dynamic objects. However, the motion often leads to artifacts in reconstructions due to the sequential recording of the set of patterns. In order to reduce the adverse impact of the movement, we present a novel high speed 3D scanning technique combining the fringe projection and stereo. Firstly, promising measuring speed is achieved by modifying the traditional aperiodic sinusoidal patterns so that the fringe images can be cast at kilohertz with the widely used defocusing strategy. Next, a temporal intensity tracing algorithm is developed to further alleviate the influence of motion by accurately tracing the ideal intensity for stereo matching. Then, a combined cost measure is suggested to robustly estimate the cost for each pixel. In comparison with the traditional method where the effect of motion is not considered, experimental results show that the reconstruction accuracy for dynamic objects can be improved by an order of magnitude with the proposed method.

Diffusion imaging quality control via entropy of principal direction distribution.

PubMed

Farzinfar, Mahshid; Oguz, Ipek; Smith, Rachel G; Verde, Audrey R; Dietrich, Cheryl; Gupta, Aditya; Escolar, Maria L; Piven, Joseph; Pujol, Sonia; Vachet, Clement; Gouttard, Sylvain; Gerig, Guido; Dager, Stephen; McKinstry, Robert C; Paterson, Sarah; Evans, Alan C; Styner, Martin A

2013-11-15

Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, "venetian blind" artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies. Copyright © 2013 Elsevier Inc. All rights reserved.

Diffusion imaging quality control via entropy of principal direction distribution

PubMed Central

Oguz, Ipek; Smith, Rachel G.; Verde, Audrey R.; Dietrich, Cheryl; Gupta, Aditya; Escolar, Maria L.; Piven, Joseph; Pujol, Sonia; Vachet, Clement; Gouttard, Sylvain; Gerig, Guido; Dager, Stephen; McKinstry, Robert C.; Paterson, Sarah; Evans, Alan C.; Styner, Martin A.

2013-01-01

Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, “venetian blind” artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies. PMID:23684874

Ballistocardiogram Artifact Removal with a Reference Layer and Standard EEG Cap

PubMed Central

Luo, Qingfei; Huang, Xiaoshan; Glover, Gary H.

2014-01-01

Background In simultaneous EEG-fMRI, the EEG recordings are severely contaminated by ballistocardiogram (BCG) artifacts, which are caused by cardiac pulsations. To reconstruct and remove the BCG artifacts, one promising method is to measure the artifacts in the absence of EEG signal by placing a group of electrodes (BCG electrodes) on a conductive layer (reference layer) insulated from the scalp. However, current BCG reference layer (BRL) methods either use a customized EEG cap composed of electrode pairs, or need to construct the custom reference layer through additional model-building experiments for each EEG-fMRI experiment. These requirements have limited the versatility and efficiency of BRL. The aim of this study is to propose a more practical and efficient BRL method and compare its performance with the most popular BCG removal method, the optimal basis sets (OBS) algorithm. New Method By designing the reference layer as a permanent and reusable cap, the new BRL method is able to be used with a standard EEG cap, and no extra experiments and preparations are needed to use the BRL in an EEG-fMRI experiment. Results The BRL method effectively removed the BCG artifacts from both oscillatory and evoked potential scalp recordings and recovered the EEG signal. Comparison with Existing Method Compared to the OBS, this new BRL method improved the contrast-to-noise ratios of the alpha-wave, visual, and auditory evoked potential signals by 101%, 76%, and 75% respectively, employing 160 BCG electrodes. Using only 20 BCG electrodes, the BRL improved the EEG signal by 74%/26%/41% respectively. Conclusion The proposed method can substantially improve the EEG signal quality compared with traditional methods. PMID:24960423

Non-Invasive In Vivo Ultrasound Temperature Estimation

NASA Astrophysics Data System (ADS)

Bayat, Mahdi

New emerging technologies in thermal therapy require precise monitoring and control of the delivered thermal dose in a variety of situations. The therapeutic temperature changes in target tissues range from few degrees for releasing chemotherapy drugs encapsulated in the thermosensitive liposomes to boiling temperatures in complete ablation of tumors via cell necrosis. High intensity focused ultrasound (HIFU) has emerged as a promising modality for noninvasive surgery due to its ability to create precise mechanical and thermal effects at the target without affecting surrounding tissues. An essential element in all these procedures, however, is accurate estimation of the target tissue temperature during the procedure to ensure its safety and efficacy. The advent of diagnostic imaging tools for guidance of thermal therapy was a key factor in the clinical acceptance of these minimally invasive or noninvasive methods. More recently, ultrasound and magnetic resonance (MR) thermography techniques have been proposed for guidance, monitoring, and control of noninvasive thermal therapies. MR thermography has shown acceptable sensitivity and accuracy in imaging temperature change and it is currently FDA-approved on clinical HIFU units. However, it suffers from limitations like cost of integration with ultrasound therapy system and slow rate of imaging for real time guidance. Ultrasound, on the other hand, has the advantage of real time imaging and ease of integration with the therapy system. An infinitesimal model for imaging temperature change using pulse-echo ultrasound has been demonstrated, including in vivo small-animal imaging. However, this model suffers from limitations that prevent demonstration in more clinically-relevant settings. One limitation stems from the infinitesimal nature of the model, which results in spatial inconsistencies of the estimated temperature field. Another limitation is the sensitivity to tissue motion and deformation during in vivo, which could result in significant artifacts. The first part of this thesis addresses the first limitation by introducing the Recursive Echo Strain Filter (RESF) as a new temperature reconstruction model which largely corrects for the spatial inconsistencies resulting from the infinitesimal model. The performance of this model is validated using the data collected during sub therapeutic temperature changes in the tissue mimicking phantom as well as ex vivo tissue blocks. The second part of this thesis deals with in vivo ultrasound thermography. Tissue deformations caused by natural motions (e.g. respiration, gasping, blood pulsation etc) can create non-thermal changes to the ultrasound echoes which are not accounted for in the derivation of physical model for temperature estimation. These fluctuations can create severe artifacts in the estimated temperature field. Using statistical signal processing techniques an adaptive method is presented which takes advantage of the localized and global availability of these interference patterns and use this data to enhance the estimated temperature in the region of interest. We then propose a model based technique for continuous tracking of temperature in the presence of natural motion and deformation. The method uses the direct discretization of the transient bioheat equation to derive a state space model of temperature change. This model is then used to build a linear estimator based on the Kalman filtering capable of robust estimation of temperature change in the presence of tissue motion and deformation. The robustness of the adaptive and model-based models in removing motion and deformation artifacts is demonstrated using data from in vivo experiments. Both methods are shown to provide effective cancellation of the artifacts with minimal effect on the expected temperature dynamics.

Local collective motion analysis for multi-probe dynamic imaging and microrheology

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2016-08-01

Dynamical artifacts, such as mechanical drift, advection, and hydrodynamic flow, can adversely affect multi-probe dynamic imaging and passive particle-tracking microrheology experiments. Alternatively, active driving by molecular motors can cause interesting non-Brownian motion of probes in local regions. Existing drift-correction techniques, which require large ensembles of probes or fast temporal sampling, are inadequate for handling complex spatio-temporal drifts and non-Brownian motion of localized domains containing relatively few probes. Here, we report an analytical method based on local collective motion (LCM) analysis of as few as two probes for detecting the presence of non-Brownian motion and for accurately eliminating it to reveal the underlying Brownian motion. By calculating an ensemble-average, time-dependent, LCM mean square displacement (MSD) of two or more localized probes and comparing this MSD to constituent single-probe MSDs, we can identify temporal regimes during which either thermal or athermal motion dominates. Single-probe motion, when referenced relative to the moving frame attached to the multi-probe LCM trajectory, provides a true Brownian MSD after scaling by an appropriate correction factor that depends on the number of probes used in LCM analysis. We show that LCM analysis can be used to correct many different dynamical artifacts, including spatially varying drifts, gradient flows, cell motion, time-dependent drift, and temporally varying oscillatory advection, thereby offering a significant improvement over existing approaches.

Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: Block LOw-rank Sparsity with Motion-guidance (BLOSM)

PubMed Central

Chen, Xiao; Salerno, Michael; Yang, Yang; Epstein, Frederick H.

2014-01-01

Purpose Dynamic contrast-enhanced MRI of the heart is well-suited for acceleration with compressed sensing (CS) due to its spatiotemporal sparsity; however, respiratory motion can degrade sparsity and lead to image artifacts. We sought to develop a motion-compensated CS method for this application. Methods A new method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was developed to accelerate first-pass cardiac MRI, even in the presence of respiratory motion. This method divides the images into regions, tracks the regions through time, and applies matrix low-rank sparsity to the tracked regions. BLOSM was evaluated using computer simulations and first-pass cardiac datasets from human subjects. Using rate-4 acceleration, BLOSM was compared to other CS methods such as k-t SLR that employs matrix low-rank sparsity applied to the whole image dataset, with and without motion tracking, and to k-t FOCUSS with motion estimation and compensation that employs spatial and temporal-frequency sparsity. Results BLOSM was qualitatively shown to reduce respiratory artifact compared to other methods. Quantitatively, using root mean squared error and the structural similarity index, BLOSM was superior to other methods. Conclusion BLOSM, which exploits regional low rank structure and uses region tracking for motion compensation, provides improved image quality for CS-accelerated first-pass cardiac MRI. PMID:24243528

Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.

PubMed

Bou Assi, Elie; Rihana, Sandy; Sawan, Mohamad

2014-01-01

Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG) to identify the ocular artifact components. In this study, artifactual components were identified using an adaptive thresholding by means of Kmeans clustering. The denoised EEG signals have been fed into a feature extraction algorithm extracting the band power, the coherence and the phase locking value and inserted into a linear discriminant analysis classifier for a motor imagery classification.

Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

PubMed Central

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

2016-01-01

This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

The energy-efficient implementation of an adaptive-filtering-based QRS complex detection method for wearable devices

NASA Astrophysics Data System (ADS)

Tian, Shudong; Han, Jun; Yang, Jianwei; Zeng, Xiaoyang

2017-10-01

Electrocardiogram (ECG) can be used as a valid way for diagnosing heart disease. To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost, two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal, respectively. The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%, tested under the MIT-BIH ECG database. The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation. Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09 × 10 5 μm2, respectively. Project supported by the National Natural Science Foundation of China (Nos. 61574040, 61234002, 61525401).

Real-time detection of transients in OGLE-IV with application of machine learning

NASA Astrophysics Data System (ADS)

Klencki, Jakub; Wyrzykowski, Łukasz

2016-06-01

The current bottleneck of transient detection in most surveys is the problem of rejecting numerous artifacts from detected candidates. We present a triple-stage hierarchical machine learning system for automated artifact filtering in difference imaging, based on self-organizing maps. The classifier, when tested on the OGLE-IV Transient Detection System, accepts 97% of real transients while removing up to 97.5% of artifacts.

Technical note: suppression of artifacts arising from simultaneous cone-beam imaging and RF transponder tracking in prostate radiotherapy.

PubMed

Poludniowski, Gavin; Webb, Steve; Evans, Philip M

2012-03-01

Artifacts in treatment-room cone-beam reconstructions have been observed at the authors' center when cone-beam acquisition is simultaneous with radio frequency (RF) transponder tracking using the Calypso 4D system (Calypso Medical, Seattle, WA). These artifacts manifest as CT-number modulations and increased CT-noise. The authors present a method for the suppression of the artifacts. The authors propose a three-stage postprocessing technique that can be applied to image volumes previously reconstructed by a cone-beam system. The stages are (1) segmentation of voxels into air, soft-tissue, and bone; (2) application of a 2D spatial-filter in the axial plane to the soft-tissue voxels; and (3) normalization to remove streaking along the axial-direction. The algorithm was tested on patient data acquired with Synergy XVI cone-beam CT systems (Elekta, Crawley, United Kingdom). The computational demands of the suggested correction are small, taking less than 15 s per cone-beam reconstruction on a desktop PC. For a moderate loss of spatial-resolution, the artifacts are strongly suppressed and low-contrast visibility is improved. The correction technique proposed is fast and effective in removing the artifacts caused by simultaneous cone-beam imaging and RF-transponder tracking.

A preliminary study of muscular artifact cancellation in single-channel EEG.

PubMed

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K

2014-10-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-Ray Phase CT

DTIC Science & Technology

2014-06-01

normal, pathologic and Alzheimer’s brains, in which the amyloid precursor protein (APP) will be included as a reference. Toward this goal, we have made...in x-ray flat panel imagers and the artifact removal using a wavelet -analysis-based algorithm” Med. Phys., 28(3): 812-25, 2001. 4. X Wu and H Liu...panel imagers and the artifact removal using a wavelet -analysis-based algorithm” Med. Phys., 28(3): 812-25, 2001 12. Tang X, Hsieh J, Nilsen RA

Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-Ray Phase CT

DTIC Science & Technology

2013-06-01

fibrils in the x-ray phase contrast CT imaging, as a function over the molar concentrations corresponding to normal, pathologic and Alzheimer’s...panel imagers and the artifact removal using a wavelet -analysis-based algorithm” Med. Phys., 28(3): 812-25, 2001. 4. X Wu and H Liu, “Clinical...and the artifact removal using a wavelet -analysis-based algorithm” Med. Phys., 28(3): 812-25, 2001 12. Tang X, Hsieh J, Nilsen RA, Hagiwara A

Evaluation of scatter limitation correction: a new method of correcting photopenic artifacts caused by patient motion during whole-body PET/CT imaging.

PubMed

Miwa, Kenta; Umeda, Takuro; Murata, Taisuke; Wagatsuma, Kei; Miyaji, Noriaki; Terauchi, Takashi; Koizumi, Mitsuru; Sasaki, Masayuki

2016-02-01

Overcorrection of scatter caused by patient motion during whole-body PET/computed tomography (CT) imaging can induce the appearance of photopenic artifacts in the PET images. The present study aimed to quantify the accuracy of scatter limitation correction (SLC) for eliminating photopenic artifacts. This study analyzed photopenic artifacts in (18)F-fluorodeoxyglucose ((18)F-FDG) PET/CT images acquired from 12 patients and from a National Electrical Manufacturers Association phantom with two peripheral plastic bottles that simulated the human body and arms, respectively. The phantom comprised a sphere (diameter, 10 or 37 mm) containing fluorine-18 solutions with target-to-background ratios of 2, 4, and 8. The plastic bottles were moved 10 cm posteriorly between CT and PET acquisitions. All PET data were reconstructed using model-based scatter correction (SC), no scatter correction (NSC), and SLC, and the presence or absence of artifacts on the PET images was visually evaluated. The SC and SLC images were also semiquantitatively evaluated using standardized uptake values (SUVs). Photopenic artifacts were not recognizable in any NSC and SLC image from all 12 patients in the clinical study. The SUVmax of mismatched SLC PET/CT images were almost equal to those of matched SC and SLC PET/CT images. Applying NSC and SLC substantially eliminated the photopenic artifacts on SC PET images in the phantom study. SLC improved the activity concentration of the sphere for all target-to-background ratios. The highest %errors of the 10 and 37-mm spheres were 93.3 and 58.3%, respectively, for mismatched SC, and 73.2 and 22.0%, respectively, for mismatched SLC. Photopenic artifacts caused by SC error induced by CT and PET image misalignment were corrected using SLC, indicating that this method is useful and practical for clinical qualitative and quantitative PET/CT assessment.

The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis

PubMed Central

Cassani, Raymundo; Falk, Tiago H.; Fraga, Francisco J.; Kanda, Paulo A. M.; Anghinah, Renato

2014-01-01

Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are susceptible to several artifacts, such as ocular, muscular, movement, and environmental. To overcome this limitation, existing diagnostic systems commonly depend on experienced clinicians to manually select artifact-free epochs from the collected multi-channel EEG data. Manual selection, however, is a tedious and time-consuming process, rendering the diagnostic system “semi-automated.” Notwithstanding, a number of EEG artifact removal algorithms have been proposed in the literature. The (dis)advantages of using such algorithms in automated AD diagnostic systems, however, have not been documented; this paper aims to fill this gap. Here, we investigate the effects of three state-of-the-art automated artifact removal (AAR) algorithms (both alone and in combination with each other) on AD diagnostic systems based on four different classes of EEG features, namely, spectral, amplitude modulation rate of change, coherence, and phase. The three AAR algorithms tested are statistical artifact rejection (SAR), blind source separation based on second order blind identification and canonical correlation analysis (BSS-SOBI-CCA), and wavelet enhanced independent component analysis (wICA). Experimental results based on 20-channel resting-awake EEG data collected from 59 participants (20 patients with mild AD, 15 with moderate-to-severe AD, and 24 age-matched healthy controls) showed the wICA algorithm alone outperforming other enhancement algorithm combinations across three tasks: diagnosis (control vs. mild vs. moderate), early detection (control vs. mild), and disease progression (mild vs. moderate), thus opening the doors for fully-automated systems that can assist clinicians with early detection of AD, as well as disease severity progression assessment. PMID:24723886

Stimulation artifact correction method for estimation of early cortico-cortical evoked potentials.

PubMed

Trebaul, Lena; Rudrauf, David; Job, Anne-Sophie; Mălîia, Mihai Dragos; Popa, Irina; Barborica, Andrei; Minotti, Lorella; Mîndruţă, Ioana; Kahane, Philippe; David, Olivier

2016-05-01

Effective connectivity can be explored using direct electrical stimulations in patients suffering from drug-resistant focal epilepsies and investigated with intracranial electrodes. Responses to brief electrical pulses mimic the physiological propagation of signals and manifest as cortico-cortical evoked potentials (CCEP). The first CCEP component is believed to reflect direct connectivity with the stimulated region but the stimulation artifact, a sharp deflection occurring during a few milliseconds, frequently contaminates it. In order to recover the characteristics of early CCEP responses, we developed an artifact correction method based on electrical modeling of the electrode-tissue interface. The biophysically motivated artifact templates are then regressed out of the recorded data as in any classical template-matching removal artifact methods. Our approach is able to make the distinction between the physiological responses time-locked to the stimulation pulses and the non-physiological component. We tested the correction on simulated CCEP data in order to quantify its efficiency for different stimulation and recording parameters. We demonstrated the efficiency of the new correction method on simulations of single trial recordings for early responses contaminated with the stimulation artifact. The results highlight the importance of sampling frequency for an accurate analysis of CCEP. We then applied the approach to experimental data. The model-based template removal was compared to a correction based on the subtraction of the averaged artifact. This new correction method of stimulation artifact will enable investigators to better analyze early CCEP components and infer direct effective connectivity in future CCEP studies. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Suppression of Stimulus Artifact Contaminating Electrically Evoked Electromyography

PubMed Central

Liu, Jie; Li, Sheng; Li, Xiaoyan; Klein, Cliff; Rymer, William Z.; Zhou, Ping

2013-01-01

Background Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves. Objectives The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals. Methods The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using the Savitzky-Golay filtering, estimation of the artifact contaminated region with the Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them. Results The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel’s M wave recording using the linear electrode array. Conclusions The developed method can suppress stimulus artifacts contaminating M wave recordings. PMID:24419021

Development and validation of a rebinner with rigid motion correction for the Siemens PET-MR scanner: Application to a large cohort of [11C]-PIB scans.

PubMed

Reilhac, Anthonin; Merida, Ines; Irace, Zacharie; Stephenson, Mary; Weekes, Ashley; Chen, Christopher; Totman, John; Townsend, David W; Fayad, Hadi; Costes, Nicolas

2018-04-13

Objective: Head motion occuring during brain PET studies leads to image blurring and to bias in measured local quantities. Our first objective was to implement an accurate list-mode-based rigid motion correction method for PET data acquired with the mMR synchronous Positron Emission Tomography/Magnetic Resonance (PET/MR) scanner. Our second objective was to optimize the correction for [ 11 C]-PIB scans using simulated and actual data with well-controlled motions. Results: An efficient list-mode based motion correction approach has been implemented, fully optimized and validated using simulated as well as actual PET data. The average spatial resolution loss induced by inaccuracies in motion parameter estimates as well as by the rebinning process was estimated to correspond to a 1 mm increase in Full Width Half Maximum (FWHM) with motion parameters estimated directly from the PET data with a temporal frequency of 20 secs. The results show that it can be safely applied to the [ 11 C]-PIB scans, allowing almost complete removal of motion induced artifacts.The application of the correction method on a large cohort of 11C-PIB scans led to the following observations: i) more than 21% of the scans were affected by a motion greater than 10 mm (39% for subjects with Mini-Mental State Examination -MMSE scores below 20) and ii), the correction led to quantitative changes in Alzheimer-specific cortical regions of up to 30%. Conclusion: The rebinner allows an accurate motion correction at a cost of minimal resolution reduction. The application of the correction to a large cohort of [ 11 C]-PIB scans confirmed the necessity to systematically correct for motion for quantitative results. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Artificial bee colony algorithm for single-trial electroencephalogram analysis.

PubMed

Hsu, Wei-Yen; Hu, Ya-Ping

2015-04-01

In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise removal, feature extraction, feature selection, and feature classification. First, the artifacts and background noise are removed automatically by means of independent component analysis and surface Laplacian filter, respectively. Several potential features, such as band power, autoregressive model, and coherence and phase-locking value, are then extracted for subsequent classification. Next, artificial bee colony (ABC) algorithm is used to select features from the aforementioned feature combination. Finally, selected subfeatures are classified by support vector machine. Comparing with and without artifact removal and feature selection, using a genetic algorithm on single-trial EEG data for 6 subjects, the results indicate that the proposed system is promising and suitable for brain-computer interface applications. © EEG and Clinical Neuroscience Society (ECNS) 2014.

The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

PubMed

Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

2016-09-01

The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

Optimal weighted averaging of event related activity from acquisitions with artifacts.

PubMed

Vollero, Luca; Petrichella, Sara; Innello, Giulio

2016-08-01

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

Motion Detection in Ultrasound Image-Sequences Using Tensor Voting

NASA Astrophysics Data System (ADS)

Inba, Masafumi; Yanagida, Hirotaka; Tamura, Yasutaka

2008-05-01

Motion detection in ultrasound image sequences using tensor voting is described. We have been developing an ultrasound imaging system adopting a combination of coded excitation and synthetic aperture focusing techniques. In our method, frame rate of the system at distance of 150 mm reaches 5000 frame/s. Sparse array and short duration coded ultrasound signals are used for high-speed data acquisition. However, many artifacts appear in the reconstructed image sequences because of the incompleteness of the transmitted code. To reduce the artifacts, we have examined the application of tensor voting to the imaging method which adopts both coded excitation and synthetic aperture techniques. In this study, the basis of applying tensor voting and the motion detection method to ultrasound images is derived. It was confirmed that velocity detection and feature enhancement are possible using tensor voting in the time and space of simulated ultrasound three-dimensional image sequences.

Detection of MRI artifacts produced by intrinsic heart motion using a saliency model

NASA Astrophysics Data System (ADS)

Salguero, Jennifer; Velasco, Nelson; Romero, Eduardo

2017-11-01

Cardiac Magnetic Resonance (CMR) requires synchronization with the ECG to correct many types of noise. However, the complex heart motion frequently produces displaced slices that have to be either ignored or manually corrected since the ECG correction is useless in this case. This work presents a novel methodology that detects the motion artifacts in CMR using a saliency method that highlights the region where the heart chambers are located. Once the Region of Interest (RoI) is set, its center of gravity is determined for the set of slices composing the volume. The deviation of the gravity center is an estimation of the coherence between the slices and is used to find out slices with certain displacement. Validation was performed with distorted real images where a slice is artificially misaligned with respect to set of slices. The displaced slice is found with a Recall of 84% and F Score of 68%.

Use of Video Goggles to Distract Patients During PET/CT Studies of School-Aged Children.

PubMed

Gelfand, Michael J; Harris, Jennifer M; Rich, Amanda C; Kist, Chelsea S

2016-12-01

This study was designed to evaluate the effectiveness of video goggles in distracting children undergoing PET/CT and to determine whether the goggles create CT and PET artifacts. Video goggles with small amounts of internal radioopaque material were used. During whole-body PET/CT imaging, 30 nonsedated patients aged 4-13 y watched videos of their choice using the goggles. Fifteen of the PET/CT studies were performed on a scanner installed in 2006, and the other 15 were performed on a scanner installed in 2013. The fused scans were reviewed for evidence of head movement, and the individual PET and CT scans of the head were reviewed for the presence and severity of streak artifact. The CT exposure settings were recorded for each scan at the anatomic level at which the goggles were worn. Only one of the 30 scans had evidence of significant head motion. Two of the 30 had minor coregistration problems due to motion, and 27 of the 30 had very good to excellent coregistration. For the 2006 scanner, 2 of the 14 evaluable localization CT scans of the head demonstrated no streak artifact in brain tissue, 6 of the 14 had mild streak artifact in brain tissue, and 6 of the 14 had moderate streak artifact in brain tissue. Mild streak artifact in bone was noted in 2 of the 14 studies. For the 2013 scanner, 7 of 15 studies had mild streak artifact in brain tissue and 8 of 15 had no streak artifact in brain tissue, whereas none of the 15 had streak artifact in bone. There were no artifacts attributable to the goggles on the 18 F-FDG PET brain images of any of the 29 evaluable studies. The average CT exposure parameters at the level of the orbits were 36% lower on the 2013 scanner than on the 2006 scanner. Video goggles may be used successfully to distract children undergoing PET with localization CT. The goggles cause no significant degradation of the PET brain images or the CT skull images. The degree of artifact on brain tissue images varies from none to moderate and depends on the CT equipment used. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Effect of motion artifacts and their correction on near-infrared spectroscopy oscillation data: a study in healthy subjects and stroke patients.

PubMed

Selb, Juliette; Yücel, Meryem A; Phillip, Dorte; Schytz, Henrik W; Iversen, Helle K; Vangel, Mark; Ashina, Messoud; Boas, David A

2015-05-01

Functional near-infrared spectroscopy is prone to contamination by motion artifacts (MAs). Motion correction algorithms have previously been proposed and their respective performance compared for evoked rain activation studies. We study instead the effect of MAs on "oscillation" data which is at the basis of functional connectivity and autoregulation studies. We use as our metric of interest the interhemispheric correlation (IHC), the correlation coefficient between symmetrical time series of oxyhemoglobin oscillations. We show that increased motion content results in a decreased IHC. Using a set of motion-free data on which we add real MAs, we find that the best motion correction approach consists of discarding the segments of MAs following a careful approach to minimize the contamination due to band-pass filtering of data from "bad" segments spreading into adjacent "good" segments. Finally, we compare the IHC in a stroke group and in a healthy group that we artificially contaminated with the MA content of the stroke group, in order to avoid the confounding effect of increased motion incidence in the stroke patients. After motion correction, the IHC remains lower in the stroke group in the frequency band around 0.1 and 0.04 Hz, suggesting a physiological origin for the difference. We emphasize the importance of considering MAs as a confounding factor in oscillation-based functional near-infrared spectroscopy studies.

Enhanced Ultrasound Visualization of Brachytherapy Seeds by a Novel Magnetically Induced Motion Imaging Method

DTIC Science & Technology

2007-04-01

We report our progress in developing Magnetically Induced Motion Imaging (MIMI) for unambiguous identification and localization brachytherapy seeds ...tail artifacts in segmented seed images. The second is a method for joining ends of seeds in segmented seed images based on the phase of the detected

Cardiac gating with a pulse oximeter for dual-energy imaging.

PubMed

Shkumat, N A; Siewerdsen, J H; Dhanantwari, A C; Williams, D B; Paul, N S; Yorkston, J; Van Metter, R

2008-11-07

The development and evaluation of a prototype cardiac gating system for double-shot dual-energy (DE) imaging is described. By acquiring both low- and high-kVp images during the resting phase of the cardiac cycle (diastole), heart misalignment between images can be reduced, thereby decreasing the magnitude of cardiac motion artifacts. For this initial implementation, a fingertip pulse oximeter was employed to measure the peripheral pulse waveform ('plethysmogram'), offering potential logistic, cost and workflow advantages compared to an electrocardiogram. A gating method was developed that accommodates temporal delays due to physiological pulse propagation, oximeter waveform processing and the imaging system (software, filter-wheel, anti-scatter Bucky-grid and flat-panel detector). Modeling the diastolic period allowed the calculation of an implemented delay, t(imp), required to trigger correctly during diastole at any patient heart rate (HR). The model suggests a triggering scheme characterized by two HR regimes, separated by a threshold, HR(thresh). For rates at or below HR(thresh), sufficient time exists to expose on the same heartbeat as the plethysmogram pulse [t(imp)(HR) = 0]. Above HR(thresh), a characteristic t(imp)(HR) delays exposure to the subsequent heartbeat, accounting for all fixed and variable system delays. Performance was evaluated in terms of accuracy and precision of diastole-trigger coincidence and quantitative evaluation of artifact severity in gated and ungated DE images. Initial implementation indicated 85% accuracy in diastole-trigger coincidence. Through the identification of an improved HR estimation method (modified temporal smoothing of the oximeter waveform), trigger accuracy of 100% could be achieved with improved precision. To quantify the effect of the gating system on DE image quality, human observer tests were conducted to measure the magnitude of cardiac artifact under conditions of successful and unsuccessful diastolic gating. Six observers independently measured the artifact in 111 patient DE images. The data indicate that successful diastolic gating results in a statistically significant reduction (p < 0.001) in the magnitude of cardiac motion artifact, with residual artifact attributed primarily to gross patient motion.

Removal of eye blink artifacts in wireless EEG sensor networks using reduced-bandwidth canonical correlation analysis.

PubMed

Somers, Ben; Bertrand, Alexander

2016-12-01

Chronic, 24/7 EEG monitoring requires the use of highly miniaturized EEG modules, which only measure a few EEG channels over a small area. For improved spatial coverage, a wireless EEG sensor network (WESN) can be deployed, consisting of multiple EEG modules, which interact through short-distance wireless communication. In this paper, we aim to remove eye blink artifacts in each EEG channel of a WESN by optimally exploiting the correlation between EEG signals from different modules, under stringent communication bandwidth constraints. We apply a distributed canonical correlation analysis (CCA-)based algorithm, in which each module only transmits an optimal linear combination of its local EEG channels to the other modules. The method is validated on both synthetic and real EEG data sets, with emulated wireless transmissions. While strongly reducing the amount of data that is shared between nodes, we demonstrate that the algorithm achieves the same eye blink artifact removal performance as the equivalent centralized CCA algorithm, which is at least as good as other state-of-the-art multi-channel algorithms that require a transmission of all channels. Due to their potential for extreme miniaturization, WESNs are viewed as an enabling technology for chronic EEG monitoring. However, multi-channel analysis is hampered in WESNs due to the high energy cost for wireless communication. This paper shows that multi-channel eye blink artifact removal is possible with a significantly reduced wireless communication between EEG modules.

Removal of eye blink artifacts in wireless EEG sensor networks using reduced-bandwidth canonical correlation analysis

NASA Astrophysics Data System (ADS)

Somers, Ben; Bertrand, Alexander

2016-12-01

Objective. Chronic, 24/7 EEG monitoring requires the use of highly miniaturized EEG modules, which only measure a few EEG channels over a small area. For improved spatial coverage, a wireless EEG sensor network (WESN) can be deployed, consisting of multiple EEG modules, which interact through short-distance wireless communication. In this paper, we aim to remove eye blink artifacts in each EEG channel of a WESN by optimally exploiting the correlation between EEG signals from different modules, under stringent communication bandwidth constraints. Approach. We apply a distributed canonical correlation analysis (CCA-)based algorithm, in which each module only transmits an optimal linear combination of its local EEG channels to the other modules. The method is validated on both synthetic and real EEG data sets, with emulated wireless transmissions. Main results. While strongly reducing the amount of data that is shared between nodes, we demonstrate that the algorithm achieves the same eye blink artifact removal performance as the equivalent centralized CCA algorithm, which is at least as good as other state-of-the-art multi-channel algorithms that require a transmission of all channels. Significance. Due to their potential for extreme miniaturization, WESNs are viewed as an enabling technology for chronic EEG monitoring. However, multi-channel analysis is hampered in WESNs due to the high energy cost for wireless communication. This paper shows that multi-channel eye blink artifact removal is possible with a significantly reduced wireless communication between EEG modules.

Refinement of motion correction strategies for lower-cost CT for under-resourced regions of the world

NASA Astrophysics Data System (ADS)

Wells, Jered R.; Segars, W. Paul; Kigongo, Christopher J. N.; Dobbins, James T., III

2011-03-01

This paper describes a recently developed post-acquisition motion correction strategy for application to lower-cost computed tomography (LCCT) for under-resourced regions of the world. Increased awareness regarding global health and its challenges has encouraged the development of more affordable healthcare options for underserved people worldwide. In regions such as sub-Saharan Africa, intermediate level medical facilities may serve millions with inadequate or antiquated equipment due to financial limitations. In response, the authors have proposed a LCCT design which utilizes a standard chest x-ray examination room with a digital flat panel detector (FPD). The patient rotates on a motorized stage between the fixed cone-beam source and FPD, and images are reconstructed using a Feldkamp algorithm for cone-beam scanning. One of the most important proofs-of-concept in determining the feasibility of this system is the successful correction of undesirable motion. A 3D motion correction algorithm was developed in order to correct for potential patient motion, stage instabilities and detector misalignments which can all lead to motion artifacts in reconstructed images. Motion will be monitored by the radiographic position of fiducial markers to correct for rigid body motion in three dimensions. Based on simulation studies, projection images corrupted by motion were re-registered with average errors of 0.080 mm, 0.32 mm and 0.050 mm in the horizontal, vertical and depth dimensions, respectively. The overall absence of motion artifacts in motion-corrected reconstructions indicates that reasonable amounts of motion may be corrected using this novel technique without significant loss of image quality.

The Effects of Breathing Motion on DCE-MRI Images: Phantom Studies Simulating Respiratory Motion to Compare CAIPIRINHA-VIBE, Radial-VIBE, and Conventional VIBE

PubMed Central

Lee, Chang Kyung; Seo, Nieun; Kim, Bohyun; Huh, Jimi; Kim, Jeong Kon; Lee, Seung Soo; Kim, In Seong; Nickel, Dominik

2017-01-01

Objective To compare the breathing effects on dynamic contrast-enhanced (DCE)-MRI between controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), radial VIBE with k-space-weighted image contrast view-sharing (radial-VIBE), and conventional VIBE (c-VIBE) sequences using a dedicated phantom experiment. Materials and Methods We developed a moving platform to simulate breathing motion. We conducted dynamic scanning on a 3T machine (MAGNETOM Skyra, Siemens Healthcare) using CAIPIRINHA-VIBE, radial-VIBE, and c-VIBE for six minutes per sequence. We acquired MRI images of the phantom in both static and moving modes, and we also obtained motion-corrected images for the motion mode. We compared the signal stability and signal-to-noise ratio (SNR) of each sequence according to motion state and used the coefficients of variation (CoV) to determine the degree of signal stability. Results With motion, CAIPIRINHA-VIBE showed the best image quality, and the motion correction aligned the images very well. The CoV (%) of CAIPIRINHA-VIBE in the moving mode (18.65) decreased significantly after the motion correction (2.56) (p < 0.001). In contrast, c-VIBE showed severe breathing motion artifacts that did not improve after motion correction. For radial-VIBE, the position of the phantom in the images did not change during motion, but streak artifacts significantly degraded image quality, also after motion correction. In addition, SNR increased in both CAIPIRINHA-VIBE (from 3.37 to 9.41, p < 0.001) and radial-VIBE (from 4.3 to 4.96, p < 0.001) after motion correction. Conclusion CAIPIRINHA-VIBE performed best for free-breathing DCE-MRI after motion correction, with excellent image quality. PMID:28246509

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

Ex Vivo Artifacts and Histopathologic Pitfalls in the Lung.

PubMed

Thunnissen, Erik; Blaauwgeers, Hans J L G; de Cuba, Erienne M V; Yick, Ching Yong; Flieder, Douglas B

2016-03-01

Surgical and pathologic handling of lung physically affects lung tissue. This leads to artifacts that alter the morphologic appearance of pulmonary parenchyma. To describe and illustrate mechanisms of ex vivo artifacts that may lead to diagnostic pitfalls. In this study 4 mechanisms of ex vivo artifacts and corresponding diagnostic pitfalls are described and illustrated. The 4 patterns of artifacts are: (1) surgical collapse, due to the removal of air and blood from pulmonary resections; (2) ex vivo contraction of bronchial and bronchiolar smooth muscle; (3) clamping edema of open lung biopsies; and (4) spreading of tissue fragments and individual cells through a knife surface. Morphologic pitfalls include diagnostic patterns of adenocarcinoma, asthma, constrictive bronchiolitis, and lymphedema. Four patterns of pulmonary ex vivo artifacts are important to recognize in order to avoid morphologic misinterpretations.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

Single-layer and dual-layer contrast-enhanced mammography using amorphous selenium flat panel detectors

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Karim, K. S.

2011-09-01

The accumulation of injected contrast agents allows the image enhancement of lesions through the use of contrast-enhanced mammography. In this technique, the combination of two acquired images is used to create an enhanced image. There exist several methods to acquire the images to be combined, which include dual energy subtraction using a single detection layer that suffers from motion artifacts due to patient motion between image acquisition. To mitigate motion artifacts, a detector composed of two layers may be used to simultaneously acquire the low and high energy images. In this work, we evaluate both of these methods using amorphous selenium as the detection material to find the system parameters (tube voltage, filtration, photoconductor thickness and relative intensity ratio) leading to the optimal performance. We then compare the performance of the two detectors under the variation of contrast agent concentration, tumor size and dose. The detectability was found to be most comparable at the lower end of the evaluated factors. The single-layer detector not only led to better contrast, due to its greater spectral separation capabilities, but also had lower quantum noise. The single-layer detector was found to have a greater detectability by a factor of 2.4 for a 2.5 mm radius tumor having a contrast agent concentration of 1.5 mg ml-1 in a 4.5 cm thick 50% glandular breast. The inclusion of motion artifacts in the comparison is part of ongoing research efforts.

Single-layer and dual-layer contrast-enhanced mammography using amorphous selenium flat panel detectors.

PubMed

Allec, N; Abbaszadeh, S; Karim, K S

2011-09-21

The accumulation of injected contrast agents allows the image enhancement of lesions through the use of contrast-enhanced mammography. In this technique, the combination of two acquired images is used to create an enhanced image. There exist several methods to acquire the images to be combined, which include dual energy subtraction using a single detection layer that suffers from motion artifacts due to patient motion between image acquisition. To mitigate motion artifacts, a detector composed of two layers may be used to simultaneously acquire the low and high energy images. In this work, we evaluate both of these methods using amorphous selenium as the detection material to find the system parameters (tube voltage, filtration, photoconductor thickness and relative intensity ratio) leading to the optimal performance. We then compare the performance of the two detectors under the variation of contrast agent concentration, tumor size and dose. The detectability was found to be most comparable at the lower end of the evaluated factors. The single-layer detector not only led to better contrast, due to its greater spectral separation capabilities, but also had lower quantum noise. The single-layer detector was found to have a greater detectability by a factor of 2.4 for a 2.5 mm radius tumor having a contrast agent concentration of 1.5 mg ml(-1) in a 4.5 cm thick 50% glandular breast. The inclusion of motion artifacts in the comparison is part of ongoing research efforts.

Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis.

PubMed

Mantini, D; Franciotti, R; Romani, G L; Pizzella, V

2008-03-01

The major limitation for the acquisition of high-quality magnetoencephalography (MEG) recordings is the presence of disturbances of physiological and technical origins: eye movements, cardiac signals, muscular contractions, and environmental noise are serious problems for MEG signal analysis. In the last years, multi-channel MEG systems have undergone rapid technological developments in terms of noise reduction, and many processing methods have been proposed for artifact rejection. Independent component analysis (ICA) has already shown to be an effective and generally applicable technique for concurrently removing artifacts and noise from the MEG recordings. However, no standardized automated system based on ICA has become available so far, because of the intrinsic difficulty in the reliable categorization of the source signals obtained with this technique. In this work, approximate entropy (ApEn), a measure of data regularity, is successfully used for the classification of the signals produced by ICA, allowing for an automated artifact rejection. The proposed method has been tested using MEG data sets collected during somatosensory, auditory and visual stimulation. It was demonstrated to be effective in attenuating both biological artifacts and environmental noise, in order to reconstruct clear signals that can be used for improving brain source localizations.

A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics

PubMed Central

Yan, Chao-Gan; Cheung, Brian; Kelly, Clare; Colcombe, Stan; Craddock, R. Cameron; Di Martino, Adriana; Li, Qingyang; Zuo, Xi-Nian; Castellanos, F. Xavier; Milham, Michael P.

2014-01-01

Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that “micro” head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD > 0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics – particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion. PMID:23499792

Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

PubMed Central

2015-01-01

Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies. PMID:24417579

Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.

PubMed

Vogel, Wouter V; van Dalen, Jorn A; Wiering, Bas; Huisman, Henkjan; Corstens, Frans H M; Ruers, Theo J M; Oyen, Wim J G

2007-06-01

Multimodality PET/CT of the liver can be performed with an integrated (hybrid) PET/CT scanner or with software fusion of dedicated PET and CT. Accurate anatomic correlation and good image quality of both modalities are important prerequisites, regardless of the applied method. Registration accuracy is influenced by breathing motion differences on PET and CT, which may also have impact on (attenuation correction-related) artifacts, especially in the upper abdomen. The impact of these issues was evaluated for both hybrid PET/CT and software fusion, focused on imaging of the liver. Thirty patients underwent hybrid PET/CT, 20 with CT during expiration breath-hold (EB) and 10 with CT during free breathing (FB). Ten additional patients underwent software fusion of dedicated PET and dedicated expiration breath-hold CT (SF). The image registration accuracy was evaluated at the location of liver borders on CT and uncorrected PET images and at the location of liver lesions. Attenuation-correction artifacts were evaluated by comparison of liver borders on uncorrected and attenuation-corrected PET images. CT images were evaluated for the presence of breathing artifacts. In EB, 40% of patients had an absolute registration error of the diaphragm in the craniocaudal direction of >1 cm (range, -16 to 44 mm), and 45% of lesions were mispositioned >1 cm. In 50% of cases, attenuation-correction artifacts caused a deformation of the liver dome on PET of >1 cm. Poor compliance to breath-hold instructions caused CT artifacts in 55% of cases. In FB, 30% had registration errors of >1 cm (range, -4 to 16 mm) and PET artifacts were less extensive, but all CT images had breathing artifacts. As SF allows independent alignment of PET and CT, no registration errors or artifacts of >1 cm of the diaphragm occurred. Hybrid PET/CT of the liver may have significant registration errors and artifacts related to breathing motion. The extent of these issues depends on the selected breathing protocol and the speed of the CT scanner. No protocol or scanner can guarantee perfect image fusion. On the basis of these findings, recommendations were formulated with regard to scanner requirements, breathing protocols, and reporting.

Three-dimensional constructive interference in steady-state magnetic resonance imaging in syringomyelia: advantages over conventional imaging.

PubMed

Roser, Florian; Ebner, Florian H; Danz, Søren; Riether, Felix; Ritz, Rainer; Dietz, Klaus; Naegele, Thomas; Tatagiba, Marcos S

2008-05-01

Neuroradiology has become indispensable in detecting the pathophysiology in syringomyelia. Constructive interference in steady-state (CISS) magnetic resonance (MR) imaging can provide superior contrast at the sub-arachnoid tissue borders. As this region is critical in preoperative evaluation, the authors hypothesized that CISS imaging would provide superior assessment of syrinx pathology and surgical planning. Based on records collected from a database of 130 patients with syringomyelia treated at the authors' institution, 59 patients were prospectively evaluated with complete neuroradiological examinations. In addition to routine acquisitions with FLAIR, T1- and T2-weighted, and contrast-enhanced MR imaging series, the authors obtained sagittal cardiac-gated sequences to visualize cerebrospinal fluid (CSF) pulsations and axial 3D CISS MR sequences to detect focal arachnoid webs. Statistical qualitative and quantitative evaluations of spinal cord/CSF contrast, spinal cord/CSF delineation, motion artifacts, and artifacts induced by pulsatile CSF flow were performed. The 3D CISS MR sequences demonstrated a contrast-to-noise ratio significantly better than any other routine imaging sequence (p < 0.001). Moreover, 3D CISS imaging can detect more subarachnoid webs and cavitations in the syrinx than T2-weighted MR imaging with less flow-void artifact. The limitation of 3D CISS imaging is a susceptibility to motion artifacts that can cause reduced spatial resolution. Lengthy acquisition times for axial segments can be reduced with multiplanar reconstruction of 3D CISS-generated sagittal images. Constructive interference in steady-state imaging is the MR sequence of choice in the preoperative evaluation of syringomyelia, allowing significantly higher detection rates of focal subarachnoid webs, whereas standard T2-weighted MR imaging shows turbulent CSF flow voids. Constructive interference in steady-state MR imaging enables the neurosurgeon to accurately identify cases requiring decompression for obstructed CSF. Motion artifacts can be eliminated with technical variations.

Comparison of DWI Methods in the Pediatric Brain: PROPELLER Turbo Spin-Echo Imaging Versus Readout-Segmented Echo-Planar Imaging Versus Single-Shot Echo-Planar Imaging.

PubMed

Kim, Tae-Hyung; Baek, Moon-Young; Park, Ji Eun; Ryu, Young Jin; Cheon, Jung-Eun; Kim, In-One; Choi, Young Hun

2018-06-01

The purpose of this study is to compare DWI for pediatric brain evaluation using single-shot echo-planar imaging (EPI), periodically rotated overlapping parallel lines with enhanced reconstruction (Blade), and readout-segmented EPI (Resolve). Blade, Resolve, and single-shot EPI were performed for 27 pediatric patients (median age, 9 years), and three datasets were independently reviewed by two radiologists. Qualitative analyses were performed for perceptive coarseness, image distortion, susceptibility-related changes, motion artifacts, and lesion conspicuity using a 5-point Likert scale. Quantitative analyses were conducted for spatial distortion and signal uniformity of each sequence. Mean scores were 2.13, 3.17, and 3.76 for perceptive coarseness; 4.85, 3.96, and 2.19 for image distortion; 4.76, 3.96, and 2.30 for susceptibility-related change; 4.96, 3.83, and 4.69 for motion artifacts; and 2.71, 3.75, and 1.92 for lesion conspicuity, for Blade, Resolve, and single-shot EPI, respectively. Blade and Resolve showed better quality than did single-shot EPI for image distortion, susceptibility-related changes, and lesion conspicuity. Blade showed less image distortion, fewer susceptibility-related changes, and fewer motion artifacts than did Resolve, whereas lesion conspicuity was better with Resolve. Blade showed increased signal variation compared with Resolve and single-shot EPI (coefficients of variation were 0.10, 0.08, and 0.05 for lateral ventricle; 0.13, 0.09, and 0.05 for centrum semiovale; and 0.16, 0.09, and 0.06 for pons in Blade, Resolve, and single-shot EPI, respectively). DWI with Resolve or Blade yields better quality regarding distortion, susceptibility-related changes, and lesion conspicuity, compared with single-shot EPI. Blade is less susceptible to motion artifacts than is Resolve, whereas Resolve yields less noise and better lesion conspicuity than does Blade.

Acoustic monitoring of first responder's physiology for health and performance surveillance

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2002-08-01

Acoustic sensors have been used to monitor firefighter and soldier physiology to assess health and performance. The Army Research Laboratory has developed a unique body-contacting acoustic sensor that can monitor the health and performance of firefighters and soldiers while they are doing their mission. A gel-coupled sensor has acoustic impedance properties similar to the skin that facilitate the transmission of body sounds into the sensor pad, yet significantly repel ambient airborne noises due to an impedance mismatch. This technology can monitor heartbeats, breaths, blood pressure, motion, voice, and other indicators that can provide vital feedback to the medics and unit commanders. Diverse physiological parameters can be continuously monitored with acoustic sensors and transmitted for remote surveillance of personnel status. Body-worn acoustic sensors located at the neck, breathing mask, and wrist do an excellent job at detecting heartbeats and activity. However, they have difficulty extracting physiology during rigorous exercise or movements due to the motion artifacts sensed. Rigorous activity often indicates that the person is healthy by virtue of being active, and injury often causes the subject to become less active or incapacitated making the detection of physiology easier. One important measure of performance, heart rate variability, is the measure of beat-to-beat timing fluctuations derived from the interval between two adjacent beats. The Lomb periodogram is optimized for non-uniformly sampled data, and can be applied to non-stationary acoustic heart rate features (such as 1st and 2nd heart sounds) to derive heart rate variability and help eliminate errors created by motion artifacts. Simple peak-detection above or below a certain threshold or waveform derivative parameters can produce the timing and amplitude features necessary for the Lomb periodogram and cross-correlation techniques. High-amplitude motion artifacts may contribute to a different frequency or baseline noise due to the timing differences between the noise artifacts and heartbeat features. Data from a firefighter experiment is presented.

An automated method for identifying artifact in independent component analysis of resting-state FMRI.

PubMed

Bhaganagarapu, Kaushik; Jackson, Graeme D; Abbott, David F

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

PubMed Central

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available. PMID:23847511

Simulation of the Beating Heart Based on Physically Modeling aDeformable Balloon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohmer, Damien; Sitek, Arkadiusz; Gullberg, Grant T.

2006-07-18

The motion of the beating heart is complex and createsartifacts in SPECT and x-ray CT images. Phantoms such as the JaszczakDynamic Cardiac Phantom are used to simulate cardiac motion forevaluationof acquisition and data processing protocols used for cardiacimaging. Two concentric elastic membranes filled with water are connectedto tubing and pump apparatus for creating fluid flow in and out of theinner volume to simulate motion of the heart. In the present report, themovement of two concentric balloons is solved numerically in order tocreate a computer simulation of the motion of the moving membranes in theJaszczak Dynamic Cardiac Phantom. A system ofmore » differential equations,based on the physical properties, determine the motion. Two methods aretested for solving the system of differential equations. The results ofboth methods are similar providing a final shape that does not convergeto a trivial circular profile. Finally,a tomographic imaging simulationis performed by acquiring static projections of the moving shape andreconstructing the result to observe motion artifacts. Two cases aretaken into account: in one case each projection angle is sampled for ashort time interval and the other case is sampled for a longer timeinterval. The longer sampling acquisition shows a clear improvement indecreasing the tomographic streaking artifacts.« less

Automatic classification of artifactual ICA-components for artifact removal in EEG signals.

PubMed

Winkler, Irene; Haufe, Stefan; Tangermann, Michael

2011-08-02

Artifacts contained in EEG recordings hamper both, the visual interpretation by experts as well as the algorithmic processing and analysis (e.g. for Brain-Computer Interfaces (BCI) or for Mental State Monitoring). While hand-optimized selection of source components derived from Independent Component Analysis (ICA) to clean EEG data is widespread, the field could greatly profit from automated solutions based on Machine Learning methods. Existing ICA-based removal strategies depend on explicit recordings of an individual's artifacts or have not been shown to reliably identify muscle artifacts. We propose an automatic method for the classification of general artifactual source components. They are estimated by TDSEP, an ICA method that takes temporal correlations into account. The linear classifier is based on an optimized feature subset determined by a Linear Programming Machine (LPM). The subset is composed of features from the frequency-, the spatial- and temporal domain. A subject independent classifier was trained on 640 TDSEP components (reaction time (RT) study, n = 12) that were hand labeled by experts as artifactual or brain sources and tested on 1080 new components of RT data of the same study. Generalization was tested on new data from two studies (auditory Event Related Potential (ERP) paradigm, n = 18; motor imagery BCI paradigm, n = 80) that used data with different channel setups and from new subjects. Based on six features only, the optimized linear classifier performed on level with the inter-expert disagreement (<10% Mean Squared Error (MSE)) on the RT data. On data of the auditory ERP study, the same pre-calculated classifier generalized well and achieved 15% MSE. On data of the motor imagery paradigm, we demonstrate that the discriminant information used for BCI is preserved when removing up to 60% of the most artifactual source components. We propose a universal and efficient classifier of ICA components for the subject independent removal of artifacts from EEG data. Based on linear methods, it is applicable for different electrode placements and supports the introspection of results. Trained on expert ratings of large data sets, it is not restricted to the detection of eye- and muscle artifacts. Its performance and generalization ability is demonstrated on data of different EEG studies.

Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging.

PubMed

Hunter, Chad R R N; Klein, Ran; Beanlands, Rob S; deKemp, Robert A

2016-04-01

Patient motion is a common problem during dynamic positron emission tomography (PET) scans for quantification of myocardial blood flow (MBF). The purpose of this study was to quantify the prevalence of body motion in a clinical setting and evaluate with realistic phantoms the effects of motion on blood flow quantification, including CT attenuation correction (CTAC) artifacts that result from PET-CT misalignment. A cohort of 236 sequential patients was analyzed for patient motion under resting and peak stress conditions by two independent observers. The presence of motion, affected time-frames, and direction of motion was recorded; discrepancy between observers was resolved by consensus review. Based on these results, patient body motion effects on MBF quantification were characterized using the digital NURBS-based cardiac-torso phantom, with characteristic time activity curves (TACs) assigned to the heart wall (myocardium) and blood regions. Simulated projection data were corrected for attenuation and reconstructed using filtered back-projection. All simulations were performed without noise added, and a single CT image was used for attenuation correction and aligned to the early- or late-frame PET images. In the patient cohort, mild motion of 0.5 ± 0.1 cm occurred in 24% and moderate motion of 1.0 ± 0.3 cm occurred in 38% of patients. Motion in the superior/inferior direction accounted for 45% of all detected motion, with 30% in the superior direction. Anterior/posterior motion was predominant (29%) in the posterior direction. Left/right motion occurred in 24% of cases, with similar proportions in the left and right directions. Computer simulation studies indicated that errors in MBF can approach 500% for scans with severe patient motion (up to 2 cm). The largest errors occurred when the heart wall was shifted left toward the adjacent lung region, resulting in a severe undercorrection for attenuation of the heart wall. Simulations also indicated that the magnitude of MBF errors resulting from motion in the superior/inferior and anterior/posterior directions was similar (up to 250%). Body motion effects were more detrimental for higher resolution PET imaging (2 vs 10 mm full-width at half-maximum), and for motion occurring during the mid-to-late time-frames. Motion correction of the reconstructed dynamic image series resulted in significant reduction in MBF errors, but did not account for the residual PET-CTAC misalignment artifacts. MBF bias was reduced further using global partial-volume correction, and using dynamic alignment of the PET projection data to the CT scan for accurate attenuation correction during image reconstruction. Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts.

Self-Motion Perception and Motion Sickness

NASA Technical Reports Server (NTRS)

Fox, Robert A.

1991-01-01

Motion sickness typically is considered a bothersome artifact of exposure to passive motion in vehicles of conveyance. This condition seldom has significant impact on the health of individuals because it is of brief duration, it usually can be prevented by simply avoiding the eliciting condition and, when the conditions that produce it are unavoidable, sickness dissipates with continued exposure. The studies conducted examined several aspects of motion sickness in animal models. A principle objective of these studies was to investigate the neuroanatomy that is important in motion sickness with the objectives of examining both the utility of putative models and defining neural mechanisms that are important in motion sickness.

Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl

2013-03-15

Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phasemore » (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum improvement of the NCC value by 100% and of the RMSD value by 81%. The corresponding maximum improvements for the registration-based approach were 20% and 40%. In phases with very rapid motion the registration-based algorithm obtained better image quality, while the image quality of the MAM algorithm was superior in phases with less motion. The image quality improvement of the MAM optimization was visually confirmed for the different clinical cases. Conclusions: The proposed method allows a software-based best-phase image quality improvement in coronary CT angiography. A short scan data interval at the target heart phase is sufficient, no additional scan data in other cardiac phases are required. The algorithm is therefore directly applicable to any standard cardiac CT acquisition protocol.« less

Effect of causal and acausal filters on elastic and inelastic response spectra

USGS Publications Warehouse

Boore, D.M.; Akkar, Sinan

2003-01-01

With increasing interest in displacement spectra and long-period motions, it is important to check the sensitivity of both elastic and inelastic response spectra to the filtering that is often necessary to remove long period artifacts, even from many modern digital recordings. Using two records of very different character from the M=7.1, 1999 Hector Mine, California, earthquake, we find that the response spectra can be sensitive to the corner periods used in causal filtering, even for oscillator periods much less than the filter corner periods. The effect is most pronounced for inelastic response spectra, where the ratio of response spectra computed from accelerations filtered at 25 and 200 sec can be close to a factor of 2 for oscillator periods less than 5 sec. Published in 2003 by John Wiley and Sons, Ltd.

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

PubMed

Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy

2016-04-01

Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average correction efficiency over the 305 fMRI scans is 18% and the largest achieved efficiency is 71%. The utility of aE-REMCOR on the resting state fMRI connectivity of the default mode network is also examined. The motion-induced position-dependent error in the DMN connectivity analysis is shown to be reduced when aE-REMCOR is utilized. These results demonstrate that aE-REMCOR can be conveniently and efficiently used to improve fMRI motion correction in large clinical EEG-fMRI studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Head motion during MRI acquisition reduces gray matter volume and thickness estimates.

PubMed

Reuter, Martin; Tisdall, M Dylan; Qureshi, Abid; Buckner, Randy L; van der Kouwe, André J W; Fischl, Bruce

2015-02-15

Imaging biomarkers derived from magnetic resonance imaging (MRI) data are used to quantify normal development, disease, and the effects of disease-modifying therapies. However, motion during image acquisition introduces image artifacts that, in turn, affect derived markers. A systematic effect can be problematic since factors of interest like age, disease, and treatment are often correlated with both a structural change and the amount of head motion in the scanner, confounding the ability to distinguish biology from artifact. Here we evaluate the effect of head motion during image acquisition on morphometric estimates of structures in the human brain using several popular image analysis software packages (FreeSurfer 5.3, VBM8 SPM, and FSL Siena 5.0.7). Within-session repeated T1-weighted MRIs were collected on 12 healthy volunteers while performing different motion tasks, including two still scans. We show that volume and thickness estimates of the cortical gray matter are biased by head motion with an average apparent volume loss of roughly 0.7%/mm/min of subject motion. Effects vary across regions and remain significant after excluding scans that fail a rigorous quality check. In view of these results, the interpretation of reported morphometric effects of movement disorders or other conditions with increased motion tendency may need to be revisited: effects may be overestimated when not controlling for head motion. Furthermore, drug studies with hypnotic, sedative, tranquilizing, or neuromuscular-blocking substances may contain spurious "effects" of reduced atrophy or brain growth simply because they affect motion distinct from true effects of the disease or therapeutic process. Copyright © 2014 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, X; Sisniega, A; Zbijewski, W

Purpose: Visualization and quantification of coronary artery calcification and atherosclerotic plaque benefits from coronary artery motion (CAM) artifact elimination. This work applies a rigid linear motion model to a Volume of Interest (VoI) for estimating motion estimation and compensation of image degradation in Coronary Computed Tomography Angiography (CCTA). Methods: In both simulation and testbench experiments, translational CAM was generated by displacement of the imaging object (i.e. simulated coronary artery and explanted human heart) by ∼8 mm, approximating the motion of a main coronary branch. Rotation was assumed to be negligible. A motion degraded region containing a calcification was selected asmore » the VoI. Local residual motion was assumed to be rigid and linear over the acquisition window, simulating motion observed during diastasis. The (negative) magnitude of the image gradient of the reconstructed VoI was chosen as the motion estimation objective and was minimized with Covariance Matrix Adaptation Evolution Strategy (CMAES). Results: Reconstruction incorporated the estimated CAM yielded signification recovery of fine calcification structures as well as reduced motion artifacts within the selected local region. The compensated reconstruction was further evaluated using two image similarity metrics, the structural similarity index (SSIM) and Root Mean Square Error (RMSE). At the calcification site, the compensated data achieved a 3% increase in SSIM and a 91.2% decrease in RMSE in comparison with the uncompensated reconstruction. Conclusion: Results demonstrate the feasibility of our image-based motion estimation method exploiting a local rigid linear model for CAM compensation. The method shows promising preliminary results for the application of such estimation in CCTA. Further work will involve motion estimation of complex motion corrupted patient data acquired from clinical CT scanner.« less

ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings

NASA Astrophysics Data System (ADS)

O'Shea, Daniel J.; Shenoy, Krishna V.

2018-04-01

Objective. Electrical stimulation is a widely used and effective tool in systems neuroscience, neural prosthetics, and clinical neurostimulation. However, electrical artifacts evoked by stimulation prevent the detection of spiking activity on nearby recording electrodes, which obscures the neural population response evoked by stimulation. We sought to develop a method to clean artifact-corrupted electrode signals recorded on multielectrode arrays in order to recover the underlying neural spiking activity. Approach. We created an algorithm, which performs estimation and removal of array artifacts via sequential principal components regression (ERAASR). This approach leverages the similar structure of artifact transients, but not spiking activity, across simultaneously recorded channels on the array, across pulses within a train, and across trials. The ERAASR algorithm requires no special hardware, imposes no requirements on the shape of the artifact or the multielectrode array geometry, and comprises sequential application of straightforward linear methods with intuitive parameters. The approach should be readily applicable to most datasets where stimulation does not saturate the recording amplifier. Main results. The effectiveness of the algorithm is demonstrated in macaque dorsal premotor cortex using acute linear multielectrode array recordings and single electrode stimulation. Large electrical artifacts appeared on all channels during stimulation. After application of ERAASR, the cleaned signals were quiescent on channels with no spontaneous spiking activity, whereas spontaneously active channels exhibited evoked spikes which closely resembled spontaneously occurring spiking waveforms. Significance. We hope that enabling simultaneous electrical stimulation and multielectrode array recording will help elucidate the causal links between neural activity and cognition and facilitate naturalistic sensory protheses.

Evaluation of tumor localization in respiration motion-corrected cone-beam CT: Prospective study in lung

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dzyubak, Oleksandr; Kincaid, Russell; Hertanto, Agung

Purpose: Target localization accuracy of cone-beam CT (CBCT) images used in radiation treatment of respiratory disease sites is affected by motion artifacts (blurring and streaking). The authors have previously reported on a method of respiratory motion correction in thoracic CBCT at end expiration (EE). The previous retrospective study was limited to examination of reducing motion artifacts in a small number of patient cases. They report here on a prospective study in a larger group of lung cancer patients to evaluate respiratory motion-corrected (RMC)-CBCT ability to improve lung tumor localization accuracy and reduce motion artifacts in Linac-mounted CBCT images. A secondmore » study goal examines whether the motion correction derived from a respiration-correlated CT (RCCT) at simulation yields similar tumor localization accuracy at treatment. Methods: In an IRB-approved study, 19 lung cancer patients (22 tumors) received a RCCT at simulation, and on one treatment day received a RCCT, a respiratory-gated CBCT at end expiration, and a 1-min CBCT. A respiration monitor of abdominal displacement was used during all scans. In addition to a CBCT reconstruction without motion correction, the motion correction method was applied to the same 1-min scan. Projection images were sorted into ten bins based on abdominal displacement, and each bin was reconstructed to produce ten intermediate CBCT images. Each intermediate CBCT was deformed to the end expiration state using a motion model derived from RCCT. The deformed intermediate CBCT images were then added to produce a final RMC-CBCT. In order to evaluate the second study goal, the CBCT was corrected in two ways, one using a model derived from the RCCT at simulation [RMC-CBCT(sim)], the other from the RCCT at treatment [RMC-CBCT(tx)]. Image evaluation compared uncorrected CBCT, RMC-CBCT(sim), and RMC-CBCT(tx). The gated CBCT at end expiration served as the criterion standard for comparison. Using automatic rigid image registration, each CBCT was registered twice to the gated CBCT, first aligned to spine, second to tumor in lung. Localization discrepancy was defined as the difference between tumor and spine registration. Agreement in tumor localization with the gated CBCT was further evaluated by calculating a normalized cross correlation (NCC) of pixel intensities within a volume-of-interest enclosing the tumor in lung. Results: Tumor localization discrepancy was reduced with RMC-CBCT(tx) in 17 out of 22 cases relative to no correction. If one considers cases in which tumor motion is 5 mm or more in the RCCT, tumor localization discrepancy is reduced with RMC-CBCT(tx) in 14 out of 17 cases (p = 0.04), and with RMC-CBCT(sim) in 13 out of 17 cases (p = 0.05). Differences in localization discrepancy between correction models [RMC-CBCT(sim) vs RMC-CBCT(tx)] were less than 2 mm. In 21 out of 22 cases, improvement in NCC was higher with RMC-CBCT(tx) relative to no correction (p < 0.0001). Differences in NCC between RMC-CBCT(sim) and RMC-CBCT(tx) were small. Conclusions: Motion-corrected CBCT improves lung tumor localization accuracy and reduces motion artifacts in nearly all cases. Motion correction at end expiration using RCCT acquired at simulation yields similar results to that using a RCCT on the treatment day (2–3 weeks after simulation)« less

Evaluation of tumor localization in respiration motion-corrected cone-beam CT: prospective study in lung.

PubMed

Dzyubak, Oleksandr; Kincaid, Russell; Hertanto, Agung; Hu, Yu-Chi; Pham, Hai; Rimner, Andreas; Yorke, Ellen; Zhang, Qinghui; Mageras, Gig S

2014-10-01

Target localization accuracy of cone-beam CT (CBCT) images used in radiation treatment of respiratory disease sites is affected by motion artifacts (blurring and streaking). The authors have previously reported on a method of respiratory motion correction in thoracic CBCT at end expiration (EE). The previous retrospective study was limited to examination of reducing motion artifacts in a small number of patient cases. They report here on a prospective study in a larger group of lung cancer patients to evaluate respiratory motion-corrected (RMC)-CBCT ability to improve lung tumor localization accuracy and reduce motion artifacts in Linac-mounted CBCT images. A second study goal examines whether the motion correction derived from a respiration-correlated CT (RCCT) at simulation yields similar tumor localization accuracy at treatment. In an IRB-approved study, 19 lung cancer patients (22 tumors) received a RCCT at simulation, and on one treatment day received a RCCT, a respiratory-gated CBCT at end expiration, and a 1-min CBCT. A respiration monitor of abdominal displacement was used during all scans. In addition to a CBCT reconstruction without motion correction, the motion correction method was applied to the same 1-min scan. Projection images were sorted into ten bins based on abdominal displacement, and each bin was reconstructed to produce ten intermediate CBCT images. Each intermediate CBCT was deformed to the end expiration state using a motion model derived from RCCT. The deformed intermediate CBCT images were then added to produce a final RMC-CBCT. In order to evaluate the second study goal, the CBCT was corrected in two ways, one using a model derived from the RCCT at simulation [RMC-CBCT(sim)], the other from the RCCT at treatment [RMC-CBCT(tx)]. Image evaluation compared uncorrected CBCT, RMC-CBCT(sim), and RMC-CBCT(tx). The gated CBCT at end expiration served as the criterion standard for comparison. Using automatic rigid image registration, each CBCT was registered twice to the gated CBCT, first aligned to spine, second to tumor in lung. Localization discrepancy was defined as the difference between tumor and spine registration. Agreement in tumor localization with the gated CBCT was further evaluated by calculating a normalized cross correlation (NCC) of pixel intensities within a volume-of-interest enclosing the tumor in lung. Tumor localization discrepancy was reduced with RMC-CBCT(tx) in 17 out of 22 cases relative to no correction. If one considers cases in which tumor motion is 5 mm or more in the RCCT, tumor localization discrepancy is reduced with RMC-CBCT(tx) in 14 out of 17 cases (p = 0.04), and with RMC-CBCT(sim) in 13 out of 17 cases (p = 0.05). Differences in localization discrepancy between correction models [RMC-CBCT(sim) vs RMC-CBCT(tx)] were less than 2 mm. In 21 out of 22 cases, improvement in NCC was higher with RMC-CBCT(tx) relative to no correction (p < 0.0001). Differences in NCC between RMC-CBCT(sim) and RMC-CBCT(tx) were small. Motion-corrected CBCT improves lung tumor localization accuracy and reduces motion artifacts in nearly all cases. Motion correction at end expiration using RCCT acquired at simulation yields similar results to that using a RCCT on the treatment day (2-3 weeks after simulation).

A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings.

PubMed

Corera, Íñigo; Eciolaza, Adrián; Rubio, Oliver; Malanda, Armando; Rodríguez-Falces, Javier; Navallas, Javier

2018-01-11

Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components. Graphical Abstract The raw scanning-EMG signal (left figure) is processed by the MLSS algorithm in order to remove the artifact interference. Firstly, artifacts are detected from the raw signal, obtaining a validity mask (central figure) that determines the samples that have been contaminated by artifacts. Secondly, a least-squares smoothing procedure in the spatial dimension is applied to the raw signal using the not contaminated samples according to the validity mask. The resulting MLSS-processed scanning-EMG signal (right figure) is clean of artifact interference.

A Fiber-Based Ratiometric Optical Cardiac Mapping Channel Using a Diffraction Grating and Split Detector

PubMed Central

Brown, Ninita H.; Dobrovolny, Hana M.; Gauthier, Daniel J.; Wolf, Patrick D.

2007-01-01

Optical fiber-based mapping systems are used to record the cardiac action potential (AP) throughout the myocardium. The optical AP contains a contraction-induced motion artifact (MA), which makes it difficult to accurately measure the action potential duration (APD). MA is removed by preventing contraction with electrical-mechanical uncoupling drugs, such as 2,3-butanedione monoxime (BDM). We designed a novel fiber-based ratiometric optical channel using a blue light emitting diode, a diffraction grating, and a split photodetector that can accurately measure the cardiac AP without the need for BDM. The channel was designed based on simulations using the optical design software ZEMAX. The channel has an electrical bandwidth of 150 Hz and an root mean-square dark noise of 742 μV. The channel successfully recorded the cardiac AP from the wall of five rabbit heart preparations without the use of BDM. After 20-point median filtering, the mean signal/noise ratio was 25.3 V/V. The APD measured from the base of a rabbit heart was 134 ± 8.4 ms, compared to 137.6 ± 3.3 ms from simultaneous microelectrode recordings. This difference was not statistically significant (p-value = 0.3). The quantity of MA removed was also measured using the motion ratio. The reduction in MA was significant (p-value = 0.0001). This fiber-based system is the first of its kind to enable optical APD measurements in the beating heart wall without the use of BDM. PMID:17416627

Removing Beam Current Artifacts in Helium Ion Microscopy: A Comparison of Image Processing Techniques.

PubMed

Barlow, Anders J; Portoles, Jose F; Sano, Naoko; Cumpson, Peter J

2016-10-01

The development of the helium ion microscope (HIM) enables the imaging of both hard, inorganic materials and soft, organic or biological materials. Advantages include outstanding topographical contrast, superior resolution down to <0.5 nm at high magnification, high depth of field, and no need for conductive coatings. The instrument relies on helium atom adsorption and ionization at a cryogenically cooled tip that is atomically sharp. Under ideal conditions this arrangement provides a beam of ions that is stable for days to weeks, with beam currents in the order of picoamperes. Over time, however, this stability is lost as gaseous contamination builds up in the source region, leading to adsorbed atoms of species other than helium, which ultimately results in beam current fluctuations. This manifests itself as horizontal stripe artifacts in HIM images. We investigate post-processing methods to remove these artifacts from HIM images, such as median filtering, Gaussian blurring, fast Fourier transforms, and principal component analysis. We arrive at a simple method for completely removing beam current fluctuation effects from HIM images while maintaining the full integrity of the information within the image.

Reducing Interpolation Artifacts for Mutual Information Based Image Registration

PubMed Central

Soleimani, H.; Khosravifard, M.A.

2011-01-01

Medical image registration methods which use mutual information as similarity measure have been improved in recent decades. Mutual Information is a basic concept of Information theory which indicates the dependency of two random variables (or two images). In order to evaluate the mutual information of two images their joint probability distribution is required. Several interpolation methods, such as Partial Volume (PV) and bilinear, are used to estimate joint probability distribution. Both of these two methods yield some artifacts on mutual information function. Partial Volume-Hanning window (PVH) and Generalized Partial Volume (GPV) methods are introduced to remove such artifacts. In this paper we show that the acceptable performance of these methods is not due to their kernel function. It's because of the number of pixels which incorporate in interpolation. Since using more pixels requires more complex and time consuming interpolation process, we propose a new interpolation method which uses only four pixels (the same as PV and bilinear interpolations) and removes most of the artifacts. Experimental results of the registration of Computed Tomography (CT) images show superiority of the proposed scheme. PMID:22606673

False colors removal on the YCr-Cb color space

NASA Astrophysics Data System (ADS)

Tomaselli, Valeria; Guarnera, Mirko; Messina, Giuseppe

2009-01-01

Post-processing algorithms are usually placed in the pipeline of imaging devices to remove residual color artifacts introduced by the demosaicing step. Although demosaicing solutions aim to eliminate, limit or correct false colors and other impairments caused by a non ideal sampling, post-processing techniques are usually more powerful in achieving this purpose. This is mainly because the input of post-processing algorithms is a fully restored RGB color image. Moreover, post-processing can be applied more than once, in order to meet some quality criteria. In this paper we propose an effective technique for reducing the color artifacts generated by conventional color interpolation algorithms, in YCrCb color space. This solution efficiently removes false colors and can be executed while performing the edge emphasis process.

MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.

PubMed

Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian

2016-01-01

An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods.

Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data

PubMed Central

Plöchl, Michael; Ossandón, José P.; König, Peter

2012-01-01

Eye movements introduce large artifacts to electroencephalographic recordings (EEG) and thus render data analysis difficult or even impossible. Trials contaminated by eye movement and blink artifacts have to be discarded, hence in standard EEG-paradigms subjects are required to fixate on the screen. To overcome this restriction, several correction methods including regression and blind source separation have been proposed. Yet, there is no automated standard procedure established. By simultaneously recording eye movements and 64-channel-EEG during a guided eye movement paradigm, we investigate and review the properties of eye movement artifacts, including corneo-retinal dipole changes, saccadic spike potentials and eyelid artifacts, and study their interrelations during different types of eye- and eyelid movements. In concordance with earlier studies our results confirm that these artifacts arise from different independent sources and that depending on electrode site, gaze direction, and choice of reference these sources contribute differently to the measured signal. We assess the respective implications for artifact correction methods and therefore compare the performance of two prominent approaches, namely linear regression and independent component analysis (ICA). We show and discuss that due to the independence of eye artifact sources, regression-based correction methods inevitably over- or under-correct individual artifact components, while ICA is in principle suited to address such mixtures of different types of artifacts. Finally, we propose an algorithm, which uses eye tracker information to objectively identify eye-artifact related ICA-components (ICs) in an automated manner. In the data presented here, the algorithm performed very similar to human experts when those were given both, the topographies of the ICs and their respective activations in a large amount of trials. Moreover it performed more reliable and almost twice as effective than human experts when those had to base their decision on IC topographies only. Furthermore, a receiver operating characteristic (ROC) analysis demonstrated an optimal balance of false positive and false negative at an area under curve (AUC) of more than 0.99. Removing the automatically detected ICs from the data resulted in removal or substantial suppression of ocular artifacts including microsaccadic spike potentials, while the relevant neural signal remained unaffected. In conclusion the present work aims at a better understanding of individual eye movement artifacts, their interrelations and the respective implications for eye artifact correction. Additionally, the proposed ICA-procedure provides a tool for optimized detection and correction of eye movement-related artifact components. PMID:23087632

Utility of CT-compatible EEG electrodes in critically ill children.

PubMed

Abend, Nicholas S; Dlugos, Dennis J; Zhu, Xiaowei; Schwartz, Erin S

2015-04-01

Electroencephalographic monitoring is being used with increasing frequency in critically ill children who may require frequent and sometimes urgent brain CT scans. Standard metallic disk EEG electrodes commonly produce substantial imaging artifact, and they must be removed and later reapplied when CT scans are indicated. To determine whether conductive plastic electrodes caused artifact that limited CT interpretation. We describe a retrospective cohort of 13 consecutive critically ill children who underwent 17 CT scans with conductive plastic electrodes during 1 year. CT images were evaluated by a pediatric neuroradiologist for artifact presence, type and severity. All CT scans had excellent quality images without artifact that impaired CT interpretation except for one scan in which improper wire placement resulted in artifact. Conductive plastic electrodes do not cause artifact limiting CT scan interpretation and may be used in critically ill children to permit concurrent electroencephalographic monitoring and CT imaging.

Auditory steady-state responses in cochlear implant users: Effect of modulation frequency and stimulation artifacts.

PubMed

Gransier, Robin; Deprez, Hanne; Hofmann, Michael; Moonen, Marc; van Wieringen, Astrid; Wouters, Jan

2016-05-01

Previous studies have shown that objective measures based on stimulation with low-rate pulse trains fail to predict the threshold levels of cochlear implant (CI) users for high-rate pulse trains, as used in clinical devices. Electrically evoked auditory steady-state responses (EASSRs) can be elicited by modulated high-rate pulse trains, and can potentially be used to objectively determine threshold levels of CI users. The responsiveness of the auditory pathway of profoundly hearing-impaired CI users to modulation frequencies is, however, not known. In the present study we investigated the responsiveness of the auditory pathway of CI users to a monopolar 500 pulses per second (pps) pulse train modulated between 1 and 100 Hz. EASSRs to forty-three modulation frequencies, elicited at the subject's maximum comfort level, were recorded by means of electroencephalography. Stimulation artifacts were removed by a linear interpolation between a pre- and post-stimulus sample (i.e., blanking). The phase delay across modulation frequencies was used to differentiate between the neural response and a possible residual stimulation artifact after blanking. Stimulation artifacts were longer than the inter-pulse interval of the 500pps pulse train for recording electrodes ipsilateral to the CI. As a result the stimulation artifacts could not be removed by artifact removal on the bases of linear interpolation for recording electrodes ipsilateral to the CI. However, artifact-free responses could be obtained in all subjects from recording electrodes contralateral to the CI, when subject specific reference electrodes (Cz or Fpz) were used. EASSRs to modulation frequencies within the 30-50 Hz range resulted in significant responses in all subjects. Only a small number of significant responses could be obtained, during a measurement period of 5 min, that originate from the brain stem (i.e., modulation frequencies in the 80-100 Hz range). This reduced synchronized activity of brain stem responses in long-term severely-hearing impaired CI users could be an attribute of processes associated with long-term hearing impairment and/or electrical stimulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Embodied Semiotic Activities and Their Role in the Construction of Mathematical Meaning of Motion Graphs

ERIC Educational Resources Information Center

Botzer, Galit; Yerushalmy, Michal

2008-01-01

This paper examines the relation between bodily actions, artifact-mediated activities, and semiotic processes that students experience while producing and interpreting graphs of two-dimensional motion in the plane. We designed a technology-based setting that enabled students to engage in embodied semiotic activities and experience two modes of…

Multi-Objective Memetic Search for Robust Motion and Distortion Correction in Diffusion MRI.

PubMed

Hering, Jan; Wolf, Ivo; Maier-Hein, Klaus H

2016-10-01

Effective image-based artifact correction is an essential step in the analysis of diffusion MR images. Many current approaches are based on retrospective registration, which becomes challenging in the realm of high b -values and low signal-to-noise ratio, rendering the corresponding correction schemes more and more ineffective. We propose a novel registration scheme based on memetic search optimization that allows for simultaneous exploitation of different signal intensity relationships between the images, leading to more robust registration results. We demonstrate the increased robustness and efficacy of our method on simulated as well as in vivo datasets. In contrast to the state-of-art methods, the median target registration error (TRE) stayed below the voxel size even for high b -values (3000 s ·mm -2 and higher) and low SNR conditions. We also demonstrate the increased precision in diffusion-derived quantities by evaluating Neurite Orientation Dispersion and Density Imaging (NODDI) derived measures on a in vivo dataset with severe motion artifacts. These promising results will potentially inspire further studies on metaheuristic optimization in diffusion MRI artifact correction and image registration in general.

Correction of motion artifacts and serial correlations for real-time functional near-infrared spectroscopy

PubMed Central

Barker, Jeffrey W.; Rosso, Andrea L.; Sparto, Patrick J.; Huppert, Theodore J.

2016-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is a relatively low-cost, portable, noninvasive neuroimaging technique for measuring task-evoked hemodynamic changes in the brain. Because fNIRS can be applied to a wide range of populations, such as children or infants, and under a variety of study conditions, including those involving physical movement, gait, or balance, fNIRS data are often confounded by motion artifacts. Furthermore, the high sampling rate of fNIRS leads to high temporal autocorrelation due to systemic physiology. These two factors can reduce the sensitivity and specificity of detecting hemodynamic changes. In a previous work, we showed that these factors could be mitigated by autoregressive-based prewhitening followed by the application of an iterative reweighted least squares algorithm offline. This current work extends these same ideas to real-time analysis of brain signals by modifying the linear Kalman filter, resulting in an algorithm for online estimation that is robust to systemic physiology and motion artifacts. We evaluated the performance of the proposed method via simulations of evoked hemodynamics that were added to experimental resting-state data, which provided realistic fNIRS noise. Last, we applied the method post hoc to data from a standing balance task. Overall, the new method showed good agreement with the analogous offline algorithm, in which both methods outperformed ordinary least squares methods. PMID:27226974

Closed-Loop Control of Myoelectric Prostheses With Electrotactile Feedback: Influence of Stimulation Artifact and Blanking.

PubMed

Hartmann, Cornelia; Dosen, Strahinja; Amsuess, Sebastian; Farina, Dario

2015-09-01

Electrocutaneous stimulation is a promising approach to provide sensory feedback to amputees, and thus close the loop in upper limb prosthetic systems. However, the stimulation introduces artifacts in the recorded electromyographic (EMG) signals, which may be detrimental for the control of myoelectric prostheses. In this study, artifact blanking with three data segmentation approaches was investigated as a simple method to restore the performance of pattern recognition in prosthesis control (eight motions) when EMG signals are corrupted by stimulation artifacts. The methods were tested over a range of stimulation conditions and using four feature sets, comprising both time and frequency domain features. The results demonstrated that when stimulation artifacts were present, the classification performance improved with blanking in all tested conditions. In some cases, the classification performance with blanking was at the level of the benchmark (artifact-free data). The greatest pulse duration and frequency that allowed a full performance recovery were 400 μs and 150 Hz, respectively. These results show that artifact blanking can be used as a practical solution to eliminate the negative influence of the stimulation artifact on EMG pattern classification in a broad range of conditions, thus allowing to close the loop in myoelectric prostheses using electrotactile feedback.

Striping artifact reduction in lunar orbiter mosaic images

USGS Publications Warehouse

Mlsna, P.A.; Becker, T.

2006-01-01

Photographic images of the moon from the 1960s Lunar Orbiter missions are being processed into maps for visual use. The analog nature of the images has produced numerous artifacts, the chief of which causes a vertical striping pattern in mosaic images formed from a series of filmstrips. Previous methods of stripe removal tended to introduce ringing and aliasing problems in the image data. This paper describes a recently developed alternative approach that succeeds at greatly reducing the striping artifacts while avoiding the creation of ringing and aliasing artifacts. The algorithm uses a one dimensional frequency domain step to deal with the periodic component of the striping artifact and a spatial domain step to handle the aperiodic residue. Several variations of the algorithm have been explored. Results, strengths, and remaining challenges are presented. ?? 2006 IEEE.

Variability of ICA decomposition may impact EEG signals when used to remove eyeblink artifacts

PubMed Central

PONTIFEX, MATTHEW B.; GWIZDALA, KATHRYN L.; PARKS, ANDREW C.; BILLINGER, MARTIN; BRUNNER, CLEMENS

2017-01-01

Despite the growing use of independent component analysis (ICA) algorithms for isolating and removing eyeblink-related activity from EEG data, we have limited understanding of how variability associated with ICA uncertainty may be influencing the reconstructed EEG signal after removing the eyeblink artifact components. To characterize the magnitude of this ICA uncertainty and to understand the extent to which it may influence findings within ERP and EEG investigations, ICA decompositions of EEG data from 32 college-aged young adults were repeated 30 times for three popular ICA algorithms. Following each decomposition, eyeblink components were identified and removed. The remaining components were back-projected, and the resulting clean EEG data were further used to analyze ERPs. Findings revealed that ICA uncertainty results in variation in P3 amplitude as well as variation across all EEG sampling points, but differs across ICA algorithms as a function of the spatial location of the EEG channel. This investigation highlights the potential of ICA uncertainty to introduce additional sources of variance when the data are back-projected without artifact components. Careful selection of ICA algorithms and parameters can reduce the extent to which ICA uncertainty may introduce an additional source of variance within ERP/EEG studies. PMID:28026876

Lévy meets poisson: a statistical artifact may lead to erroneous recategorization of Lévy walk as Brownian motion.

PubMed

Gautestad, Arild O

2013-03-01

The flow of GPS data on animal space is challenging old paradigms, such as the issue of the scale-free Lévy walk versus scale-specific Brownian motion. Since these movement classes often require different protocols with respect to ecological analyses, further theoretical development in this field is important. I describe central concepts such as scale-specific versus scale-free movement and the difference between mechanistic and statistical-mechanical levels of analysis. Next, I report how a specific sampling scheme may have produced much confusion: a Lévy walk may be wrongly categorized as Brownian motion if the duration of a move, or bout, is used as a proxy for step length and a move is subjectively defined. Hence, the categorization and recategorization of movement class compliance surrounding the Lévy walk controversy may have been based on a statistical artifact. This issue may be avoided by collecting relocations at a fixed rate at a temporal scale that minimizes over- and undersampling.

Types of diaphragmatic motion during hepatic angiography.

PubMed

Katsuda, T; Kuroda, C; Fujita, M

1997-01-01

To determine the types and causes of diaphragmatic motion during hepatic angiography, the authors used transarterial cut-film portography (TAP) to study movement of the diaphragm during breath-holding. Thirty-three TAP sequences were studied, and the patients' diaphragmatic motions were classified into four categories according to the distance their diaphragms moved. Results showed that the diaphragm was stationary in 33% of the TAP studies, while perpetual motion occurred in 15% of the studies, early-phase motion occurred in 12% and late-phase motion occurred in 40%. Ten sequences showed diaphragmatic motion of more than 10 mm, with eight sequences showing caudal motion and two showing cranial motion. This article discusses the cause of diaphragmatic motion during breath-holding for hepatic angiography and presents suggestions to reduce motion artifacts during the exam.

Prospective observer and software-based assessment of magnetic resonance imaging quality in head and neck cancer: Should standard positioning and immobilization be required for radiation therapy applications?

PubMed

Ding, Yao; Mohamed, Abdallah S R; Yang, Jinzhong; Colen, Rivka R; Frank, Steven J; Wang, Jihong; Wassal, Eslam Y; Wang, Wenjie; Kantor, Michael E; Balter, Peter A; Rosenthal, David I; Lai, Stephen Y; Hazle, John D; Fuller, Clifton D

2015-01-01

The purpose of this study was to investigate the potential of a head and neck magnetic resonance simulation and immobilization protocol on reducing motion-induced artifacts and improving positional variance for radiation therapy applications. Two groups (group 1, 17 patients; group 2, 14 patients) of patients with head and neck cancer were included under a prospective, institutional review board-approved protocol and signed informed consent. A 3.0-T magnetic resonance imaging (MRI) scanner was used for anatomic and dynamic contrast-enhanced acquisitions with standard diagnostic MRI setup for group 1 and radiation therapy immobilization devices for group 2 patients. The impact of magnetic resonance simulation/immobilization was evaluated qualitatively by 2 observers in terms of motion artifacts and positional reproducibility and quantitatively using 3-dimensional deformable registration to track intrascan maximum motion displacement of voxels inside 7 manually segmented regions of interest. The image quality of group 2 (29 examinations) was significantly better than that of group 1 (50 examinations) as rated by both observers in terms of motion minimization and imaging reproducibility (P < .0001). The greatest average maximum displacement was at the region of the larynx in the posterior direction for patients in group 1 (17 mm; standard deviation, 8.6 mm), whereas the smallest average maximum displacement was at the region of the posterior fossa in the superior direction for patients in group 2 (0.4 mm; standard deviation, 0.18 mm). Compared with group 1, maximum regional motion was reduced in group 2 patients in the oral cavity, floor of mouth, oropharynx, and larynx regions; however, the motion reduction reached statistical significance only in the regions of the oral cavity and floor of mouth (P < .0001). The image quality of head and neck MRI in terms of motion-related artifacts and positional reproducibility was greatly improved by use of radiation therapy immobilization devices. Consequently, immobilization with external and intraoral fixation in MRI examinations is required for radiation therapy application. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

T1 weighted brain images at 7 Tesla unbiased for Proton Density, T2* contrast and RF coil receive B1 sensitivity with simultaneous vessel visualization.

PubMed

Van de Moortele, Pierre-François; Auerbach, Edwards J; Olman, Cheryl; Yacoub, Essa; Uğurbil, Kâmil; Moeller, Steen

2009-06-01

At high magnetic field, MR images exhibit large, undesirable signal intensity variations commonly referred to as "intensity field bias". Such inhomogeneities mostly originate from heterogeneous RF coil B(1) profiles and, with no appropriate correction, are further pronounced when utilizing rooted sum of square reconstruction with receive coil arrays. These artifacts can significantly alter whole brain high resolution T(1)-weighted (T(1)w) images that are extensively utilized for clinical diagnosis, for gray/white matter segmentation as well as for coregistration with functional time series. In T(1) weighted 3D-MPRAGE sequences, it is possible to preserve a bulk amount of T(1) contrast through space by using adiabatic inversion RF pulses that are insensitive to transmit B(1) variations above a minimum threshold. However, large intensity variations persist in the images, which are significantly more difficult to address at very high field where RF coil B(1) profiles become more heterogeneous. Another characteristic of T(1)w MPRAGE sequences is their intrinsic sensitivity to Proton Density and T(2)(*) contrast, which cannot be removed with post-processing algorithms utilized to correct for receive coil sensitivity. In this paper, we demonstrate a simple technique capable of producing normalized, high resolution T(1)w 3D-MPRAGE images that are devoid of receive coil sensitivity, Proton Density and T(2)(*) contrast. These images, which are suitable for routinely obtaining whole brain tissue segmentation at 7 T, provide higher T(1) contrast specificity than standard MPRAGE acquisitions. Our results show that removing the Proton Density component can help in identifying small brain structures and that T(2)(*) induced artifacts can be removed from the images. The resulting unbiased T(1)w images can also be used to generate Maximum Intensity Projection angiograms, without additional data acquisition, that are inherently registered with T(1)w structural images. In addition, we introduce a simple technique to reduce residual signal intensity variations induced by transmit B(1) heterogeneity. Because this approach requires two 3D images, one divided with the other, head motion could create serious problems, especially at high spatial resolution. To alleviate such inter-scan motion problems, we developed a new sequence where the two contrast acquisitions are interleaved within a single scan. This interleaved approach however comes with greater risk of intra-scan motion issues because of a longer single scan time. Users can choose between these two trade offs depending on specific protocols and patient populations. We believe that the simplicity and the robustness of this double contrast based approach to address intensity field bias at high field and improve T(1) contrast specificity, together with the capability of simultaneously obtaining angiography maps, advantageously counter balance the potential drawbacks of the technique, mainly a longer acquisition time and a moderate reduction in signal to noise ratio.

T1 weighted Brain Images at 7 Tesla Unbiased for Proton Density, T2* contrast and RF Coil Receive B1 Sensitivity with Simultaneous Vessel Visualization

PubMed Central

Van de Moortele, Pierre-François; Auerbach, Edwards J.; Olman, Cheryl; Yacoub, Essa; Uğurbil, Kâmil; Moeller, Steen

2009-01-01

At high magnetic field, MR images exhibit large, undesirable signal intensity variations commonly referred to as “intensity field bias”. Such inhomogeneities mostly originate from heterogeneous RF coil B1 profiles and, with no appropriate correction, are further pronounced when utilizing rooted sum of square reconstruction with receive coil arrays. These artifacts can significantly alter whole brain high resolution T1-weighted (T1w) images that are extensively utilized for clinical diagnosis, for gray/white matter segmentation as well as for coregistration with functional time series. In T1 weighted 3D-MPRAGE sequences, it is possible to preserve a bulk amount of T1 contrast through space by using adiabatic inversion RF pulses that are insensitive to transmit B1 variations above a minimum threshold. However, large intensity variations persist in the images, which are significantly more difficult to address at very high field where RF coil B1 profiles become more heterogeneous. Another characteristic of T1w MPRAGE sequences is their intrinsic sensitivity to Proton Density and T2* contrast, which cannot be removed with post-processing algorithms utilized to correct for receive coil sensitivity. In this paper, we demonstrate a simple technique capable of producing normalized, high resolution T1w 3D-MPRAGE images that are devoid of receive coil sensitivity, Proton Density and T2* contrast. These images, which are suitable for routinely obtaining whole brain tissue segmentation at 7 Tesla, provide higher T1 contrast specificity than standard MPRAGE acquisitions. Our results show that removing the Proton Density component can help identifying small brain structures and that T2* induced artifacts can be removed from the images. The resulting unbiased T1w images can also be used to generate Maximum Intensity Projection angiograms, without additional data acquisition, that are inherently registered with T1w structural images. In addition, we introduce a simple technique to reduce residual signal intensity variations induced by Transmit B1 heterogeneity. Because this approach requires two 3D images, one divided with the other, head motion could create serious problems, especially at high spatial resolution. To alleviate such inter-scan motion problems, we developed a new sequence where the two contrast acquisitions are interleaved within a single scan. This interleaved approach however comes with greater risk of intra-scan motion issues because of a longer single scan time. Users can choose between these two trade offs depending on specific protocols and patient populations. We believe that the simplicity and the robustness of this double contrast based approach to address intensity field bias at high field and improve T1 contrast specificity, together with the capability of simultaneously obtaining angiography maps, advantageously counter balance the potential drawbacks of the technique, mainly a longer acquisition time and a moderate reduction in signal to noise ratio. PMID:19233292

Empirical Corrections for MISR Calibration Temporal Trends, Point-Spread Function, Flat-Fielding, and Ghosting

NASA Astrophysics Data System (ADS)

Limbacher, J.; Kahn, R. A.

2015-12-01

MISR aerosol optical depth retrievals are fairly robust to small radiometric calibration artifacts, due to the multi-angle observations. However, even small errors in the MISR calibration, especially structured artifacts in the imagery, have a disproportionate effect on the retrieval of aerosol properties from these data. Using MODIS, POLDER-3, AERONET, MAN, and MISR lunar images, we diagnose and correct various calibration and radiometric artifacts found in the MISR radiance (Level 1) data, using empirical image analysis. The calibration artifacts include temporal trends in MISR top-of-atmosphere reflectance at relatively stable desert sites and flat-fielding artifacts detected by comparison to MODIS over bright, low-contrast scenes. The radiometric artifacts include ghosting (as compared to MODIS, POLDER-3, and forward model results) and point-spread function mischaracterization (using the MISR lunar data and MODIS). We minimize the artifacts to the extent possible by parametrically modeling the artifacts and then removing them from the radiance (reflectance) data. Validation is performed using non-training scenes (reflectance comparison), and also by using the MISR Research Aerosol retrieval algorithm results compared to MAN and AERONET.

Reducing motion artifacts in 4D MR images using principal component analysis (PCA) combined with linear polynomial fitting model

PubMed Central

Yang, Juan; Yin, Yong; Li, Dengwang

2015-01-01

We have previously developed a retrospective 4D‐MRI technique using body area as the respiratory surrogate, but generally, the reconstructed 4D MR images suffer from severe or mild artifacts mainly caused by irregular motion during image acquisition. Those image artifacts may potentially affect the accuracy of tumor target delineation or the shape representation of surrounding nontarget tissues and organs. So the purpose of this study is to propose an approach employing principal component analysis (PCA), combined with a linear polynomial fitting model, to remodel the displacement vector fields (DVFs) obtained from deformable image registration (DIR), with the main goal of reducing the motion artifacts in 4D MR images. Seven patients with hepatocellular carcinoma (2/7) or liver metastases (5/7) in the liver, as well as a patient with non‐small cell lung cancer (NSCLC), were enrolled in an IRB‐approved prospective study. Both CT and MR simulations were performed for each patient for treatment planning. Multiple‐slice, multiple‐phase, cine‐MRI images were acquired in the axial plane for 4D‐MRI reconstruction. Single‐slice 2D cine‐MR images were acquired across the center of the tumor in axial, coronal, and sagittal planes. For a 4D MR image dataset, the DVFs in three orthogonal direction (inferior–superior (SI), anterior–posterior (AP), and medial–lateral (ML)) relative to a specific reference phase were calculated using an in‐house DIR algorithm. The DVFs were preprocessed in three temporal and spatial dimensions using a polynomial fitting model, with the goal of correcting the potential registration errors introduced by three‐dimensional DIR. Then PCA was used to decompose each fitted DVF into a linear combination of three principal motion bases whose spanned subspaces combined with their projections had been validated to be sufficient to represent the regular respiratory motion. By wrapping the reference MR image using the remodeled DVFs, ‘synthetic’ MR images with reduced motion artifacts were generated at selected phase. Tumor motion trajectories derived from cine‐MRI, 4D CT, original 4D MRI, and ‘synthetic’ 4D MRI were analyzed in the SI, AP, and ML directions, respectively. Their correlation coefficient (CC) and difference (D) in motion amplitude were calculated for comparison. Of all the patients, the means and standard deviations (SDs) of CC comparing ‘synthetic’ 4D MRI and cine‐MRI were 0.98±0.01,0.98±0,01, and 0.99±0.01 in SI, AP, and ML directions, respectively. The mean±SD Ds were 0.59±0.09 mm,0.29±0.10 mm, and 0.15±0.05 mm in SI, AP and ML directions, respectively. The means and SDs of CC comparing ‘synthetic’ 4D MRI and 4D CT were 0.96±0.01,0.95±0.01, and 0.95±0.01 in SI, AP, and ML directions, respectively. The mean±SD Ds were 0.76±0.20 mm,0.33±0.14 mm, and 0.19±0.07 mm in SI, AP, and ML directions, respectively. The means and SDs of CC comparing ‘synthetic’ 4D MRI and original 4D MRI were 0.98±0.01,0.98±0.01, and 0.97±0.01 in SI, AP, and ML directions, respectively. The mean±SD Ds were 0.58±0.10 mm,0.30±0.09 mm, and 0.17±0.04 mm in SI, AP, and ML directions, respectively. In this study we have proposed an approach employing PCA combined with a linear polynomial fitting model to capture the regular respiratory motion from a 4D MR image dataset. And its potential usefulness in reducing motion artifacts and improving image quality has been demonstrated by the preliminary results in oncological patients. PACS numbers: 87.57.cp, 87.57.nj, 87.61.‐c PMID:26103185

Quality of MR thermometry during palliative MR-guided high-intensity focused ultrasound (MR-HIFU) treatment of bone metastases.

PubMed

Lam, Mie K; Huisman, Merel; Nijenhuis, Robbert J; van den Bosch, Maurice Aaj; Viergever, Max A; Moonen, Chrit Tw; Bartels, Lambertus W

2015-01-01

Magnetic resonance (MR)-guided high-intensity focused ultrasound has emerged as a clinical option for palliative treatment of painful bone metastases, with MR thermometry (MRT) used for treatment monitoring. In this study, the general image quality of the MRT was assessed in terms of signal-to-noise ratio (SNR) and apparent temperature variation. Also, MRT artifacts were scored for their occurrence and hampering of the treatment monitoring. Analyses were performed on 224 MRT datasets retrieved from 13 treatments. The SNR was measured per voxel over time in magnitude images, in the target lesion and surrounding muscle, and was averaged per treatment. The standard deviation over time of the measured temperature per voxel in MRT images, in the muscle outside the heated region, was defined as the apparent temperature variation and was averaged per treatment. The scored MRT artifacts originated from the following sources: respiratory and non-respiratory time-varying field inhomogeneities, arterial ghosting, and patient motion by muscle contraction and by gross body movement. Distinction was made between lesion type, location, and procedural sedation and analgesic (PSA). The average SNR was highest in and around osteolytic lesions (21 in lesions, 27 in surrounding muscle, n = 4) and lowest in the upper body (9 in lesions, 16 in surrounding muscle, n = 4). The average apparent temperature variation was lowest in osteolytic lesions (1.2°C, n = 4) and the highest in the upper body (1.7°C, n = 4). Respiratory time-varying field inhomogeneity MRT artifacts occurred in 85% of the datasets and hampered treatment monitoring in 81%. Non-respiratory time-varying field inhomogeneities and arterial ghosting MRT artifacts were most frequent (94% and 95%) but occurred only locally. Patient motion artifacts were highly variable and occurred less in treatments of osteolytic lesions and using propofol and esketamine as PSA. In this study, the general image quality of MRT was observed to be higher in osteolytic lesions and lower in the upper body. Respiratory time-varying field inhomogeneity was the most prominent MRT artifact. Patient motion occurrence varied between treatments and seemed to be related to lesion type and type of PSA. Clinicians should be aware of these observed characteristics when interpreting MRT images.

Seamless image stitching by homography refinement and structure deformation using optimal seam pair detection

NASA Astrophysics Data System (ADS)

Lee, Daeho; Lee, Seohyung

2017-11-01

We propose an image stitching method that can remove ghost effects and realign the structure misalignments that occur in common image stitching methods. To reduce the artifacts caused by different parallaxes, an optimal seam pair is selected by comparing the cross correlations from multiple seams detected by variable cost weights. Along the optimal seam pair, a histogram of oriented gradients is calculated, and feature points for matching are detected. The homography is refined using the matching points, and the remaining misalignment is eliminated using the propagation of deformation vectors calculated from matching points. In multiband blending, the overlapping regions are determined from a distance between the matching points to remove overlapping artifacts. The experimental results show that the proposed method more robustly eliminates misalignments and overlapping artifacts than the existing method that uses single seam detection and gradient features.

Four-Dimensional Respiratory Motion-Resolved Whole Heart Coronary MR Angiography

PubMed Central

Piccini, Davide; Feng, Li; Bonanno, Gabriele; Coppo, Simone; Yerly, Jérôme; Lim, Ruth P.; Schwitter, Juerg; Sodickson, Daniel K.; Otazo, Ricardo; Stuber, Matthias

2016-01-01

Purpose Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach. Methods Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation. Results Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases. Conclusion XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. PMID:27052418

Modeling respiratory mechanics in the MCAT and spline-based MCAT phantoms

NASA Astrophysics Data System (ADS)

Segars, W. P.; Lalush, D. S.; Tsui, B. M. W.

2001-02-01

Respiratory motion can cause artifacts in myocardial SPECT and computed tomography (CT). The authors incorporate models of respiratory mechanics into the current 4D MCAT and into the next generation spline-based MCAT phantoms. In order to simulate respiratory motion in the current MCAT phantom, the geometric solids for the diaphragm, heart, ribs, and lungs were altered through manipulation of parameters defining them. Affine transformations were applied to the control points defining the same respiratory structures in the spline-based MCAT phantom to simulate respiratory motion. The Non-Uniform Rational B-Spline (NURBS) surfaces for the lungs and body outline were constructed in such a way as to be linked to the surrounding ribs. Expansion and contraction of the thoracic cage then coincided with expansion and contraction of the lungs and body. The changes both phantoms underwent were spline-interpolated over time to create time continuous 4D respiratory models. The authors then used the geometry-based and spline-based MCAT phantoms in an initial simulation study of the effects of respiratory motion on myocardial SPECT. The simulated reconstructed images demonstrated distinct artifacts in the inferior region of the myocardium. It is concluded that both respiratory models can be effective tools for researching effects of respiratory motion.

Peteye detection and correction

NASA Astrophysics Data System (ADS)

Yen, Jonathan; Luo, Huitao; Tretter, Daniel

2007-01-01

Redeyes are caused by the camera flash light reflecting off the retina. Peteyes refer to similar artifacts in the eyes of other mammals caused by camera flash. In this paper we present a peteye removal algorithm for detecting and correcting peteye artifacts in digital images. Peteye removal for animals is significantly more difficult than redeye removal for humans, because peteyes can be any of a variety of colors, and human face detection cannot be used to localize the animal eyes. In many animals, including dogs and cats, the retina has a special reflective layer that can cause a variety of peteye colors, depending on the animal's breed, age, or fur color, etc. This makes the peteye correction more challenging. We have developed a semi-automatic algorithm for peteye removal that can detect peteyes based on the cursor position provided by the user and correct them by neutralizing the colors with glare reduction and glint retention.

Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunter, Chad R. R. N.; Kemp, Robert A. de, E-mail: RAdeKemp@ottawaheart.ca; Klein, Ran

Purpose: Patient motion is a common problem during dynamic positron emission tomography (PET) scans for quantification of myocardial blood flow (MBF). The purpose of this study was to quantify the prevalence of body motion in a clinical setting and evaluate with realistic phantoms the effects of motion on blood flow quantification, including CT attenuation correction (CTAC) artifacts that result from PET–CT misalignment. Methods: A cohort of 236 sequential patients was analyzed for patient motion under resting and peak stress conditions by two independent observers. The presence of motion, affected time-frames, and direction of motion was recorded; discrepancy between observers wasmore » resolved by consensus review. Based on these results, patient body motion effects on MBF quantification were characterized using the digital NURBS-based cardiac-torso phantom, with characteristic time activity curves (TACs) assigned to the heart wall (myocardium) and blood regions. Simulated projection data were corrected for attenuation and reconstructed using filtered back-projection. All simulations were performed without noise added, and a single CT image was used for attenuation correction and aligned to the early- or late-frame PET images. Results: In the patient cohort, mild motion of 0.5 ± 0.1 cm occurred in 24% and moderate motion of 1.0 ± 0.3 cm occurred in 38% of patients. Motion in the superior/inferior direction accounted for 45% of all detected motion, with 30% in the superior direction. Anterior/posterior motion was predominant (29%) in the posterior direction. Left/right motion occurred in 24% of cases, with similar proportions in the left and right directions. Computer simulation studies indicated that errors in MBF can approach 500% for scans with severe patient motion (up to 2 cm). The largest errors occurred when the heart wall was shifted left toward the adjacent lung region, resulting in a severe undercorrection for attenuation of the heart wall. Simulations also indicated that the magnitude of MBF errors resulting from motion in the superior/inferior and anterior/posterior directions was similar (up to 250%). Body motion effects were more detrimental for higher resolution PET imaging (2 vs 10 mm full-width at half-maximum), and for motion occurring during the mid-to-late time-frames. Motion correction of the reconstructed dynamic image series resulted in significant reduction in MBF errors, but did not account for the residual PET–CTAC misalignment artifacts. MBF bias was reduced further using global partial-volume correction, and using dynamic alignment of the PET projection data to the CT scan for accurate attenuation correction during image reconstruction. Conclusions: Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts.« less

Reduction hybrid artifacts of EMG-EOG in electroencephalography evoked by prefrontal transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Bai, Yang; Wan, Xiaohong; Zeng, Ke; Ni, Yinmei; Qiu, Lirong; Li, Xiaoli

2016-12-01

Objective. When prefrontal-transcranial magnetic stimulation (p-TMS) performed, it may evoke hybrid artifact mixed with muscle activity and blink activity in EEG recordings. Reducing this kind of hybrid artifact challenges the traditional preprocessing methods. We aim to explore method for the p-TMS evoked hybrid artifact removal. Approach. We propose a novel method used as independent component analysis (ICA) post processing to reduce the p-TMS evoked hybrid artifact. Ensemble empirical mode decomposition (EEMD) was used to decompose signal into multi-components, then the components were separated with artifact reduced by blind source separation (BSS) method. Three standard BSS methods, ICA, independent vector analysis, and canonical correlation analysis (CCA) were tested. Main results. Synthetic results showed that EEMD-CCA outperformed others as ICA post processing step in hybrid artifacts reduction. Its superiority was clearer when signal to noise ratio (SNR) was lower. In application to real experiment, SNR can be significantly increased and the p-TMS evoked potential could be recovered from hybrid artifact contaminated signal. Our proposed method can effectively reduce the p-TMS evoked hybrid artifacts. Significance. Our proposed method may facilitate future prefrontal TMS-EEG researches.

Motion correction for functional MRI with three‐dimensional hybrid radial‐Cartesian EPI

PubMed Central

McNab, Jennifer A.; Chiew, Mark; Miller, Karla L.

2016-01-01

Purpose Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three‐dimensional (3D EPI). We present a hybrid radial‐Cartesian 3D EPI trajectory enabling motion correction in k‐space for functional MRI. Methods The EPI “blades” of the 3D hybrid radial‐Cartesian EPI sequence, called TURBINE, are rotated about the phase‐encoding axis to fill out a cylinder in 3D k‐space. Angular blades are acquired over time using a golden‐angle rotation increment, allowing reconstruction at flexible temporal resolution. The self‐navigating properties of the sequence are used to determine motion parameters from a high temporal‐resolution navigator time series. The motion is corrected in k‐space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion. Results We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal‐to‐noise ratio and fMRI activation in the presence of both severe and subtle motion. Conclusion We show the potential for hybrid radial‐Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527–540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:27604503

Diffusion Weighted Magnetic Resonance Imaging Assessment of Blood Flow in the Microvasculature of Abdominal Organs

NASA Astrophysics Data System (ADS)

Truica, Loredana Sorina

In this thesis, water diffusion in human liver and placenta is studied using diffusion weighted magnetic resonance imaging. For short, randomly oriented vascular segments, intravascular water motion is diffusion-like. For tissues with large vascular compartments the diffusion decay is bi-exponential with one component corresponding to diffusing water and the other to water in the microvasculature. This model, known as the intravoxel incoherent motion (IVIM) model, is seldom used with abdominal organs because of motion artifacts. This limitation was overcome for the experiments reported here by introducing: 1) parallel imaging, 2) navigator echo respiratory triggering (NRT), 3) a double echo diffusion sequence that inherently compensates for eddy current effects, 4) SPAIR fat suppression and 5) a superior approach to image analysis. In particular, the use of NRT allowed us to use a free breathing protocol instead of the previously required breath hold protocol. The resulting DWI images were of high quality and motion artifact free. Diffusion decays were measured over a larger portion of the decay than had previously been reported and the results are considerably better than those previously reported. For both studies, reliable measurements of the diffusion coefficient (D), pseudo-diffusion coefficient (D) and perfusion fraction (f), were obtained using a region of interest analysis as well as a pixel-by-pixel approach. To within experimental error, all patients had the same values of D (1.10 mum 2/ms +/- 0.16 mum2/ms), D* (46 mum2/ms +/- 17 mum2/ms) and f (44.0% +/- 6.9%) in liver and D (1.8 mum 2/ms +/- 0.2 mum2/ms), D* (30 mum 2/ms +/- 12 mmu2/ms), and f (40% +/- 6%) in the placenta. No dependence on gestational age was found for the placental study. Parametric maps of f and D* were consistent with blood flow patterns in both systems. The model worked well for both investigated organs even though their anatomical structures are quite different. A method for removing rectified noise bias from low intensity magnitude MR images measured with phased array coils is also presented. This algorithm has significance for diffusion decay measurements since it permits the use of low intensity data points which could, for example, allow the acquisition of high resolution parametric maps.

Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.

PubMed

Anderson, Charles W; Knight, James N; O'Connor, Tim; Kirby, Michael J; Sokolov, Artem

2006-06-01

Generalized singular-value decomposition is used to separate multichannel electroencephalogram (EEG) into components found by optimizing a signal-to-noise quotient. These components are used to filter out artifacts. Short-time principal components analysis of time-delay embedded EEG is used to represent windowed EEG data to classify EEG according to which mental task is being performed. Examples are presented of the filtering of various artifacts and results are shown of classification of EEG from five mental tasks using committees of decision trees.

Use of Multiscale Entropy to Facilitate Artifact Detection in Electroencephalographic Signals

PubMed Central

Mariani, Sara; Borges, Ana F. T.; Henriques, Teresa; Goldberger, Ary L.; Costa, Madalena D.

2016-01-01

Electroencephalographic (EEG) signals present a myriad of challenges to analysis, beginning with the detection of artifacts. Prior approaches to noise detection have utilized multiple techniques, including visual methods, independent component analysis and wavelets. However, no single method is broadly accepted, inviting alternative ways to address this problem. Here, we introduce a novel approach based on a statistical physics method, multiscale entropy (MSE) analysis, which quantifies the complexity of a signal. We postulate that noise corrupted EEG signals have lower information content, and, therefore, reduced complexity compared with their noise free counterparts. We test the new method on an open-access database of EEG signals with and without added artifacts due to electrode motion. PMID:26738116

Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals

PubMed Central

2011-01-01

Background Artifacts contained in EEG recordings hamper both, the visual interpretation by experts as well as the algorithmic processing and analysis (e.g. for Brain-Computer Interfaces (BCI) or for Mental State Monitoring). While hand-optimized selection of source components derived from Independent Component Analysis (ICA) to clean EEG data is widespread, the field could greatly profit from automated solutions based on Machine Learning methods. Existing ICA-based removal strategies depend on explicit recordings of an individual's artifacts or have not been shown to reliably identify muscle artifacts. Methods We propose an automatic method for the classification of general artifactual source components. They are estimated by TDSEP, an ICA method that takes temporal correlations into account. The linear classifier is based on an optimized feature subset determined by a Linear Programming Machine (LPM). The subset is composed of features from the frequency-, the spatial- and temporal domain. A subject independent classifier was trained on 640 TDSEP components (reaction time (RT) study, n = 12) that were hand labeled by experts as artifactual or brain sources and tested on 1080 new components of RT data of the same study. Generalization was tested on new data from two studies (auditory Event Related Potential (ERP) paradigm, n = 18; motor imagery BCI paradigm, n = 80) that used data with different channel setups and from new subjects. Results Based on six features only, the optimized linear classifier performed on level with the inter-expert disagreement (<10% Mean Squared Error (MSE)) on the RT data. On data of the auditory ERP study, the same pre-calculated classifier generalized well and achieved 15% MSE. On data of the motor imagery paradigm, we demonstrate that the discriminant information used for BCI is preserved when removing up to 60% of the most artifactual source components. Conclusions We propose a universal and efficient classifier of ICA components for the subject independent removal of artifacts from EEG data. Based on linear methods, it is applicable for different electrode placements and supports the introspection of results. Trained on expert ratings of large data sets, it is not restricted to the detection of eye- and muscle artifacts. Its performance and generalization ability is demonstrated on data of different EEG studies. PMID:21810266

Analysis of free breathing motion using artifact reduced 4D CT image data

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Werner, Rene; Frenzel, Thorsten; Lu, Wei; Low, Daniel; Handels, Heinz

2007-03-01

The mobility of lung tumors during the respiratory cycle is a source of error in radiotherapy treatment planning. Spatiotemporal CT data sets can be used for studying the motion of lung tumors and inner organs during the breathing cycle. We present methods for the analysis of respiratory motion using 4D CT data in high temporal resolution. An optical flow based reconstruction method was used to generate artifact-reduced 4D CT data sets of lung cancer patients. The reconstructed 4D CT data sets were segmented and the respiratory motion of tumors and inner organs was analyzed. A non-linear registration algorithm is used to calculate the velocity field between consecutive time frames of the 4D data. The resulting velocity field is used to analyze trajectories of landmarks and surface points. By this technique, the maximum displacement of any surface point is calculated, and regions with large respiratory motion are marked. To describe the tumor mobility the motion of the lung tumor center in three orthogonal directions is displayed. Estimated 3D appearance probabilities visualize the movement of the tumor during the respiratory cycle in one static image. Furthermore, correlations between trajectories of the skin surface and the trajectory of the tumor center are determined and skin regions are identified which are suitable for prediction of the internal tumor motion. The results of the motion analysis indicate that the described methods are suitable to gain insight into the spatiotemporal behavior of anatomical and pathological structures during the respiratory cycle.

Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis.

PubMed

Xinyang Li; Cuntai Guan; Haihong Zhang; Kai Keng Ang

2017-08-01

Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for independent component analysis based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact. To address these issues, we propose a novel discriminative ocular artifact correction approach for feature learning in EEG analysis. Without extra ocular movement measurements, the artifact is extracted from raw EEG data, which is totally automatic and requires no visual inspection of artifacts. Then, artifact correction is optimized jointly with feature extraction by maximizing oscillatory correlations between trials from the same class and minimizing them between trials from different classes. We evaluate this approach on a real-world EEG dataset comprising 68 subjects performing cognitive tasks. The results showed that the approach is capable of not only suppressing the artifact components but also improving the discriminative power of a classifier with statistical significance. We also demonstrate that the proposed method addresses the confounding issues induced by ocular movements in cognitive EEG study.

Correction of Motion Artifacts From Shuttle Mode Computed Tomography Acquisitions for Body Perfusion Imaging Applications.

PubMed

Ghosh, Payel; Chandler, Adam G; Altinmakas, Emre; Rong, John; Ng, Chaan S

2016-01-01

The aim of this study was to investigate the feasibility of shuttle-mode computed tomography (CT) technology for body perfusion applications by quantitatively assessing and correcting motion artifacts. Noncontrast shuttle-mode CT scans (10 phases, 2 nonoverlapping bed locations) were acquired from 4 patients on a GE 750HD CT scanner. Shuttling effects were quantified using Euclidean distances (between-phase and between-bed locations) of corresponding fiducial points on the shuttle and reference phase scans (prior to shuttle mode). Motion correction with nonrigid registration was evaluated using sum-of-squares differences and distances between centers of segmented volumes of interest on shuttle and references images. Fiducial point analysis showed an average shuttling motion of 0.85 ± 1.05 mm (between-bed) and 1.18 ± 1.46 mm (between-phase), respectively. The volume-of-interest analysis of the nonrigid registration results showed improved sum-of-squares differences from 2950 to 597, between-bed distance from 1.64 to 1.20 mm, and between-phase distance from 2.64 to 1.33 mm, respectively, averaged over all cases. Shuttling effects introduced during shuttle-mode CT acquisitions can be computationally corrected for body perfusion applications.

Development of motion resistant instrumentation for ambulatory near-infrared spectroscopy

PubMed Central

Zhang, Quan; Yan, Xiangguo; Strangman, Gary E.

2011-01-01

Ambulatory near-infrared spectroscopy (aNIRS) enables recording of systemic or tissue-specific hemodynamics and oxygenation during a person's normal activities. It has particular potential for the diagnosis and management of health problems with unpredictable and transient hemodynamic symptoms, or medical conditions requiring continuous, long-duration monitoring. aNIRS is also needed in conditions where regular monitoring or imaging cannot be applied, including remote environments such as during spaceflight or at high altitude. One key to the successful application of aNIRS is reducing the impact of motion artifacts in aNIRS recordings. In this paper, we describe the development of a novel prototype aNIRS monitor, called NINscan, and our efforts to reduce motion artifacts in aNIRS monitoring. Powered by 2 AA size batteries and weighting 350 g, NINscan records NIRS, ECG, respiration, and acceleration for up to 14 h at a 250 Hz sampling rate. The system's performance and resistance to motion is demonstrated by long term quantitative phantom tests, Valsalva maneuver tests, and multiparameter monitoring during parabolic flight and high altitude hiking. To the best of our knowledge, this is the first report of multiparameter aNIRS monitoring and its application in parabolic flight. PMID:21895335

Methodological aspects of EEG and body dynamics measurements during motion

PubMed Central

Reis, Pedro M. R.; Hebenstreit, Felix; Gabsteiger, Florian; von Tscharner, Vinzenz; Lochmann, Matthias

2014-01-01

EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements that are performed in response to the environment. However, there are methodological difficulties which can occur when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions on how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics, and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determinating real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks. PMID:24715858

Assessment of gunshot bullet injuries with the use of magnetic resonance imaging.

PubMed

Hess, U; Harms, J; Schneider, A; Schleef, M; Ganter, C; Hannig, C

2000-10-01

Magnetic resonance imaging (MRI) is rarely used for preoperative assessment of shotgun injuries because of concerns of displacing the possibly ferromagnetic foreign body within the surrounding tissue. A total of 56 different projectiles underwent MRI testing for ferromagnetism and imaging quality in vitro and in pig carcasses with a commercially available 1.5-MRI scan. Image quality was compared with that of computed tomographic scans. Projectiles with ferromagnetic properties can be distinguished easily from nonferromagnetic ones by pretesting the motion of an identical projectile within the MRI coil. When ferromagnetic projectiles were excluded, MRI yielded the more precise images compared with other imaging techniques. Projectile localization and associated soft tissue injuries were visualized without artifacts in all cases. When ferromagnetic foreign bodies are excluded by pretesting their properties within the MRI with a comparative projectile, MRI portends an excellent imaging procedure for assessing the extent of injury and planning the removal by surgery.

An image analysis system for near-infrared (NIR) fluorescence lymph imaging

NASA Astrophysics Data System (ADS)

Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

2011-03-01

Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

Accuracy of specimen-specific nonlinear finite element analysis for evaluation of radial diaphysis strength in cadaver material.

PubMed

Matsuura, Yusuke; Kuniyoshi, Kazuki; Suzuki, Takane; Ogawa, Yasufumi; Sukegawa, Koji; Rokkaku, Tomoyuki; Thoreson, Andrew Ryan; An, Kai-Nan; Takahashi, Kazuhisa

2015-01-01

The feasibility of a user-specific finite element model for predicting the in situ strength of the radius after implantation of bone plates for open fracture reduction was established. The effect of metal artifact in CT imaging was characterized. The results were verified against biomechanical test data. Fourteen cadaveric radii were divided into two groups: (1) intact radii for evaluating the accuracy of radial diaphysis strength predictions with finite element analysis and (2) radii with a locking plate affixed for evaluating metal artifact. All bones were imaged with CT. In the plated group, radii were first imaged with the plates affixed (for simulating digital plate removal). They were then subsequently imaged with the locking plates and screws removed (actual plate removal). Fracture strength of the radius diaphysis under axial compression was predicted with a three-dimensional, specimen-specific, nonlinear finite element analysis for both the intact and plated bones (bones with and without the plate captured in the scan). Specimens were then loaded to failure using a universal testing machine to verify the actual fracture load. In the intact group, the physical and predicted fracture loads were strongly correlated. For radii with plates affixed, the physical and predicted (simulated plate removal and actual plate removal) fracture loads were strongly correlated. This study demonstrates that our specimen-specific finite element analysis can accurately predict the strength of the radial diaphysis. The metal artifact from CT imaging was shown to produce an overestimate of strength.

SU-C-207-01: Four-Dimensional Inverse Geometry Computed Tomography: Concept and Its Validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, K; Kim, D; Kim, T

2015-06-15

Purpose: In past few years, the inverse geometry computed tomography (IGCT) system has been developed to overcome shortcomings of a conventional computed tomography (CT) system such as scatter problem induced from large detector size and cone-beam artifact. In this study, we intend to present a concept of a four-dimensional (4D) IGCT system that has positive aspects above all with temporal resolution for dynamic studies and reduction of motion artifact. Methods: Contrary to conventional CT system, projection data at a certain angle in IGCT was a group of fractionated narrow cone-beam projection data, projection group (PG), acquired from multi-source array whichmore » have extremely short time gap of sequential operation between each of sources. At this, for 4D IGCT imaging, time-related data acquisition parameters were determined by combining multi-source scanning time for collecting one PG with conventional 4D CBCT data acquisition sequence. Over a gantry rotation, acquired PGs from multi-source array were tagged time and angle for 4D image reconstruction. Acquired PGs were sorted into 10 phase and image reconstructions were independently performed at each phase. Image reconstruction algorithm based upon filtered-backprojection was used in this study. Results: The 4D IGCT had uniform image without cone-beam artifact on the contrary to 4D CBCT image. In addition, the 4D IGCT images of each phase had no significant artifact induced from motion compared with 3D CT. Conclusion: The 4D IGCT image seems to give relatively accurate dynamic information of patient anatomy based on the results were more endurable than 3D CT about motion artifact. From this, it will be useful for dynamic study and respiratory-correlated radiation therapy. This work was supported by the Industrial R&D program of MOTIE/KEIT [10048997, Development of the core technology for integrated therapy devices based on real-time MRI guided tumor tracking] and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.« less

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

A comparative quantitative analysis of the IDEAL (iterative decomposition of water and fat with echo asymmetry and least-squares estimation) and the CHESS (chemical shift selection suppression) techniques in 3.0 T L-spine MRI

NASA Astrophysics Data System (ADS)

Kim, Eng-Chan; Cho, Jae-Hwan; Kim, Min-Hye; Kim, Ki-Hong; Choi, Cheon-Woong; Seok, Jong-min; Na, Kil-Ju; Han, Man-Seok

2013-03-01

This study was conducted on 20 patients who had undergone pedicle screw fixation between March and December 2010 to quantitatively compare a conventional fat suppression technique, CHESS (chemical shift selection suppression), and a new technique, IDEAL (iterative decomposition of water and fat with echo asymmetry and least squares estimation). The general efficacy and usefulness of the IDEAL technique was also evaluated. Fat-suppressed transverse-relaxation-weighed images and longitudinal-relaxation-weighted images were obtained before and after contrast injection by using these two techniques with a 1.5T MR (magnetic resonance) scanner. The obtained images were analyzed for image distortion, susceptibility artifacts and homogenous fat removal in the target region. The results showed that the image distortion due to the susceptibility artifacts caused by implanted metal was lower in the images obtained using the IDEAL technique compared to those obtained using the CHESS technique. The results of a qualitative analysis also showed that compared to the CHESS technique, fewer susceptibility artifacts and more homogenous fat removal were found in the images obtained using the IDEAL technique in a comparative image evaluation of the axial plane images before and after contrast injection. In summary, compared to the CHESS technique, the IDEAL technique showed a lower occurrence of susceptibility artifacts caused by metal and lower image distortion. In addition, more homogenous fat removal was shown in the IDEAL technique.

TH-EF-BRA-03: Assessment of Data-Driven Respiratory Motion-Compensation Methods for 4D-CBCT Image Registration and Reconstruction Using Clinical Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riblett, MJ; Weiss, E; Hugo, GD

Purpose: To evaluate the performance of a 4D-CBCT registration and reconstruction method that corrects for respiratory motion and enhances image quality under clinically relevant conditions. Methods: Building on previous work, which tested feasibility of a motion-compensation workflow using image datasets superior to clinical acquisitions, this study assesses workflow performance under clinical conditions in terms of image quality improvement. Evaluated workflows utilized a combination of groupwise deformable image registration (DIR) and image reconstruction. Four-dimensional cone beam CT (4D-CBCT) FDK reconstructions were registered to either mean or respiratory phase reference frame images to model respiratory motion. The resulting 4D transformation was usedmore » to deform projection data during the FDK backprojection operation to create a motion-compensated reconstruction. To simulate clinically realistic conditions, superior quality projection datasets were sampled using a phase-binned striding method. Tissue interface sharpness (TIS) was defined as the slope of a sigmoid curve fit to the lung-diaphragm boundary or to the carina tissue-airway boundary when no diaphragm was discernable. Image quality improvement was assessed in 19 clinical cases by evaluating mitigation of view-aliasing artifacts, tissue interface sharpness recovery, and noise reduction. Results: For clinical datasets, evaluated average TIS recovery relative to base 4D-CBCT reconstructions was observed to be 87% using fixed-frame registration alone; 87% using fixed-frame with motion-compensated reconstruction; 92% using mean-frame registration alone; and 90% using mean-frame with motion-compensated reconstruction. Soft tissue noise was reduced on average by 43% and 44% for the fixed-frame registration and registration with motion-compensation methods, respectively, and by 40% and 42% for the corresponding mean-frame methods. Considerable reductions in view aliasing artifacts were observed for each method. Conclusion: Data-driven groupwise registration and motion-compensated reconstruction have the potential to improve the quality of 4D-CBCT images acquired under clinical conditions. For clinical image datasets, the addition of motion compensation after groupwise registration visibly reduced artifact impact. This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA166119. Hugo and Weiss hold a research agreement with Philips Healthcare and license agreement with Varian Medical Systems. Weiss receives royalties from UpToDate. Christensen receives funds from Roger Koch to support research.« less

Motion-insensitive carotid intraplaque hemorrhage imaging using 3D inversion recovery preparation stack of stars (IR-prep SOS) technique.

PubMed

Kim, Seong-Eun; Roberts, John A; Eisenmenger, Laura B; Aldred, Booth W; Jamil, Osama; Bolster, Bradley D; Bi, Xiaoming; Parker, Dennis L; Treiman, Gerald S; McNally, J Scott

2017-02-01

Carotid artery imaging is important in the clinical management of patients at risk for stroke. Carotid intraplaque hemorrhage (IPH) presents an important diagnostic challenge. 3D magnetization prepared rapid acquisition gradient echo (MPRAGE) has been shown to accurately image carotid IPH; however, this sequence can be limited due to motion- and flow-related artifact. The purpose of this work was to develop and evaluate an improved 3D carotid MPRAGE sequence for IPH detection. We hypothesized that a radial-based k-space trajectory sequence such as "Stack of Stars" (SOS) incorporated with inversion recovery preparation would offer reduced motion sensitivity and more robust flow suppression by oversampling of central k-space. A total of 31 patients with carotid disease (62 carotid arteries) were imaged at 3T magnetic resonance imaging (MRI) with 3D IR-prep Cartesian and SOS sequences. Image quality was determined between SOS and Cartesian MPRAGE in 62 carotid arteries using t-tests and multivariable linear regression. Kappa analysis was used to determine interrater reliability. In all, 25 among 62 carotid plaques had carotid IPH by consensus from the reviewers on SOS compared to 24 on Cartesian sequence. Image quality was significantly higher with SOS compared to Cartesian (mean 3.74 vs. 3.11, P < 0.001). SOS acquisition yielded sharper image features with less motion (19.4% vs. 45.2%, P < 0.002) and flow artifact (27.4% vs. 41.9%, P < 0.089). There was also excellent interrater reliability with SOS (kappa = 0.89), higher than that of Cartesian (kappa = 0.84). By minimizing flow and motion artifacts and retaining high interrater reliability, the SOS MPRAGE has important advantages over Cartesian MPRAGE in carotid IPH detection. 1 J. Magn. Reson. Imaging 2017;45:410-417. © 2016 International Society for Magnetic Resonance in Medicine.

Quality assurance in mammography: artifact analysis.

PubMed

Hogge, J P; Palmer, C H; Muller, C C; Little, S T; Smith, D C; Fatouros, P P; de Paredes, E S

1999-01-01

Evaluation of mammograms for artifacts is essential for mammographic quality assurance. A variety of mammographic artifacts (i.e., variations in mammographic density not caused by true attenuation differences) can occur and can create pseudolesions or mask true abnormalities. Many artifacts are readily identified, whereas others present a true diagnostic challenge. Factors that create artifacts may be related to the processor (eg, static, dirt or excessive developer buildup on the rollers, excessive roller pressure, damp film, scrapes and scratches, incomplete fixing, power failure, contaminated developer), the technologist (eg, improper film handling and loading, improper use of the mammography unit and related equipment, positioning and darkroom errors), the mammography unit (eg, failure of the collimation mirror to rotate, grid inhomogeneity, failure of the reciprocating grid to move, material in the tube housing, compression failure, improper alignment of the compression paddle with the Bucky tray, defective compression paddle), or the patient (e.g., motion, superimposed objects or substances [jewelry, body parts, clothing, hair, implanted medical devices, foreign bodies, substances on the skin]). Familiarity with the broad range of artifacts and the measures required to eliminate them is vital. Careful attention to darkroom cleanliness, care in film handling, regularly scheduled processor maintenance and chemical replenishment, daily quality assurance activities, and careful attention to detail during patient positioning and mammography can reduce or eliminate most mammographic artifacts.

Multishot cartesian turbo spin-echo diffusion imaging using iterative POCSMUSE Reconstruction.

PubMed

Zhang, Zhe; Zhang, Bing; Li, Ming; Liang, Xue; Chen, Xiaodong; Liu, Renyuan; Zhang, Xin; Guo, Hua

2017-07-01

To report a diffusion imaging technique insensitive to off-resonance artifacts and motion-induced ghost artifacts using multishot Cartesian turbo spin-echo (TSE) acquisition and iterative POCS-based reconstruction of multiplexed sensitivity encoded magnetic resonance imaging (MRI) (POCSMUSE) for phase correction. Phase insensitive diffusion preparation was used to deal with the violation of the Carr-Purcell-Meiboom-Gill (CPMG) conditions of TSE diffusion-weighted imaging (DWI), followed by a multishot Cartesian TSE readout for data acquisition. An iterative diffusion phase correction method, iterative POCSMUSE, was developed and implemented to eliminate the ghost artifacts in multishot TSE DWI. The in vivo human brain diffusion images (from one healthy volunteer and 10 patients) using multishot Cartesian TSE were acquired at 3T and reconstructed using iterative POCSMUSE, and compared with single-shot and multishot echo-planar imaging (EPI) results. These images were evaluated by two radiologists using visual scores (considering both image quality and distortion levels) from 1 to 5. The proposed iterative POCSMUSE reconstruction was able to correct the ghost artifacts in multishot DWI. The ghost-to-signal ratio of TSE DWI using iterative POCSMUSE (0.0174 ± 0.0024) was significantly (P < 0.0005) smaller than using POCSMUSE (0.0253 ± 0.0040). The image scores of multishot TSE DWI were significantly higher than single-shot (P = 0.004 and 0.006 from two reviewers) and multishot (P = 0.008 and 0.004 from two reviewers) EPI-based methods. The proposed multishot Cartesian TSE DWI using iterative POCSMUSE reconstruction can provide high-quality diffusion images insensitive to motion-induced ghost artifacts and off-resonance related artifacts such as chemical shifts and susceptibility-induced image distortions. 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:167-174. © 2016 International Society for Magnetic Resonance in Medicine.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.

PubMed

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features

NASA Astrophysics Data System (ADS)

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Objective. Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. Approach. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. Main results. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Significance. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.« less

Correction of Non-Linear Propagation Artifact in Contrast-Enhanced Ultrasound Imaging of Carotid Arteries: Methods and in Vitro Evaluation.

PubMed

Yildiz, Yesna O; Eckersley, Robert J; Senior, Roxy; Lim, Adrian K P; Cosgrove, David; Tang, Meng-Xing

2015-07-01

Non-linear propagation of ultrasound creates artifacts in contrast-enhanced ultrasound images that significantly affect both qualitative and quantitative assessments of tissue perfusion. This article describes the development and evaluation of a new algorithm to correct for this artifact. The correction is a post-processing method that estimates and removes non-linear artifact in the contrast-specific image using the simultaneously acquired B-mode image data. The method is evaluated on carotid artery flow phantoms with large and small vessels containing microbubbles of various concentrations at different acoustic pressures. The algorithm significantly reduces non-linear artifacts while maintaining the contrast signal from bubbles to increase the contrast-to-tissue ratio by up to 11 dB. Contrast signal from a small vessel 600 μm in diameter buried in tissue artifacts before correction was recovered after the correction. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Voting strategy for artifact reduction in digital breast tomosynthesis.

PubMed

Wu, Tao; Moore, Richard H; Kopans, Daniel B

2006-07-01

Artifacts are observed in digital breast tomosynthesis (DBT) reconstructions due to the small number of projections and the narrow angular range that are typically employed in tomosynthesis imaging. In this work, we investigate the reconstruction artifacts that are caused by high-attenuation features in breast and develop several artifact reduction methods based on a "voting strategy." The voting strategy identifies the projection(s) that would introduce artifacts to a voxel and rejects the projection(s) when reconstructing the voxel. Four approaches to the voting strategy were compared, including projection segmentation, maximum contribution deduction, one-step classification, and iterative classification. The projection segmentation method, based on segmentation of high-attenuation features from the projections, effectively reduces artifacts caused by metal and large calcifications that can be reliably detected and segmented from projections. The other three methods are based on the observation that contributions from artifact-inducing projections have higher value than those from normal projections. These methods attempt to identify the projection(s) that would cause artifacts by comparing contributions from different projections. Among the three methods, the iterative classification method provides the best artifact reduction; however, it can generate many false positive classifications that degrade the image quality. The maximum contribution deduction method and one-step classification method both reduce artifacts well from small calcifications, although the performance of artifact reduction is slightly better with the one-step classification. The combination of one-step classification and projection segmentation removes artifacts from both large and small calcifications.

Effect of ISDN bandwidth on image quality for telemedicine transmission of obstetric ultrasonography.

PubMed

Malone, F D; Athanassiou, A; Nores, J; D'Alton, M E

1998-01-01

To evaluate objectively the effect of different bandwidths on the ability to interpret obstetric ultrasound scans transmitted live over a commercial telephone network. An integrated services digital network (ISDN) was established from three satellite offices to our central prenatal diagnostic center. In the first half of the study, the network was based on four ISDN channels transmitting at a bandwidth of 256 kbits per second (kbps), while in the second half of the study, this was increased to six ISDN channels transmitting at 384 kbps. A physician trained in obstetric ultrasonography provided an interpretation of fetal anatomy using a live, real-time telemedicine link. A scoring system consisting of 33 anatomic items was used to evaluate image quality objectively. The number of transmissions complicated by motion artifact was also recorded. One hundred patients had a fetal anatomy survey performed using the 256 kbps system, and these interpretations were compared with those from another group of 100 patients who were examined using the 384 kbps system. Although the visibility of the 33 anatomic items was similar using the two systems, significantly more examinations at 256 kbps were complicated by motion artifact (12% vs. 3%; P = 0.02). Remote sonographic viewing of fetal anatomy was adequate using both 256 and 384 kbps systems, although motion artifact was significantly more likely to occur using the slower system. This problem may affect the ability of the lower-bandwidth system to allow optimal detection when fetal anomalies are present.

Accurate Heart Rate Monitoring During Physical Exercises Using PPG.

PubMed

Temko, Andriy

2017-09-01

The challenging task of heart rate (HR) estimation from the photoplethysmographic (PPG) signal, during intensive physical exercises, is tackled in this paper. The study presents a detailed analysis of a novel algorithm (WFPV) that exploits a Wiener filter to attenuate the motion artifacts, a phase vocoder to refine the HR estimate and user-adaptive post-processing to track the subject physiology. Additionally, an offline version of the HR estimation algorithm that uses Viterbi decoding is designed for scenarios that do not require online HR monitoring (WFPV+VD). The performance of the HR estimation systems is rigorously compared with existing algorithms on the publically available database of 23 PPG recordings. On the whole dataset of 23 PPG recordings, the algorithms result in average absolute errors of 1.97 and 1.37 BPM in the online and offline modes, respectively. On the test dataset of 10 PPG recordings which were most corrupted with motion artifacts, WFPV has an error of 2.95 BPM on its own and 2.32 BPM in an ensemble with two existing algorithms. The error rate is significantly reduced when compared with the state-of-the art PPG-based HR estimation methods. The proposed system is shown to be accurate in the presence of strong motion artifacts and in contrast to existing alternatives has very few free parameters to tune. The algorithm has a low computational cost and can be used for fitness tracking and health monitoring in wearable devices. The MATLAB implementation of the algorithm is provided online.

General rigid motion correction for computed tomography imaging based on locally linear embedding

NASA Astrophysics Data System (ADS)

Chen, Mianyi; He, Peng; Feng, Peng; Liu, Baodong; Yang, Qingsong; Wei, Biao; Wang, Ge

2018-02-01

The patient motion can damage the quality of computed tomography images, which are typically acquired in cone-beam geometry. The rigid patient motion is characterized by six geometric parameters and are more challenging to correct than in fan-beam geometry. We extend our previous rigid patient motion correction method based on the principle of locally linear embedding (LLE) from fan-beam to cone-beam geometry and accelerate the computational procedure with the graphics processing unit (GPU)-based all scale tomographic reconstruction Antwerp toolbox. The major merit of our method is that we need neither fiducial markers nor motion-tracking devices. The numerical and experimental studies show that the LLE-based patient motion correction is capable of calibrating the six parameters of the patient motion simultaneously, reducing patient motion artifacts significantly.

Combined Electrocardiography- and Respiratory-Triggered CT of the Lung to Reduce Respiratory Misregistration Artifacts between Imaging Slabs in Free-Breathing Children: Initial Experience.

PubMed

Goo, Hyun Woo; Allmendinger, Thomas

2017-01-01

Cardiac and respiratory motion artifacts degrade the image quality of lung CT in free-breathing children. The aim of this study was to evaluate the effect of combined electrocardiography (ECG) and respiratory triggering on respiratory misregistration artifacts on lung CT in free-breathing children. In total, 15 children (median age 19 months, range 6 months-8 years; 7 boys), who underwent free-breathing ECG-triggered lung CT with and without respiratory-triggering were included. A pressure-sensing belt of a respiratory gating system was used to obtain the respiratory signal. The degree of respiratory misregistration artifacts between imaging slabs was graded on a 4-point scale (1, excellent image quality) on coronal and sagittal images and compared between ECG-triggered lung CT studies with and without respiratory triggering. A p value < 0.05 was considered significant. Lung CT with combined ECG and respiratory triggering showed significantly less respiratory misregistration artifacts than lung CT with ECG triggering only (1.1 ± 0.4 vs. 2.2 ± 1.0, p = 0.003). Additional respiratory-triggering reduces respiratory misregistration artifacts on ECG-triggered lung CT in free-breathing children.

Image-derived input function in PET brain studies: blood-based methods are resistant to motion artifacts.

PubMed

Zanotti-Fregonara, Paolo; Liow, Jeih-San; Comtat, Claude; Zoghbi, Sami S; Zhang, Yi; Pike, Victor W; Fujita, Masahiro; Innis, Robert B

2012-09-01

Image-derived input function (IDIF) from carotid arteries is an elegant alternative to full arterial blood sampling for brain PET studies. However, a recent study using blood-free IDIFs found that this method is particularly vulnerable to patient motion. The present study used both simulated and clinical [11C](R)-rolipram data to assess the robustness of a blood-based IDIF method (a method that is ultimately normalized with blood samples) with regard to motion artifacts. The impact of motion on the accuracy of IDIF was first assessed with an analytical simulation of a high-resolution research tomograph using a numerical phantom of the human brain, equipped with internal carotids. Different degrees of translational (from 1 to 20 mm) and rotational (from 1 to 15°) motions were tested. The impact of motion was then tested on the high-resolution research tomograph dynamic scans of three healthy volunteers, reconstructed with and without an online motion correction system. IDIFs and Logan-distribution volume (VT) values derived from simulated and clinical scans with motion were compared with those obtained from the scans with motion correction. In the phantom scans, the difference in the area under the curve (AUC) for the carotid time-activity curves was up to 19% for rotations and up to 66% for translations compared with the motionless simulation. However, for the final IDIFs, which were fitted to blood samples, the AUC difference was 11% for rotations and 8% for translations. Logan-VT errors were always less than 10%, except for the maximum translation of 20 mm, in which the error was 18%. Errors in the clinical scans without motion correction appeared to be minor, with differences in AUC and Logan-VT always less than 10% compared with scans with motion correction. When a blood-based IDIF method is used for neurological PET studies, the motion of the patient affects IDIF estimation and kinetic modeling only minimally.

Removal of muscle artifact from EEG data: comparison between stochastic (ICA and CCA) and deterministic (EMD and wavelet-based) approaches

NASA Astrophysics Data System (ADS)

Safieddine, Doha; Kachenoura, Amar; Albera, Laurent; Birot, Gwénaël; Karfoul, Ahmad; Pasnicu, Anca; Biraben, Arnaud; Wendling, Fabrice; Senhadji, Lotfi; Merlet, Isabelle

2012-12-01

Electroencephalographic (EEG) recordings are often contaminated with muscle artifacts. This disturbing myogenic activity not only strongly affects the visual analysis of EEG, but also most surely impairs the results of EEG signal processing tools such as source localization. This article focuses on the particular context of the contamination epileptic signals (interictal spikes) by muscle artifact, as EEG is a key diagnosis tool for this pathology. In this context, our aim was to compare the ability of two stochastic approaches of blind source separation, namely independent component analysis (ICA) and canonical correlation analysis (CCA), and of two deterministic approaches namely empirical mode decomposition (EMD) and wavelet transform (WT) to remove muscle artifacts from EEG signals. To quantitatively compare the performance of these four algorithms, epileptic spike-like EEG signals were simulated from two different source configurations and artificially contaminated with different levels of real EEG-recorded myogenic activity. The efficiency of CCA, ICA, EMD, and WT to correct the muscular artifact was evaluated both by calculating the normalized mean-squared error between denoised and original signals and by comparing the results of source localization obtained from artifact-free as well as noisy signals, before and after artifact correction. Tests on real data recorded in an epileptic patient are also presented. The results obtained in the context of simulations and real data show that EMD outperformed the three other algorithms for the denoising of data highly contaminated by muscular activity. For less noisy data, and when spikes arose from a single cortical source, the myogenic artifact was best corrected with CCA and ICA. Otherwise when spikes originated from two distinct sources, either EMD or ICA offered the most reliable denoising result for highly noisy data, while WT offered the better denoising result for less noisy data. These results suggest that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals. Eventually, some insights into the numerical complexity of these four algorithms are given.

Dual-wavelength polarimetric glucose sensing in the presence of birefringence and motion artifact using anterior chamber of the eye phantoms

PubMed Central

Pirnstill, Casey W.; Coté, Gerard L.

2013-01-01

Abstract. Noninvasive glucose monitoring is being investigated as a tool for effectively managing diabetes mellitus. Optical polarimetry has emerged as one such method, which can potentially be used to ascertain blood glucose levels by measuring the aqueous humor glucose levels in the anterior chamber of the eye. The key limitation for realizing this technique is the presence of sample noise due to corneal birefringence, which in the presence of motion artifact can confound the glucose signature in the aqueous humor of the eye. We present the development and characterization of a real-time, closed-loop, dual-wavelength polarimetric system for glucose monitoring using both a custom-built plastic eye phantom (in vitro) and isolated rabbit corneas (ex vivo) mounted in an artificial anterior chamber. The results show that the system can account for these noise sources and can monitor physiologic glucose levels accurately for a limited range of motion-induced birefringence. Using the dual-wavelength system in vitro and ex vivo, standard errors were 14.5  mg/dL and 22.4  mg/dL, respectively, in the presence of birefringence with motion. The results indicate that although dual-wavelength polarimetry has a limited range of compensation for motion-induced birefringence, when aligned correctly, it can minimize the effect of time-varying corneal birefringence for a range of motion larger than what has been reported in vivo. PMID:23299516

Four-dimensional respiratory motion-resolved whole heart coronary MR angiography.

PubMed

Piccini, Davide; Feng, Li; Bonanno, Gabriele; Coppo, Simone; Yerly, Jérôme; Lim, Ruth P; Schwitter, Juerg; Sodickson, Daniel K; Otazo, Ricardo; Stuber, Matthias

2017-04-01

Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach. Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation. Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases. XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. Magn Reson Med 77:1473-1484, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging.

PubMed

Holdsworth, Samantha J; Aksoy, Murat; Newbould, Rexford D; Yeom, Kristen; Van, Anh T; Ooi, Melvyn B; Barnes, Patrick D; Bammer, Roland; Skare, Stefan

2012-10-01

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion. The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation. This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data. Copyright © 2012 Wiley Periodicals, Inc.

Metallic artifact mitigation and organ-constrained tissue assignment for Monte Carlo calculations of permanent implant lung brachytherapy.

PubMed

Sutherland, J G H; Miksys, N; Furutani, K M; Thomson, R M

2014-01-01

To investigate methods of generating accurate patient-specific computational phantoms for the Monte Carlo calculation of lung brachytherapy patient dose distributions. Four metallic artifact mitigation methods are applied to six lung brachytherapy patient computed tomography (CT) images: simple threshold replacement (STR) identifies high CT values in the vicinity of the seeds and replaces them with estimated true values; fan beam virtual sinogram replaces artifact-affected values in a virtual sinogram and performs a filtered back-projection to generate a corrected image; 3D median filter replaces voxel values that differ from the median value in a region of interest surrounding the voxel and then applies a second filter to reduce noise; and a combination of fan beam virtual sinogram and STR. Computational phantoms are generated from artifact-corrected and uncorrected images using several tissue assignment schemes: both lung-contour constrained and unconstrained global schemes are considered. Voxel mass densities are assigned based on voxel CT number or using the nominal tissue mass densities. Dose distributions are calculated using the EGSnrc user-code BrachyDose for (125)I, (103)Pd, and (131)Cs seeds and are compared directly as well as through dose volume histograms and dose metrics for target volumes surrounding surgical sutures. Metallic artifact mitigation techniques vary in ability to reduce artifacts while preserving tissue detail. Notably, images corrected with the fan beam virtual sinogram have reduced artifacts but residual artifacts near sources remain requiring additional use of STR; the 3D median filter removes artifacts but simultaneously removes detail in lung and bone. Doses vary considerably between computational phantoms with the largest differences arising from artifact-affected voxels assigned to bone in the vicinity of the seeds. Consequently, when metallic artifact reduction and constrained tissue assignment within lung contours are employed in generated phantoms, this erroneous assignment is reduced, generally resulting in higher doses. Lung-constrained tissue assignment also results in increased doses in regions of interest due to a reduction in the erroneous assignment of adipose to voxels within lung contours. Differences in dose metrics calculated for different computational phantoms are sensitive to radionuclide photon spectra with the largest differences for (103)Pd seeds and smallest but still considerable differences for (131)Cs seeds. Despite producing differences in CT images, dose metrics calculated using the STR, fan beam + STR, and 3D median filter techniques produce similar dose metrics. Results suggest that the accuracy of dose distributions for permanent implant lung brachytherapy is improved by applying lung-constrained tissue assignment schemes to metallic artifact corrected images.

Phase processing for quantitative susceptibility mapping of regions with large susceptibility and lack of signal.

PubMed

Fortier, Véronique; Levesque, Ives R

2018-06-01

Phase processing impacts the accuracy of quantitative susceptibility mapping (QSM). Techniques for phase unwrapping and background removal have been proposed and demonstrated mostly in brain. In this work, phase processing was evaluated in the context of large susceptibility variations (Δχ) and negligible signal, in particular for susceptibility estimation using the iterative phase replacement (IPR) algorithm. Continuous Laplacian, region-growing, and quality-guided unwrapping were evaluated. For background removal, Laplacian boundary value (LBV), projection onto dipole fields (PDF), sophisticated harmonic artifact reduction for phase data (SHARP), variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP), regularization enabled sophisticated harmonic artifact reduction for phase data (RESHARP), and 3D quadratic polynomial field removal were studied. Each algorithm was quantitatively evaluated in simulation and qualitatively in vivo. Additionally, IPR-QSM maps were produced to evaluate the impact of phase processing on the susceptibility in the context of large Δχ with negligible signal. Quality-guided unwrapping was the most accurate technique, whereas continuous Laplacian performed poorly in this context. All background removal algorithms tested resulted in important phase inaccuracies, suggesting that techniques used for brain do not translate well to situations where large Δχ and no or low signal are expected. LBV produced the smallest errors, followed closely by PDF. Results suggest that quality-guided unwrapping should be preferred, with PDF or LBV for background removal, for QSM in regions with large Δχ and negligible signal. This reduces the susceptibility inaccuracy introduced by phase processing. Accurate background removal remains an open question. Magn Reson Med 79:3103-3113, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Hui, E-mail: corinna@seu.edu.cn; Key Laboratory of Computer Network and Information Integration; Centre de Recherche en Information Biomédicale sino-français, Laboratoire International Associé, Inserm, Université de Rennes 1, Rennes 35000

2015-04-15

Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods: The method is as follows. The input image is first recursively decomposed into several smaller subimagesmore » using a multiscale 2D discrete wavelet transform. The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these subimages using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected subimages to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform. Results: The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1D Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions: The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time.« less

SU-F-J-158: Respiratory Motion Resolved, Self-Gated 4D-MRI Using Rotating Cartesian K-Space Sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, F; Zhou, Z; Yang, Y

Purpose: Dynamic MRI has been used to quantify respiratory motion of abdominal organs in radiation treatment planning. Many existing 4D-MRI methods based on 2D acquisitions suffer from limited slice resolution and additional stitching artifacts when evaluated in 3D{sup 1}. To address these issues, we developed a 4D-MRI (3D dynamic) technique with true 3D k-space encoding and respiratory motion self-gating. Methods: The 3D k-space was acquired using a Rotating Cartesian K-space (ROCK) pattern, where the Cartesian grid was reordered in a quasi-spiral fashion with each spiral arm rotated using golden angle{sup 2}. Each quasi-spiral arm started with the k-space center-line, whichmore » were used as self-gating{sup 3} signal for respiratory motion estimation. The acquired k-space data was then binned into 8 respiratory phases and the golden angle ensures a near-uniform k-space sampling in each phase. Finally, dynamic 3D images were reconstructed using the ESPIRiT technique{sup 4}. 4D-MRI was performed on 6 healthy volunteers, using the following parameters (bSSFP, Fat-Sat, TE/TR=2ms/4ms, matrix size=500×350×120, resolution=1×1×1.2mm, TA=5min, 8 respiratory phases). Supplemental 2D real-time images were acquired in 9 different planes. Dynamic locations of the diaphragm dome and left kidney were measured from both 4D and 2D images. The same protocol was also performed on a MRI-compatible motion phantom where the motion was programmed with different amplitude (10–30mm) and frequency (3–10/min). Results: High resolution 4D-MRI were obtained successfully in 5 minutes. Quantitative motion measurements from 4D-MRI agree with the ones from 2D CINE (<5% error). The 4D images are free of the stitching artifacts and their near-isotropic resolution facilitates 3D visualization and segmentation of abdominal organs such as the liver, kidney and pancreas. Conclusion: Our preliminary studies demonstrated a novel ROCK 4D-MRI technique with true 3D k-space encoding and respiratory motion self-gating. The technique leads to high-resolution and artifacts-free 4D images for improved abdominal organ motion studies. K.S acknowledges funding support from NIH R01CA188300.« less

Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorndyke, Brian; Schreibmann, Eduard; Koong, Albert

Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined 'retrospective stacking' (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to {sup 18}FDG-PET images of a pancreatic and a liver patient. Comparisons weremore » made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.« less

Comparison of Foam-Based and Spring-Loaded Dry EEG Electrodes with Wet Electrodes in Resting and Moving Conditions*

PubMed Central

Yeung, Arnold; Garudadri, Harinath; Van Toen, Carolyn; Mercier, Patrick; Balkan, Ozgur; Makeig, Scott; Virji-Babul, Naznin

2018-01-01

The introduction of dry electrodes for EEG measurements has opened up possibilities of recording EEG outside of standard clinical environments by reducing required preparation and maintenance. However, the signal quality of dry electrodes in comparison with wet electrodes has not yet been evaluated under activities of daily life (ADL) or high motion tasks. In this study, we compared the performances of foam-based and spring-loaded dry electrodes with wet electrodes under three different task conditions: resting state, walking, and cycling. Our analysis showed signals obtained by the 2 types of dry electrodes and obtained by wet electrodes displayed high correlation for all conditions, while being prone to similar environmental and electrode-based artifacts. Overall, our results suggest that dry electrodes have a similar signal quality in comparison to wet electrodes and may be more practical for use in mobile and real-time motion applications due to their convenience. In addition, we conclude that as with wet electrodes, post-processing can mitigate motion artifacts in ambulatory EEG acquisition. PMID:26737936

Fast automatic correction of motion artifacts in shoulder MRI

NASA Astrophysics Data System (ADS)

Manduca, Armando; McGee, Kiaran P.; Welch, Edward B.; Felmlee, Joel P.; Ehman, Richard L.

2001-07-01

The ability to correct certain types of MR images for motion artifacts from the raw data alone by iterative optimization of an image quality measure has recently been demonstrated. In the first study on a large data set of clinical images, we showed that such an autocorrection technique significantly improved the quality of clinical rotator cuff images, and performed almost as well as navigator echo correction while never degrading an image. One major criticism of such techniques is that they are computationally intensive, and reports of the processing time required have ranged form a few minutes to tens of minutes per slice. In this paper we describe a variety of improvements to our algorithm as well as approaches to correct sets of adjacent slices efficiently. The resulting algorithm is able to correct 256x256x20 clinical shoulder data sets for motion at an effective rate of 1 second/image on a standard commercial workstation. Future improvements in processor speeds and/or the use of specialized hardware will translate directly to corresponding reductions in this calculation time.

A programmable display layer for virtual reality system architectures.

PubMed

Smit, Ferdi Alexander; van Liere, Robert; Froehlich, Bernd

2010-01-01

Display systems typically operate at a minimum rate of 60 Hz. However, existing VR-architectures generally produce application updates at a lower rate. Consequently, the display is not updated by the application every display frame. This causes a number of undesirable perceptual artifacts. We describe an architecture that provides a programmable display layer (PDL) in order to generate updated display frames. This replaces the default display behavior of repeating application frames until an update is available. We will show three benefits of the architecture typical to VR. First, smooth motion is provided by generating intermediate display frames by per-pixel depth-image warping using 3D motion fields. Smooth motion eliminates various perceptual artifacts due to judder. Second, we implement fine-grained latency reduction at the display frame level using a synchronized prediction of simulation objects and the viewpoint. This improves the average quality and consistency of latency reduction. Third, a crosstalk reduction algorithm for consecutive display frames is implemented, which improves the quality of stereoscopic images. To evaluate the architecture, we compare image quality and latency to that of a classic level-of-detail approach.

Digital Correction of Motion Artifacts in Microscopy Image Sequences Collected from Living Animals Using Rigid and Non-Rigid Registration

PubMed Central

Lorenz, Kevin S.; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2013-01-01

Digital image analysis is a fundamental component of quantitative microscopy. However, intravital microscopy presents many challenges for digital image analysis. In general, microscopy volumes are inherently anisotropic, suffer from decreasing contrast with tissue depth, lack object edge detail, and characteristically have low signal levels. Intravital microscopy introduces the additional problem of motion artifacts, resulting from respiratory motion and heartbeat from specimens imaged in vivo. This paper describes an image registration technique for use with sequences of intravital microscopy images collected in time-series or in 3D volumes. Our registration method involves both rigid and non-rigid components. The rigid registration component corrects global image translations, while the non-rigid component manipulates a uniform grid of control points defined by B-splines. Each control point is optimized by minimizing a cost function consisting of two parts: a term to define image similarity, and a term to ensure deformation grid smoothness. Experimental results indicate that this approach is promising based on the analysis of several image volumes collected from the kidney, lung, and salivary gland of living rodents. PMID:22092443

Human-Robot Collaboration Dynamic Impact Testing and Calibration Instrument for Disposable Robot Safety Artifacts

PubMed Central

Dagalakis, Nicholas G.; Yoo, Jae Myung; Oeste, Thomas

2017-01-01

The Dynamic Impact Testing and Calibration Instrument (DITCI) is a simple instrument with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts. These artifacts may be used to measure the severity of injuries caused in the case of a robot impact with a human. In this paper we describe the DITCI adjustable impact and flexible foundation mechanism, which allows the selection of a variety of impact force levels and foundation stiffness. The instrument can accommodate arrays of a variety of sensors and impact tools, simulating both real manufacturing tools and the testing requirements of standards setting organizations. A computer data acquisition system may collect a variety of impact motion, force, and torque data, which are used to develop a variety of mathematical model representations of the artifacts. Finally, we describe the fabrication and testing of human abdomen soft tissue artifacts, used to display the magnitude of impact tissue deformation. Impact tests were performed at various maximum impact force and average pressure levels. PMID:28579658

Human-Robot Collaboration Dynamic Impact Testing and Calibration Instrument for Disposable Robot Safety Artifacts.

PubMed

Dagalakis, Nicholas G; Yoo, Jae Myung; Oeste, Thomas

2016-01-01

The Dynamic Impact Testing and Calibration Instrument (DITCI) is a simple instrument with a significant data collection and analysis capability that is used for the testing and calibration of biosimulant human tissue artifacts. These artifacts may be used to measure the severity of injuries caused in the case of a robot impact with a human. In this paper we describe the DITCI adjustable impact and flexible foundation mechanism, which allows the selection of a variety of impact force levels and foundation stiffness. The instrument can accommodate arrays of a variety of sensors and impact tools, simulating both real manufacturing tools and the testing requirements of standards setting organizations. A computer data acquisition system may collect a variety of impact motion, force, and torque data, which are used to develop a variety of mathematical model representations of the artifacts. Finally, we describe the fabrication and testing of human abdomen soft tissue artifacts, used to display the magnitude of impact tissue deformation. Impact tests were performed at various maximum impact force and average pressure levels.

Boosting specificity of MEG artifact removal by weighted support vector machine.

PubMed

Duan, Fang; Phothisonothai, Montri; Kikuchi, Mitsuru; Yoshimura, Yuko; Minabe, Yoshio; Watanabe, Kastumi; Aihara, Kazuyuki

2013-01-01

An automatic artifact removal method of magnetoencephalogram (MEG) was presented in this paper. The method proposed is based on independent components analysis (ICA) and support vector machine (SVM). However, different from the previous studies, in this paper we consider two factors which would influence the performance. First, the imbalance factor of independent components (ICs) of MEG is handled by weighted SVM. Second, instead of simply setting a fixed weight to each class, a re-weighting scheme is used for the preservation of useful MEG ICs. Experimental results on manually marked MEG dataset showed that the method proposed could correctly distinguish the artifacts from the MEG ICs. Meanwhile, 99.72% ± 0.67 of MEG ICs were preserved. The classification accuracy was 97.91% ± 1.39. In addition, it was found that this method was not sensitive to individual differences. The cross validation (leave-one-subject-out) results showed an averaged accuracy of 97.41% ± 2.14.

Metal artifact removal (MAR) analysis for the security inspections using the X-ray computed tomography

NASA Astrophysics Data System (ADS)

Cho, Hyo Sung; Woo, Tae Ho; Park, Chul Kyu

2016-10-01

Using the metal artifact property, it is analyzed for the X-ray computed tomography (CT) in the aspect of the security on the examined places like airport and surveillance areas. Since the importance of terror prevention strategy has been increased, the security application of X-ray CT has the significant remark. One shot X-ray image has the limitation to find out the exact shape to property in the closed box, which could be solved by the CT scanning without the tearing off the box in this work. Cleaner images can be obtained by the advanced technology if the CT scanning is utilized in the security purposes on the secured areas. A metal sample is treated by the metal artifact removal (MAR) method for the enhanced image. The mimicked explosive is experimented for the imaging processing application where the cleaner one is obtained. The procedure is explained and the further study is discussed.

Congenital Complete Absence of Pericardium Masquerading as Pulmonary Embolism

PubMed Central

Tariq, Saad; Mahmood, Sultan; Madeira, Samuel; Tarasov, Ethan

2013-01-01

Congenital absence of the pericardium is a rare cardiac condition, which can be either isolated or associated with other cardiac and extracardiac anomalies. There are six different types, depending on the severity of the involvement. Most of the patients with this defect are asymptomatic, especially the ones with complete absence of the pericardium. However, some patients are symptomatic, reporting symptoms that include chest pain, palpitations, dyspnea, and syncope. Diagnosis is established by the characteristic features on chest X-ray, echocardiogram, chest computed tomography (CT), and/or cardiac magnetic resonance imging (MRI). We present here a case of a 23 year-old-male, who presented to our hospital with complaints of pleuritic chest pain and exertional dyspnea, of a two-week duration. He was physically active and his past history was otherwise insignificant. His chest CT with contrast was interpreted as showing evidence of multiple emboli, predominantly in the left lung, and he was started on a heparin and warfarin therapy. A repeat chest CT with contrast three weeks later showed no significant change from the previous CT scan. Both scans showed that the heart was abnormally rotated to the left side of the chest. An echocardiogram raised the suspicion of congenital absence of the pericardium, with a posteriorly displaced heart. In retrospect, motion artifact on the left lung, attributed to cardiac pulsations and the lack of pericardium, resulted in a CT chest appearance, mimicking findings of pulmonary embolism. The misdiagnosis of pulmonary embolism was attributed to the artifact caused by excessive cardiac motion artifact on the chest CT scan. In non-gated CT angiograms, excessive motion causes an artifact that blurs the pulmonary vessels, reminiscent of a ′seagull′ or a ′boomerang′. Physicians need to be aware of this phenomenon, as well as the characteristic radiological features of this congenital anomaly, to enable them to make a correct diagnosis. PMID:23580923

Tackling the challenge of selective analytical clean-up of complex natural extracts: the curious case of chlorophyll removal.

PubMed

Bijttebier, Sebastiaan; D'Hondt, Els; Noten, Bart; Hermans, Nina; Apers, Sandra; Voorspoels, Stefan

2014-11-15

Alkaline saponification is often used to remove interfering chlorophylls and lipids during carotenoids analysis. However, saponification also hydrolyses esterified carotenoids and is known to induce artifacts. To avoid carotenoid artifact formation during saponification, Larsen and Christensen (2005) developed a gentler and simpler analytical clean-up procedure involving the use of a strong basic resin (Ambersep 900 OH). They hypothesised a saponification mechanism based on their Liquid Chromatography-Photodiode Array (LC-PDA) data. In the present study, we show with LC-PDA-accurate mass-Mass Spectrometry that the main chlorophyll removal mechanism is not based on saponification, apolar adsorption or anion exchange, but most probably an adsorption mechanism caused by H-bonds and dipole-dipole interactions. We showed experimentally that esterified carotenoids and glycerolipids were not removed, indicating a much more selective mechanism than initially hypothesised. This opens new research opportunities towards a much wider scope of applications (e.g. the refinement of oils rich in phytochemical content). Copyright © 2014 Elsevier Ltd. All rights reserved.

Ultrahigh speed Spectral / Fourier domain OCT ophthalmic imaging at 70,000 to 312,500 axial scans per second

PubMed Central

Potsaid, Benjamin; Gorczynska, Iwona; Srinivasan, Vivek J.; Chen, Yueli; Jiang, James; Cable, Alex; Fujimoto, James G.

2009-01-01

We demonstrate ultrahigh speed spectral / Fourier domain optical coherence tomography (OCT) using an ultrahigh speed CMOS line scan camera at rates of 70,000 - 312,500 axial scans per second. Several design configurations are characterized to illustrate trade-offs between acquisition speed, resolution, imaging range, sensitivity and sensitivity roll-off performance. Ultrahigh resolution OCT with 2.5 - 3.0 micron axial image resolution is demonstrated at ∼ 100,000 axial scans per second. A high resolution spectrometer design improves sensitivity roll-off and imaging range performance, trading off imaging speed to 70,000 axial scans per second. Ultrahigh speed imaging at >300,000 axial scans per second with standard image resolution is also demonstrated. Ophthalmic OCT imaging of the normal human retina is investigated. The high acquisition speeds enable dense raster scanning to acquire densely sampled volumetric three dimensional OCT (3D-OCT) data sets of the macula and optic disc with minimal motion artifacts. Imaging with ∼ 8 - 9 micron axial resolution at 250,000 axial scans per second, a 512 × 512 × 400 voxel volumetric 3D-OCT data set can be acquired in only ∼ 1.3 seconds. Orthogonal registration scans are used to register OCT raster scans and remove residual axial eye motion, resulting in 3D-OCT data sets which preserve retinal topography. Rapid repetitive imaging over small volumes can visualize small retinal features without motion induced distortions and enables volume registration to remove eye motion. Cone photoreceptors in some regions of the retina can be visualized without adaptive optics or active eye tracking. Rapid repetitive imaging of 3D volumes also provides dynamic volumetric information (4D-OCT) which is shown to enhance visualization of retinal capillaries and should enable functional imaging. Improvements in the speed and performance of 3D-OCT volumetric imaging promise to enable earlier diagnosis and improved monitoring of disease progression and response to therapy in ophthalmology, as well as have a wide range of research and clinical applications in other areas. PMID:18795054

Limited angle breast ultrasound tomography with a priori information and artifact removal

NASA Astrophysics Data System (ADS)

Jintamethasawat, Rungroj; Zhu, Yunhao; Kripfgans, Oliver D.; Yuan, Jie; Goodsitt, Mitchell M.; Carson, Paul L.

2017-03-01

In B-mode images from dual-sided ultrasound, it has been shown that by delineating structures suspected of being relatively homogeneous, one can enhance limited angle tomography to produce speed of sound images in the same view as X-ray Digital Breast Tomography (DBT). This could allow better breast cancer detection and discrimination, as well as improved registration of the ultrasound and X-ray images, because of the similarity of SOS and X-ray contrast in the breast. However, this speed of sound reconstruction method relies strongly on B-mode or other reflection mode segmentation. If that information is limited or incorrect, artifacts will appear in the reconstructed images. Therefore, the iterative speed of sound reconstruction algorithm has been modified in a manner of simultaneously utilizing the image segmentations and removing most artifacts. The first step of incorporating a priori information is solved by any nonlinearnonconvex optimization method while artifact removal is accomplished by employing the fast split Bregman method to perform total-variation (TV) regularization for image denoising. The proposed method was demonstrated in simplified simulations of our dual-sided ultrasound scanner. To speed these computations two opposed 40-element ultrasound linear arrays with 0.5 MHz center frequency were simulated for imaging objects in a uniform background. The proposed speed of sound reconstruction method worked well with both bent-ray and full-wave inversion methods. This is also the first demonstration of successful full-wave medical ultrasound tomography in the limited angle geometry. Presented results lend credibility to a possible translation of this method to clinical breast imaging.

Geometric correction method for 3d in-line X-ray phase contrast image reconstruction

PubMed Central

2014-01-01

Background Mechanical system with imperfect or misalignment of X-ray phase contrast imaging (XPCI) components causes projection data misplaced, and thus result in the reconstructed slice images of computed tomography (CT) blurred or with edge artifacts. So the features of biological microstructures to be investigated are destroyed unexpectedly, and the spatial resolution of XPCI image is decreased. It makes data correction an essential pre-processing step for CT reconstruction of XPCI. Methods To remove unexpected blurs and edge artifacts, a mathematics model for in-line XPCI is built by considering primary geometric parameters which include a rotation angle and a shift variant in this paper. Optimal geometric parameters are achieved by finding the solution of a maximization problem. And an iterative approach is employed to solve the maximization problem by using a two-step scheme which includes performing a composite geometric transformation and then following a linear regression process. After applying the geometric transformation with optimal parameters to projection data, standard filtered back-projection algorithm is used to reconstruct CT slice images. Results Numerical experiments were carried out on both synthetic and real in-line XPCI datasets. Experimental results demonstrate that the proposed method improves CT image quality by removing both blurring and edge artifacts at the same time compared to existing correction methods. Conclusions The method proposed in this paper provides an effective projection data correction scheme and significantly improves the image quality by removing both blurring and edge artifacts at the same time for in-line XPCI. It is easy to implement and can also be extended to other XPCI techniques. PMID:25069768

Removal of EMG and ECG artifacts from EEG based on wavelet transform and ICA.

PubMed

Zhou, Weidong; Gotman, Jean

2004-01-01

In this study, the methods of wavelet threshold de-noising and independent component analysis (ICA) are introduced. ICA is a novel signal processing technique based on high order statistics, and is used to separate independent components from measurements. The extended ICA algorithm does not need to calculate the higher order statistics, converges fast, and can be used to separate subGaussian and superGaussian sources. A pre-whitening procedure is performed to de-correlate the mixed signals before extracting sources. The experimental results indicate the electromyogram (EMG) and electrocardiograph (ECG) artifacts in electroencephalograph (EEG) can be removed by a combination of wavelet threshold de-noising and ICA.

Development of a Standard to Objectively Define and Measure the End-to-End Quality of Teleconferencing/Videophone Systems

DTIC Science & Technology

1991-02-01

lines; and edge busyness , wherein the position of the edge appears to be moving when there is a rapid signal change . E - 3 APPENDIX Fl T|QI. 5/88-070...Some of the most important new and changed factors are as follows: o Motion must be introduced as a most important feature. o Motion artifacts must be...nominal audio level (measured to ground). edge busyness : The deterioration of motion video such that the outlines of moving objects are displayed with

In situ temperature measurements with thermocouple probes during laser interstitial thermotherapy (LITT): quantification and correction of a measurement artifact.

PubMed

Manns, F; Milne, P J; Gonzalez-Cirre, X; Denham, D B; Parel, J M; Robinson, D S

1998-01-01

The purpose of this work was to quantify the magnitude of an artifact induced by stainless steel thermocouple probes in temperature measurements made in situ during experimental laser interstitial thermo-therapy (LITT). A procedure for correction of this observational error is outlined. A CW Nd:YAG laser system emitting 20W for 25-30 s delivered through a fiber-optic probe was used to create localized heating. The temperature field around the fiber-optic probe during laser irradiation was measured every 0.3 s in air, water, 0.4% intralipid solution, and fatty cadaver pig tissue, with a field of up to fifteen needle thermocouple probes. Direct absorption of Nd:YAG laser radiation by the thermocouple probes induced an overestimation of the temperature, ranging from 1.8 degrees C to 118.6 degrees C in air, 2.2 degrees C to 9.9 degrees C in water, 0.7 C to 4.7 C in intralipid and 0.3 C to 17.9 C in porcine tissue after irradiation at 20W for 30 s and depending on the thermocouple location. The artifact in porcine tissue was removed by applying exponential and linear fits to the measured temperature curves. Light absorption by thermocouple probes can induce a significant artifact in the measurement of laser-induced temperature increases. When the time constant of the thermocouple effect is much smaller than the thermal relaxation time of the surrounding tissue, the artifact can be accurately quantified. During LITT experiments where temperature differences of a few degrees are significant, the thermocouple artifact must be removed in order to be able accurately to predict the treatment outcome.

TU-F-CAMPUS-J-04: Evaluation of Metal Artifact Reduction Technique for the Radiation Therapy Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeong, K; Kuo, H; Ritter, J

Purpose: To evaluate the feasibility of using a metal artifact reduction technique in depleting metal artifact and its application in improving dose calculation in External Radiation Therapy Planning. Methods: CIRS electron density phantom was scanned with and without steel drill bits placed in some plug holes. Meta artifact reduction software with Metal Deletion Technique (MDT) was used to remove metal artifacts for scanned image with metal. Hounsfield units of electron density plugs from artifact free reference image and MDT processed images were compared. To test the dose calculation improvement after the MDT processed images, clinically approved head and neck planmore » with manual dental artifact correction was tested. Patient images were exported and processed with MDT and plan was recalculated with new MDT image without manual correction. Dose profiles near the metal artifacts were compared. Results: The MDT used in this study effectively reduced the metal artifact caused by beam hardening and scatter. The windmill around the metal drill was greatly improved with smooth rounded view. Difference of the mean HU in each density plug between reference and MDT images were less than 10 HU in most of the plugs. Dose difference between original plan and MDT images were minimal. Conclusion: Most metal artifact reduction methods were developed for diagnostic improvement purpose. Hence Hounsfield unit accuracy was not rigorously tested before. In our test, MDT effectively eliminated metal artifacts with good HU reproduciblity. However, it can introduce new mild artifacts so the MDT images should be checked with original images.« less

Real-time eye motion correction in phase-resolved OCT angiography with tracking SLO

PubMed Central

Braaf, Boy; Vienola, Kari V.; Sheehy, Christy K.; Yang, Qiang; Vermeer, Koenraad A.; Tiruveedhula, Pavan; Arathorn, David W.; Roorda, Austin; de Boer, Johannes F.

2012-01-01

In phase-resolved OCT angiography blood flow is detected from phase changes in between A-scans that are obtained from the same location. In ophthalmology, this technique is vulnerable to eye motion. We address this problem by combining inter-B-scan phase-resolved OCT angiography with real-time eye tracking. A tracking scanning laser ophthalmoscope (TSLO) at 840 nm provided eye tracking functionality and was combined with a phase-stabilized optical frequency domain imaging (OFDI) system at 1040 nm. Real-time eye tracking corrected eye drift and prevented discontinuity artifacts from (micro)saccadic eye motion in OCT angiograms. This improved the OCT spot stability on the retina and consequently reduced the phase-noise, thereby enabling the detection of slower blood flows by extending the inter-B-scan time interval. In addition, eye tracking enabled the easy compounding of multiple data sets from the fovea of a healthy volunteer to create high-quality eye motion artifact-free angiograms. High-quality images are presented of two distinct layers of vasculature in the retina and the dense vasculature of the choroid. Additionally we present, for the first time, a phase-resolved OCT angiogram of the mesh-like network of the choriocapillaris containing typical pore openings. PMID:23304647

Reduced aliasing artifacts using shaking projection k-space sampling trajectory

NASA Astrophysics Data System (ADS)

Zhu, Yan-Chun; Du, Jiang; Yang, Wen-Chao; Duan, Chai-Jie; Wang, Hao-Yu; Gao, Song; Bao, Shang-Lian

2014-03-01

Radial imaging techniques, such as projection-reconstruction (PR), are used in magnetic resonance imaging (MRI) for dynamic imaging, angiography, and short-T2 imaging. They are less sensitive to flow and motion artifacts, and support fast imaging with short echo times. However, aliasing and streaking artifacts are two main sources which degrade radial imaging quality. For a given fixed number of k-space projections, data distributions along radial and angular directions will influence the level of aliasing and streaking artifacts. Conventional radial k-space sampling trajectory introduces an aliasing artifact at the first principal ring of point spread function (PSF). In this paper, a shaking projection (SP) k-space sampling trajectory was proposed to reduce aliasing artifacts in MR images. SP sampling trajectory shifts the projection alternately along the k-space center, which separates k-space data in the azimuthal direction. Simulations based on conventional and SP sampling trajectories were compared with the same number projections. A significant reduction of aliasing artifacts was observed using the SP sampling trajectory. These two trajectories were also compared with different sampling frequencies. A SP trajectory has the same aliasing character when using half sampling frequency (or half data) for reconstruction. SNR comparisons with different white noise levels show that these two trajectories have the same SNR character. In conclusion, the SP trajectory can reduce the aliasing artifact without decreasing SNR and also provide a way for undersampling reconstruction. Furthermore, this method can be applied to three-dimensional (3D) hybrid or spherical radial k-space sampling for a more efficient reduction of aliasing artifacts.

Online Artifact Removal for Brain-Computer Interfaces Using Support Vector Machines and Blind Source Separation

PubMed Central

Halder, Sebastian; Bensch, Michael; Mellinger, Jürgen; Bogdan, Martin; Kübler, Andrea; Birbaumer, Niels; Rosenstiel, Wolfgang

2007-01-01

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to determine their ability to isolate electromyographic (EMG) and electrooculographic (EOG) artifacts into individual components. An implementation of the selected BSS/ICA method with SVMs trained to classify EMG and EOG artifacts, which enables the usage of the method as a filter in measurements with online feedback, is described. This filter is evaluated on three BCI datasets as a proof-of-concept of the method. PMID:18288259

Online artifact removal for brain-computer interfaces using support vector machines and blind source separation.

PubMed

Halder, Sebastian; Bensch, Michael; Mellinger, Jürgen; Bogdan, Martin; Kübler, Andrea; Birbaumer, Niels; Rosenstiel, Wolfgang

2007-01-01

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to determine their ability to isolate electromyographic (EMG) and electrooculographic (EOG) artifacts into individual components. An implementation of the selected BSS/ICA method with SVMs trained to classify EMG and EOG artifacts, which enables the usage of the method as a filter in measurements with online feedback, is described. This filter is evaluated on three BCI datasets as a proof-of-concept of the method.

Prospective motion correction with volumetric navigators (vNavs) reduces the bias and variance in brain morphometry induced by subject motion.

PubMed

Tisdall, M Dylan; Reuter, Martin; Qureshi, Abid; Buckner, Randy L; Fischl, Bruce; van der Kouwe, André J W

2016-02-15

Recent work has demonstrated that subject motion produces systematic biases in the metrics computed by widely used morphometry software packages, even when the motion is too small to produce noticeable image artifacts. In the common situation where the control population exhibits different behaviors in the scanner when compared to the experimental population, these systematic measurement biases may produce significant confounds for between-group analyses, leading to erroneous conclusions about group differences. While previous work has shown that prospective motion correction can improve perceived image quality, here we demonstrate that, in healthy subjects performing a variety of directed motions, the use of the volumetric navigator (vNav) prospective motion correction system significantly reduces the motion-induced bias and variance in morphometry. Copyright © 2015 Elsevier Inc. All rights reserved.

A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor

PubMed Central

Salehizadeh, Seyed M. A.; Dao, Duy; Bolkhovsky, Jeffrey; Cho, Chae; Mendelson, Yitzhak; Chon, Ki H.

2015-01-01

Accurate estimation of heart rates from photoplethysmogram (PPG) signals during intense physical activity is a very challenging problem. This is because strenuous and high intensity exercise can result in severe motion artifacts in PPG signals, making accurate heart rate (HR) estimation difficult. In this study we investigated a novel technique to accurately reconstruct motion-corrupted PPG signals and HR based on time-varying spectral analysis. The algorithm is called Spectral filter algorithm for Motion Artifacts and heart rate reconstruction (SpaMA). The idea is to calculate the power spectral density of both PPG and accelerometer signals for each time shift of a windowed data segment. By comparing time-varying spectra of PPG and accelerometer data, those frequency peaks resulting from motion artifacts can be distinguished from the PPG spectrum. The SpaMA approach was applied to three different datasets and four types of activities: (1) training datasets from the 2015 IEEE Signal Process. Cup Database recorded from 12 subjects while performing treadmill exercise from 1 km/h to 15 km/h; (2) test datasets from the 2015 IEEE Signal Process. Cup Database recorded from 11 subjects while performing forearm and upper arm exercise. (3) Chon Lab dataset including 10 min recordings from 10 subjects during treadmill exercise. The ECG signals from all three datasets provided the reference HRs which were used to determine the accuracy of our SpaMA algorithm. The performance of the SpaMA approach was calculated by computing the mean absolute error between the estimated HR from the PPG and the reference HR from the ECG. The average estimation errors using our method on the first, second and third datasets are 0.89, 1.93 and 1.38 beats/min respectively, while the overall error on all 33 subjects is 1.86 beats/min and the performance on only treadmill experiment datasets (22 subjects) is 1.11 beats/min. Moreover, it was found that dynamics of heart rate variability can be accurately captured using the algorithm where the mean Pearson’s correlation coefficient between the power spectral densities of the reference and the reconstructed heart rate time series was found to be 0.98. These results show that the SpaMA method has a potential for PPG-based HR monitoring in wearable devices for fitness tracking and health monitoring during intense physical activities. PMID:26703618

A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor.

PubMed

Salehizadeh, Seyed M A; Dao, Duy; Bolkhovsky, Jeffrey; Cho, Chae; Mendelson, Yitzhak; Chon, Ki H

2015-12-23

Accurate estimation of heart rates from photoplethysmogram (PPG) signals during intense physical activity is a very challenging problem. This is because strenuous and high intensity exercise can result in severe motion artifacts in PPG signals, making accurate heart rate (HR) estimation difficult. In this study we investigated a novel technique to accurately reconstruct motion-corrupted PPG signals and HR based on time-varying spectral analysis. The algorithm is called Spectral filter algorithm for Motion Artifacts and heart rate reconstruction (SpaMA). The idea is to calculate the power spectral density of both PPG and accelerometer signals for each time shift of a windowed data segment. By comparing time-varying spectra of PPG and accelerometer data, those frequency peaks resulting from motion artifacts can be distinguished from the PPG spectrum. The SpaMA approach was applied to three different datasets and four types of activities: (1) training datasets from the 2015 IEEE Signal Process. Cup Database recorded from 12 subjects while performing treadmill exercise from 1 km/h to 15 km/h; (2) test datasets from the 2015 IEEE Signal Process. Cup Database recorded from 11 subjects while performing forearm and upper arm exercise. (3) Chon Lab dataset including 10 min recordings from 10 subjects during treadmill exercise. The ECG signals from all three datasets provided the reference HRs which were used to determine the accuracy of our SpaMA algorithm. The performance of the SpaMA approach was calculated by computing the mean absolute error between the estimated HR from the PPG and the reference HR from the ECG. The average estimation errors using our method on the first, second and third datasets are 0.89, 1.93 and 1.38 beats/min respectively, while the overall error on all 33 subjects is 1.86 beats/min and the performance on only treadmill experiment datasets (22 subjects) is 1.11 beats/min. Moreover, it was found that dynamics of heart rate variability can be accurately captured using the algorithm where the mean Pearson's correlation coefficient between the power spectral densities of the reference and the reconstructed heart rate time series was found to be 0.98. These results show that the SpaMA method has a potential for PPG-based HR monitoring in wearable devices for fitness tracking and health monitoring during intense physical activities.

GESFIDE-PROPELLER approach for simultaneous R2 and R2* measurements in the abdomen.

PubMed

Jin, Ning; Guo, Yang; Zhang, Zhuoli; Zhang, Longjiang; Lu, Guangming; Larson, Andrew C

2013-12-01

To investigate the feasibility of combining GESFIDE with PROPELLER sampling approaches for simultaneous abdominal R2 and R2* mapping. R2 and R2* measurements were performed in 9 healthy volunteers and phantoms using the GESFIDE-PROPELLER and the conventional Cartesian-sampling GESFIDE approaches. Images acquired with the GESFIDE-PROPELLER sequence effectively mitigated the respiratory motion artifacts, which were clearly evident in the images acquired using the conventional GESFIDE approach. There was no significant difference between GESFIDE-PROPELLER and reference MGRE R2* measurements (p=0.162) whereas the Cartesian-sampling based GESFIDE methods significantly overestimated R2* values compared to MGRE measurements (p<0.001). The GESFIDE-PROPELLER sequence provided high quality images and accurate abdominal R2 and R2* maps while avoiding the motion artifacts common to the conventional Cartesian-sampling GESFIDE approaches. © 2013 Elsevier Inc. All rights reserved.

GESFIDE-PROPELLER Approach for Simultaneous R2 and R2* Measurements in the Abdomen

PubMed Central

Jin, Ning; Guo, Yang; Zhang, Zhuoli; Zhang, Longjiang; Lu, Guangming; Larson, Andrew C.

2013-01-01

Purpose To investigate the feasibility of combining GESFIDE with PROPELLER sampling approaches for simultaneous abdominal R2 and R2* mapping. Materials and Methods R2 and R2* measurements were performed in 9 healthy volunteers and phantoms using the GESFIDE-PROPELLER and the conventional Cartesian-sampling GESFIDE approaches. Results Images acquired with the GESFIDE-PROPELLER sequence effectively mitigated the respiratory motion artifacts, which were clearly evident in the images acquired using the conventional GESFIDE approach. There were no significant difference between GESFIDE-PROPELLER and reference MGRE R2* measurements (p = 0.162) whereas the Cartesian-sampling based GESFIDE methods significantly overestimated R2* values compared to MGRE measurements (p < 0.001). Conclusion The GESFIDE-PROPELLER sequence provided high quality images and accurate abdominal R2 and R2* maps while avoiding the motion artifacts common to the conventional Cartesian-sampling GESFIDE approaches. PMID:24041478

Driving technology for improving motion quality of active-matrix organic light-emitting diode display

NASA Astrophysics Data System (ADS)

Kim, Jongbin; Kim, Minkoo; Kim, Jong-Man; Kim, Seung-Ryeol; Lee, Seung-Woo

2014-09-01

This paper reports transient response characteristics of active-matrix organic light emitting diode (AMOLED) displays for mobile applications. This work reports that the rising responses look like saw-tooth waveform and are not always faster than those of liquid crystal displays. Thus, a driving technology is proposed to improve the rising transient responses of AMOLED based on the overdrive (OD) technology. We modified the OD technology by combining it with a dithering method because the conventional OD method cannot successfully enhance all the rising responses. Our method can improve all the transitions of AMOLED without modifying the conventional gamma architecture of drivers. A new artifact is found when OD is applied to certain transitions. We propose an optimum OD selection method to mitigate the artifact. The implementation results show the proposed technology can successfully improve motion quality of scrolling texts as well as moving pictures in AMOLED displays.

ECG artifact cancellation in surface EMG signals by fractional order calculus application.

PubMed

Miljković, Nadica; Popović, Nenad; Djordjević, Olivera; Konstantinović, Ljubica; Šekara, Tomislav B

2017-03-01

New aspects for automatic electrocardiography artifact removal from surface electromyography signals by application of fractional order calculus in combination with linear and nonlinear moving window filters are explored. Surface electromyography recordings of skeletal trunk muscles are commonly contaminated with spike shaped artifacts. This artifact originates from electrical heart activity, recorded by electrocardiography, commonly present in the surface electromyography signals recorded in heart proximity. For appropriate assessment of neuromuscular changes by means of surface electromyography, application of a proper filtering technique of electrocardiography artifact is crucial. A novel method for automatic artifact cancellation in surface electromyography signals by applying fractional order calculus and nonlinear median filter is introduced. The proposed method is compared with the linear moving average filter, with and without prior application of fractional order calculus. 3D graphs for assessment of window lengths of the filters, crest factors, root mean square differences, and fractional calculus orders (called WFC and WRC graphs) have been introduced. For an appropriate quantitative filtering evaluation, the synthetic electrocardiography signal and analogous semi-synthetic dataset have been generated. The examples of noise removal in 10 able-bodied subjects and in one patient with muscle dystrophy are presented for qualitative analysis. The crest factors, correlation coefficients, and root mean square differences of the recorded and semi-synthetic electromyography datasets showed that the most successful method was the median filter in combination with fractional order calculus of the order 0.9. Statistically more significant (p < 0.001) ECG peak reduction was obtained by the median filter application compared to the moving average filter in the cases of low level amplitude of muscle contraction compared to ECG spikes. The presented results suggest that the novel method combining a median filter and fractional order calculus can be used for automatic filtering of electrocardiography artifacts in the surface electromyography signal envelopes recorded in trunk muscles. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Correcting nonlinear drift distortion of scanning probe and scanning transmission electron microscopies from image pairs with orthogonal scan directions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ophus, Colin; Ciston, Jim; Nelson, Chris T.

Unwanted motion of the probe with respect to the sample is a ubiquitous problem in scanning probe and scanning transmission electron microscopies, causing both linear and nonlinear artifacts in experimental images. We have designed a procedure to correct these artifacts by using orthogonal scan pairs to align each measurement line-by-line along the slow scan direction, by fitting contrast variation along the lines. We demonstrate the accuracy of our algorithm on both synthetic and experimental data and provide an implementation of our method.

Correcting nonlinear drift distortion of scanning probe and scanning transmission electron microscopies from image pairs with orthogonal scan directions

DOE PAGES

Ophus, Colin; Ciston, Jim; Nelson, Chris T.

2015-12-10

Unwanted motion of the probe with respect to the sample is a ubiquitous problem in scanning probe and scanning transmission electron microscopies, causing both linear and nonlinear artifacts in experimental images. We have designed a procedure to correct these artifacts by using orthogonal scan pairs to align each measurement line-by-line along the slow scan direction, by fitting contrast variation along the lines. We demonstrate the accuracy of our algorithm on both synthetic and experimental data and provide an implementation of our method.

Robust artifactual independent component classification for BCI practitioners.

PubMed

Winkler, Irene; Brandl, Stephanie; Horn, Franziska; Waldburger, Eric; Allefeld, Carsten; Tangermann, Michael

2014-06-01

EEG artifacts of non-neural origin can be separated from neural signals by independent component analysis (ICA). It is unclear (1) how robustly recently proposed artifact classifiers transfer to novel users, novel paradigms or changed electrode setups, and (2) how artifact cleaning by a machine learning classifier impacts the performance of brain-computer interfaces (BCIs). Addressing (1), the robustness of different strategies with respect to the transfer between paradigms and electrode setups of a recently proposed classifier is investigated on offline data from 35 users and 3 EEG paradigms, which contain 6303 expert-labeled components from two ICA and preprocessing variants. Addressing (2), the effect of artifact removal on single-trial BCI classification is estimated on BCI trials from 101 users and 3 paradigms. We show that (1) the proposed artifact classifier generalizes to completely different EEG paradigms. To obtain similar results under massively reduced electrode setups, a proposed novel strategy improves artifact classification. Addressing (2), ICA artifact cleaning has little influence on average BCI performance when analyzed by state-of-the-art BCI methods. When slow motor-related features are exploited, performance varies strongly between individuals, as artifacts may obstruct relevant neural activity or are inadvertently used for BCI control. Robustness of the proposed strategies can be reproduced by EEG practitioners as the method is made available as an EEGLAB plug-in.

Direct vibro-elastography FEM inversion in Cartesian and cylindrical coordinate systems without the local homogeneity assumption

NASA Astrophysics Data System (ADS)

Honarvar, M.; Lobo, J.; Mohareri, O.; Salcudean, S. E.; Rohling, R.

2015-05-01

To produce images of tissue elasticity, the vibro-elastography technique involves applying a steady-state multi-frequency vibration to tissue, estimating displacements from ultrasound echo data, and using the estimated displacements in an inverse elasticity problem with the shear modulus spatial distribution as the unknown. In order to fully solve the inverse problem, all three displacement components are required. However, using ultrasound, the axial component of the displacement is measured much more accurately than the other directions. Therefore, simplifying assumptions must be used in this case. Usually, the equations of motion are transformed into a Helmholtz equation by assuming tissue incompressibility and local homogeneity. The local homogeneity assumption causes significant imaging artifacts in areas of varying elasticity. In this paper, we remove the local homogeneity assumption. In particular we introduce a new finite element based direct inversion technique in which only the coupling terms in the equation of motion are ignored, so it can be used with only one component of the displacement. Both Cartesian and cylindrical coordinate systems are considered. The use of multi-frequency excitation also allows us to obtain multiple measurements and reduce artifacts in areas where the displacement of one frequency is close to zero. The proposed method was tested in simulations and experiments against a conventional approach in which the local homogeneity is used. The results show significant improvements in elasticity imaging with the new method compared to previous methods that assumes local homogeneity. For example in simulations, the contrast to noise ratio (CNR) for the region with spherical inclusion increases from an average value of 1.5-17 after using the proposed method instead of the local inversion with homogeneity assumption, and similarly in the prostate phantom experiment, the CNR improved from an average value of 1.6 to about 20.

Parallel magnetic resonance imaging using coils with localized sensitivities.

PubMed

Goldfarb, James W; Holland, Agnes E

2004-09-01

The purpose of this study was to present clinical examples and illustrate the inefficiencies of a conventional reconstruction using a commercially available phased array coil with localized sensitivities. Five patients were imaged at 1.5 T using a cardiac-synchronized gadolinium-enhanced acquisition and a commercially available four-element phased array coil. Four unique sets of images were reconstructed from the acquired k-space data: (a) sum-of-squares image using four elements of the coil; localized sum-of-squares images from the (b) anterior coils and (c) posterior coils and a (c) local reconstruction. Images were analyzed for artifacts and usable field-of-view. Conventional image reconstruction produced images with fold-over artifacts in all cases spanning a portion of the image (mean 90 mm; range 36-126 mm). The local reconstruction removed fold-over artifacts and resulted in an effective increase in the field-of-view (mean 50%; range 20-70%). Commercially available phased array coils do not always have overlapping sensitivities. Fold-over artifacts can be removed using an alternate reconstruction method. When assessing the advantages of parallel imaging techniques, gains achieved using techniques such as SENSE and SMASH should be gauged against the acquisition time of the localized method rather than the conventional sum-of-squares method.

A graphical user interface for infant ERP analysis.

PubMed

Kaatiala, Jussi; Yrttiaho, Santeri; Forssman, Linda; Perdue, Katherine; Leppänen, Jukka

2014-09-01

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9-21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users.

Motion correction for functional MRI with three-dimensional hybrid radial-Cartesian EPI.

PubMed

Graedel, Nadine N; McNab, Jennifer A; Chiew, Mark; Miller, Karla L

2017-08-01

Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three-dimensional (3D EPI). We present a hybrid radial-Cartesian 3D EPI trajectory enabling motion correction in k-space for functional MRI. The EPI "blades" of the 3D hybrid radial-Cartesian EPI sequence, called TURBINE, are rotated about the phase-encoding axis to fill out a cylinder in 3D k-space. Angular blades are acquired over time using a golden-angle rotation increment, allowing reconstruction at flexible temporal resolution. The self-navigating properties of the sequence are used to determine motion parameters from a high temporal-resolution navigator time series. The motion is corrected in k-space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion. We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal-to-noise ratio and fMRI activation in the presence of both severe and subtle motion. We show the potential for hybrid radial-Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527-540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications

PubMed Central

Stone, David B.; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications. PMID:29618975

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications.

PubMed

Stone, David B; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications.

Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

PubMed

Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

2017-09-01

This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert neurophysiologists, EMG signal recording and user visual inspection. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Constraints as a destriping tool for Hires images

NASA Technical Reports Server (NTRS)

Cao, YU; Prince, Thomas A.

1994-01-01

Images produced from the Maximum Correlation Method sometimes suffer from visible striping artifacts, especially for areas of extended sources. Possible causes are different baseline levels and calibration errors in the detectors. We incorporated these factors into the MCM algorithm, and tested the effects of different constraints on the output image. The result shows significant visual improvement over the standard MCM Method. In some areas the new images show intelligible structures that are otherwise corrupted by striping artifacts, and the removal of these artifacts could enhance performance of object classification algorithms. The constraints were also tested on low surface brightness areas, and were found to be effective in reducing the noise level.

Motion artifact and background noise suppression on optical microangiography frames using a naïve Bayes mask.

PubMed

Reif, Roberto; Baran, Utku; Wang, Ruikang K

2014-07-01

Optical coherence tomography (OCT) is a technique that allows for the three-dimensional (3D) imaging of small volumes of tissue (a few millimeters) with high resolution (∼10  μm). Optical microangiography (OMAG) is a method of processing OCT data, which allows for the extraction of the tissue vasculature with capillary resolution from the OCT images. Cross-sectional B-frame OMAG images present the location of the patent blood vessels; however, the signal-to-noise-ratio of these images can be affected by several factors such as the quality of the OCT system and the tissue motion artifact. This background noise can appear in the en face projection view image. In this work we propose to develop a binary mask that can be applied on the cross-sectional B-frame OMAG images, which will reduce the background noise while leaving the signal from the blood vessels intact. The mask is created by using a naïve Bayes (NB) classification algorithm trained with a gold standard image which is manually segmented by an expert. The masked OMAG images present better contrast for binarizing the image and quantifying the result without the influence of noise. The results are compared with a previously developed frequency rejection filter (FRF) method which is applied on the en face projection view image. It is demonstrated that both the NB and FRF methods provide similar vessel length fractions. The advantage of the NB method is that the results are applicable in 3D and that its use is not limited to periodic motion artifacts.

Optimized statistical parametric mapping procedure for NIRS data contaminated by motion artifacts : Neurometric analysis of body schema extension.

PubMed

Suzuki, Satoshi

2017-09-01

This study investigated the spatial distribution of brain activity on body schema (BS) modification induced by natural body motion using two versions of a hand-tracing task. In Task 1, participants traced Japanese Hiragana characters using the right forefinger, requiring no BS expansion. In Task 2, participants performed the tracing task with a long stick, requiring BS expansion. Spatial distribution was analyzed using general linear model (GLM)-based statistical parametric mapping of near-infrared spectroscopy data contaminated with motion artifacts caused by the hand-tracing task. Three methods were utilized in series to counter the artifacts, and optimal conditions and modifications were investigated: a model-free method (Step 1), a convolution matrix method (Step 2), and a boxcar-function-based Gaussian convolution method (Step 3). The results revealed four methodological findings: (1) Deoxyhemoglobin was suitable for the GLM because both Akaike information criterion and the variance against the averaged hemodynamic response function were smaller than for other signals, (2) a high-pass filter with a cutoff frequency of .014 Hz was effective, (3) the hemodynamic response function computed from a Gaussian kernel function and its first- and second-derivative terms should be included in the GLM model, and (4) correction of non-autocorrelation and use of effective degrees of freedom were critical. Investigating z-maps computed according to these guidelines revealed that contiguous areas of BA7-BA40-BA21 in the right hemisphere became significantly activated ([Formula: see text], [Formula: see text], and [Formula: see text], respectively) during BS modification while performing the hand-tracing task.

Combined Electrocardiography- and Respiratory-Triggered CT of the Lung to Reduce Respiratory Misregistration Artifacts between Imaging Slabs in Free-Breathing Children: Initial Experience

PubMed Central

Allmendinger, Thomas

2017-01-01

Objective Cardiac and respiratory motion artifacts degrade the image quality of lung CT in free-breathing children. The aim of this study was to evaluate the effect of combined electrocardiography (ECG) and respiratory triggering on respiratory misregistration artifacts on lung CT in free-breathing children. Materials and Methods In total, 15 children (median age 19 months, range 6 months–8 years; 7 boys), who underwent free-breathing ECG-triggered lung CT with and without respiratory-triggering were included. A pressure-sensing belt of a respiratory gating system was used to obtain the respiratory signal. The degree of respiratory misregistration artifacts between imaging slabs was graded on a 4-point scale (1, excellent image quality) on coronal and sagittal images and compared between ECG-triggered lung CT studies with and without respiratory triggering. A p value < 0.05 was considered significant. Results Lung CT with combined ECG and respiratory triggering showed significantly less respiratory misregistration artifacts than lung CT with ECG triggering only (1.1 ± 0.4 vs. 2.2 ± 1.0, p = 0.003). Conclusion Additional respiratory-triggering reduces respiratory misregistration artifacts on ECG-triggered lung CT in free-breathing children. PMID:28860904

SU-F-303-13: Initial Evaluation of Four Dimensional Diffusion- Weighted MRI (4D-DWI) and Its Effect On Apparent Diffusion Coefficient (ADC) Measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Yin, F; Czito, B

2015-06-15

Purpose: Diffusion-weighted imaging(DWI) has been shown to have superior tumor-to-tissue contrast for cancer detection.This study aims at developing and evaluating a four dimensional DWI(4D-DWI) technique using retrospective sorting method for imaging respiratory motion for radiotherapy planning,and evaluate its effect on Apparent Diffusion Coefficient(ADC) measurement. Materials/Methods: Image acquisition was performed by repeatedly imaging a volume of interest using a multi-slice single-shot 2D-DWI sequence in the axial planes and cine MRI(served as reference) using FIESTA sequence.Each 2D-DWI image were acquired in xyz-diffusion-directions with a high b-value(b=500s/mm2).The respiratory motion was simultaneously recorded using bellows.Retrospective sorting was applied in each direction to reconstruct 4D-DWI.Themore » technique was evaluated using a computer simulated 4D-digital human phantom(XCAT),a motion phantom and a healthy volunteer under an IRB-approved study.Motion trajectories of regions-of-interests(ROI) were extracted from 4D-DWI and compared with reference.The mean motion trajectory amplitude differences(D) between the two was calculated.To quantitatively analyze the motion artifacts,XCAT were controlled to simulate regular motion and the motions of 10 liver cancer patients.4D-DWI,free-breathing DWI(FB- DWI) were reconstructed.Tumor volume difference(VD) of each phase of 4D-DWI and FB-DWI from the input static tumor were calculated.Furthermore, ADC was measured for each phase of 4D-DWI and FB-DWI data,and mean tumor ADC values(M-ADC) were calculated.Mean M-ADC over all 4D-DWI phases was compared with M-ADC calculated from FB-DWI. Results: 4D-DWI of XCAT,the motion phantom and the healthy volunteer demonstrated the respiratory motion clearly.ROI D values were 1.9mm,1.7mm and 2.0mm,respectively.For motion artifacts analysis,XCAT 4D-DWI images show much less motion artifacts compare to FB-DWI.Mean VD for 4D-WDI and FB-DWI were 8.5±1.4% and 108±15%,respectively.Mean M-ADC for ADC measured from 4D-DWI and M-ADC measured from FB-DWI were (2.29±0.04)*0.001*mm2/s and (3.80±0.01)*0.001*mm2/s,respectively.ADC value ground-truth is 2.24*0.001*mm2/s from the input of the simulation. Conclusion: A respiratory correlated 4D-DWI technique has been initially evaluated in phantoms and a human subject.Comparing to free breathing DWI,4D-DWI can lead to more accurate measurement of ADC.« less

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI.

PubMed

Alansary, Amir; Rajchl, Martin; McDonagh, Steven G; Murgasova, Maria; Damodaram, Mellisa; Lloyd, David F A; Davidson, Alice; Rutherford, Mary; Hajnal, Joseph V; Rueckert, Daniel; Kainz, Bernhard

2017-10-01

In this paper, we present a novel method for the correction of motion artifacts that are present in fetal magnetic resonance imaging (MRI) scans of the whole uterus. Contrary to current slice-to-volume registration (SVR) methods, requiring an inflexible anatomical enclosure of a single investigated organ, the proposed patch-to-volume reconstruction (PVR) approach is able to reconstruct a large field of view of non-rigidly deforming structures. It relaxes rigid motion assumptions by introducing a specific amount of redundant information that is exploited with parallelized patchwise optimization, super-resolution, and automatic outlier rejection. We further describe and provide an efficient parallel implementation of PVR allowing its execution within reasonable time on commercially available graphics processing units, enabling its use in the clinical practice. We evaluate PVR's computational overhead compared with standard methods and observe improved reconstruction accuracy in the presence of affine motion artifacts compared with conventional SVR in synthetic experiments. Furthermore, we have evaluated our method qualitatively and quantitatively on real fetal MRI data subject to maternal breathing and sudden fetal movements. We evaluate peak-signal-to-noise ratio, structural similarity index, and cross correlation with respect to the originally acquired data and provide a method for visual inspection of reconstruction uncertainty. We further evaluate the distance error for selected anatomical landmarks in the fetal head, as well as calculating the mean and maximum displacements resulting from automatic non-rigid registration to a motion-free ground truth image. These experiments demonstrate a successful application of PVR motion compensation to the whole fetal body, uterus, and placenta.

Mechanical behaviour of condenser microphone in mechanomyography.

PubMed

Watakabe, M; Mita, K; Akataki, K; Itoh, Y

2001-03-01

Condenser microphones (MIC) have been widely used in mechanomyography, together with accelerometers and piezoelectric contact sensors. The aim of the present investigation was to clarify the mechanical variable (acceleration, velocity or displacement) indicated by the signal from a MIC transducer using a mechanical sinusoidal vibration system. In addition, the mechanomyogram (MMG) was recorded simultaneously with a MIC transducer and accelerometer (ACC) during voluntary contractions to confirm the mechanical variable reflected by the actual MMG and to examine the influence of motion artifact on the MMG. To measure the displacement-frequency response, mechanical sinusoidal vibrations of 3 to 300 Hz were applied to the MIC transducer with different sizes of air chambers (5, 10, 15 and 20 mm in diameter and 15, 20 or 25 mm long). The MIC transducer showed a linear relationship between the output amplitude and the vibration displacement, however, its frequency response declined with decreasing diameter and decreasing length of the air chamber. In fact, the cut-off frequency (-3dB) of the MIC transducer with the 5-mm-diameter chamber was 10, 8 and 4 Hz for the length 15, 20 and 25 mm, respectively. The air chamber with at least a diameter of 10 mm and a length of 15 mm is recommended for the MIC transducer. The sensitivity of this MIC transducer arrangement was 92 mV microm(-1) when excited at 100 Hz. During voluntary contraction, the amplitude spectral density function of the MMG from the MIC transducer resembled that of the double integral of the ACC transducer signal. The angle of the MIC transducer was delayed by 180 degrees in relation to the ACC transducer signal. The sensitivity of the MIC transducer was reduced to one-third because of the peculiar volume change of air chamber when the MMG was detected on the surface of the skin. In addition, the MIC transducer was contaminated by a smaller motion artifact than that from the ACC transducer. The maximal peak amplitude of the MIC and ACC transducer signal with the motion artifact was 7.7 and 12.3 times as much as the RMS amplitude of each signal without the motion artifact, respectively. These findings suggest that the MIC transducer acts as a displacement meter in the MMG. The MIC transducer seems to be a possible candidate for recording the MMG during dynamic muscle contractions as well as during sustained contractions.

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Gu, Xuejun

2013-10-15

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstructionmore » to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.« less

Motion Compensation in Extremity Cone-Beam CT Using a Penalized Image Sharpness Criterion

PubMed Central

Sisniega, A.; Stayman, J. W.; Yorkston, J.; Siewerdsen, J. H.; Zbijewski, W.

2017-01-01

Cone-beam CT (CBCT) for musculoskeletal imaging would benefit from a method to reduce the effects of involuntary patient motion. In particular, the continuing improvement in spatial resolution of CBCT may enable tasks such as quantitative assessment of bone microarchitecture (0.1 mm – 0.2 mm detail size), where even subtle, sub-mm motion blur might be detrimental. We propose a purely image based motion compensation method that requires no fiducials, tracking hardware or prior images. A statistical optimization algorithm (CMA-ES) is used to estimate a motion trajectory that optimizes an objective function consisting of an image sharpness criterion augmented by a regularization term that encourages smooth motion trajectories. The objective function is evaluated using a volume of interest (VOI, e.g. a single bone and surrounding area) where the motion can be assumed to be rigid. More complex motions can be addressed by using multiple VOIs. Gradient variance was found to be a suitable sharpness metric for this application. The performance of the compensation algorithm was evaluated in simulated and experimental CBCT data, and in a clinical dataset. Motion-induced artifacts and blurring were significantly reduced across a broad range of motion amplitudes, from 0.5 mm to 10 mm. Structure Similarity Index (SSIM) against a static volume was used in the simulation studies to quantify the performance of the motion compensation. In studies with translational motion, the SSIM improved from 0.86 before compensation to 0.97 after compensation for 0.5 mm motion, from 0.8 to 0.94 for 2 mm motion and from 0.52 to 0.87 for 10 mm motion (~70% increase). Similar reduction of artifacts was observed in a benchtop experiment with controlled translational motion of an anthropomorphic hand phantom, where SSIM (against a reconstruction of a static phantom) improved from 0.3 to 0.8 for 10 mm motion. Application to a clinical dataset of a lower extremity showed dramatic reduction of streaks and improvement in delineation of tissue boundaries and trabecular structures throughout the whole volume. The proposed method will support new applications of extremity CBCT in areas where patient motion may not be sufficiently managed by immobilization, such as imaging under load and quantitative assessment of subchondral bone architecture. PMID:28327471

Metallic artifact mitigation and organ-constrained tissue assignment for Monte Carlo calculations of permanent implant lung brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sutherland, J. G. H.; Miksys, N.; Thomson, R. M., E-mail: rthomson@physics.carleton.ca

2014-01-15

Purpose: To investigate methods of generating accurate patient-specific computational phantoms for the Monte Carlo calculation of lung brachytherapy patient dose distributions. Methods: Four metallic artifact mitigation methods are applied to six lung brachytherapy patient computed tomography (CT) images: simple threshold replacement (STR) identifies high CT values in the vicinity of the seeds and replaces them with estimated true values; fan beam virtual sinogram replaces artifact-affected values in a virtual sinogram and performs a filtered back-projection to generate a corrected image; 3D median filter replaces voxel values that differ from the median value in a region of interest surrounding the voxelmore » and then applies a second filter to reduce noise; and a combination of fan beam virtual sinogram and STR. Computational phantoms are generated from artifact-corrected and uncorrected images using several tissue assignment schemes: both lung-contour constrained and unconstrained global schemes are considered. Voxel mass densities are assigned based on voxel CT number or using the nominal tissue mass densities. Dose distributions are calculated using the EGSnrc user-code BrachyDose for{sup 125}I, {sup 103}Pd, and {sup 131}Cs seeds and are compared directly as well as through dose volume histograms and dose metrics for target volumes surrounding surgical sutures. Results: Metallic artifact mitigation techniques vary in ability to reduce artifacts while preserving tissue detail. Notably, images corrected with the fan beam virtual sinogram have reduced artifacts but residual artifacts near sources remain requiring additional use of STR; the 3D median filter removes artifacts but simultaneously removes detail in lung and bone. Doses vary considerably between computational phantoms with the largest differences arising from artifact-affected voxels assigned to bone in the vicinity of the seeds. Consequently, when metallic artifact reduction and constrained tissue assignment within lung contours are employed in generated phantoms, this erroneous assignment is reduced, generally resulting in higher doses. Lung-constrained tissue assignment also results in increased doses in regions of interest due to a reduction in the erroneous assignment of adipose to voxels within lung contours. Differences in dose metrics calculated for different computational phantoms are sensitive to radionuclide photon spectra with the largest differences for{sup 103}Pd seeds and smallest but still considerable differences for {sup 131}Cs seeds. Conclusions: Despite producing differences in CT images, dose metrics calculated using the STR, fan beam + STR, and 3D median filter techniques produce similar dose metrics. Results suggest that the accuracy of dose distributions for permanent implant lung brachytherapy is improved by applying lung-constrained tissue assignment schemes to metallic artifact corrected images.« less

T1-weighted brain imaging with a 32-channel coil at 3T using TurboFLASH BLADE compared with standard cartesian k-space sampling.

PubMed

Attenberger, Ulrike I; Runge, Val M; Williams, Kenneth D; Stemmer, Alto; Michaely, Henrik J; Schoenberg, Stefan O; Reiser, Maximilian F; Wintersperger, Bernd J

2009-03-01

Motion artifacts often markedly degrade image quality in clinical scans. The BLADE technique offers an alternative k-space sampling scheme reducing the effect of patient related motion on image quality. The purpose of this study is the comparison of imaging artifacts, signal-to-noise (SNR), and contrast-to-noise ratio (CNR) of a new turboFLASH BLADE k-space trajectory with the standard Cartesian k-space sampling for brain imaging, using a 32-channel coil at 3T. The results from 32 patients included after informed consent are reported. This study was performed with a 32-channel head coil on a 3T scanner. Sagittal and axial T1-weighted FLASH sequences (TR/TE 250/2.46 milliseconds, flip angle 70-degree), acquired with Cartesian k-space sampling and T1-weighted turboFLASH sequences (TR/TE/TIsag/TIax 3200/2.77/1144/1056 milliseconds, flip angle 20-degree), using PROPELLER (BLADE) k-space trajectory, were compared. SNR and CNR were evaluated using a paired student t test. The frequency of motion artifacts was assessed in a blinded read. To analyze the differences between both techniques a McNemar test was performed. A P value <0.05 was considered statistically significant. From the blinded read, the overall preference in terms of diagnostic image quality was statistically significant in favor of the BLADE turboFLASH data sets, compared with standard FLASH for both sagittal (P < 0.0001) and axial (P < 0.0001) planes. The frequency of motion artifacts from the scalp was higher for standard FLASH sequences than for BLADE sequences on both axial (47%, P < 0.0003) and sagittal (69%, P < 0.0001) planes. BLADE was preferred in 100% (sagittal plane) and 80% (axial plane) of in-patient data sets and in 68% (sagittal plane) and 73% (axial plane) of out-patient data sets.The BLADE T1 scan did have lower SNRmean (BLADEax 179 +/- 98, Cartesianax 475 +/- 145, BLADEsag 171 +/- 51, and Cartesiansag 697 +/- 129) with P values indicating accordingly a statistically significant difference (Pax <0.0001, Psag < 0.0001), because of the fundamental difference in imaging approach (FLASH vs. turboFLASH). Differences for CNR were also statistically significant, independent of imaging plane (Pax = 0.001, Psag = 0.02). Results demonstrate that turboFLASH BLADE is applicable at 3T with a 32-channel head coil for T1-weighted imaging, with reduced ghost artifacts. This approach offers the first truly clinically applicable T1-weighted BLADE technique for brain imaging at 3T, with consistent excellent image quality.

2D and 3D registration methods for dual-energy contrast-enhanced digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Lau, Kristen C.; Roth, Susan; Maidment, Andrew D. A.

2014-03-01

Contrast-enhanced digital breast tomosynthesis (CE-DBT) uses an iodinated contrast agent to image the threedimensional breast vasculature. The University of Pennsylvania is conducting a CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 postcontrast). A hybrid subtraction scheme is proposed. First, dual-energy (DE) images are obtained by a weighted logarithmic subtraction of the high-energy and low-energy image pairs. Then, post-contrast DE images are subtracted from the pre-contrast DE image. This hybrid temporal subtraction of DE images is performed to analyze iodine uptake, but suffers from motion artifacts. Employing image registration further helps to correct for motion, enhancing the evaluation of vascular kinetics. Registration using ANTS (Advanced Normalization Tools) is performed in an iterative manner. Mutual information optimization first corrects large-scale motions. Normalized cross-correlation optimization then iteratively corrects fine-scale misalignment. Two methods have been evaluated: a 2D method using a slice-by-slice approach, and a 3D method using a volumetric approach to account for out-of-plane breast motion. Our results demonstrate that iterative registration qualitatively improves with each iteration (five iterations total). Motion artifacts near the edge of the breast are corrected effectively and structures within the breast (e.g. blood vessels, surgical clip) are better visualized. Statistical and clinical evaluations of registration accuracy in the CE-DBT images are ongoing.

Magnetic resonance imaging compatible remote catheter navigation system with 3 degrees of freedom.

PubMed

Tavallaei, M A; Lavdas, M K; Gelman, D; Drangova, M

2016-08-01

To facilitate MRI-guided catheterization procedures, we present an MRI-compatible remote catheter navigation system that allows remote navigation of steerable catheters with 3 degrees of freedom. The system consists of a user interface (master), a robot (slave), and an ultrasonic motor control servomechanism. The interventionalist applies conventional motions (axial, radial and plunger manipulations) on an input catheter in the master unit; this user input is measured and used by the servomechanism to control a compact catheter manipulating robot, such that it replicates the interventionalist's input motion on the patient catheter. The performance of the system was evaluated in terms of MRI compatibility (SNR and artifact), feasibility of remote navigation under real-time MRI guidance, and motion replication accuracy. Real-time MRI experiments demonstrated that catheter was successfully navigated remotely to desired target references in all 3 degrees of freedom. The system had an absolute value error of [Formula: see text]1 mm in axial catheter motion replication over 30 mm of travel and [Formula: see text] for radial catheter motion replication over [Formula: see text]. The worst case SNR drop was observed to be [Formula: see text]3 %; the robot did not introduce any artifacts in the MR images. An MRI-compatible compact remote catheter navigation system has been developed that allows remote navigation of steerable catheters with 3 degrees of freedom. The proposed system allows for safe and accurate remote catheter navigation, within conventional closed-bore scanners, without degrading MR image quality.

Motion corrected photoacoustic difference imaging of fluorescent contrast agents

NASA Astrophysics Data System (ADS)

Märk, Julia; Wagener, Asja; Pönick, Sarah; Grötzinger, Carsten; Zhang, Edward; Laufer, Jan

2016-03-01

In fluorophores, such as exogenous dyes and genetically expressed proteins, the excited state lifetime can be modulated using pump-probe excitation at wavelengths corresponding to the absorption and fluorescence spectra. Simultaneous pump-probe pulses induce stimulated emission (SE) which, in turn, modulates the thermalized energy, and hence the photoacoustic (PA) signal amplitude. For time-delayed pulses, by contrast, SE is suppressed. Since this is not observed in endogenous chromophores, the location of the fluorophore can be determined by subtracting images acquired using simultaneous and time-delayed pump-probe excitation. This simple experimental approach exploits a fluorophorespecific contrast mechanism, and has the potential to enable deep-tissue molecular imaging at fluences below the MPE. In this study, some of the challenges to its in vivo implementation are addressed. First, the PA signal amplitude generated in fluorophores in vivo is often much smaller than that in blood. Second, tissue motion can give rise to artifacts that correspond to endogenous chromophores in the difference image. This would not allow the unambiguous detection of fluorophores. A method to suppress motion artifacts based on fast switching between simultaneous and time-delayed pump-probe excitation was developed. This enables the acquisition of PA signals using the two excitation modes with minimal time delay (20 ms), thus minimizing the effects of tissue motion. The feasibility of this method is demonstrated by visualizing a fluorophore (Atto680) in tissue phantoms, which were moved during the image acquisition to mimic tissue motion.

LANDSAT 3 return beam vidicon response artifacts: A report on RBV photographic product characteristics and quality coding system

NASA Technical Reports Server (NTRS)

Clark, B. P.

1981-01-01

Analysis of large volumes of LANDSAT 3 RBV digital data that were converted to photographic form led to the firm identification of several visible artifacts (objects or structures not normally present, but producted by an external agency or action) in the imagery. These artifacts were identified, categorized, and traced directly to specific sensor response characteristics. None of these artifacts is easily removed and all cases remain under active study of possible future enhancement. The seven generic categories of sensor response artifacts identified to date include: (1) shading and stairsteps; (2) corners out of focus; (3) missing reseaus; (4) reseau distortion and data distortion; (5) black vertical line; (6) grain effect; and (7) faceplate contamination. An additional category under study, but not yet determined to be caused by sensor response, is a geometric anomaly. Examples of affected imagery are presented to assist in distinguishing between image content and innate defects caused by the sensor system.

Contrast-enhanced T1-weighted fluid-attenuated inversion-recovery BLADE magnetic resonance imaging of the brain: an alternative to spin-echo technique for detection of brain lesions in the unsedated pediatric patient?

PubMed

Alibek, Sedat; Adamietz, Boris; Cavallaro, Alexander; Stemmer, Alto; Anders, Katharina; Kramer, Manuel; Bautz, Werner; Staatz, Gundula

2008-08-01

We compared contrast-enhanced T1-weighted magnetic resonance (MR) imaging of the brain using different types of data acquisition techniques: periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER, BLADE) imaging versus standard k-space sampling (conventional spin-echo pulse sequence) in the unsedated pediatric patient with focus on artifact reduction, overall image quality, and lesion detectability. Forty-eight pediatric patients (aged 3 months to 18 years) were scanned with a clinical 1.5-T whole body MR scanner. Cross-sectional contrast-enhanced T1-weighted spin-echo sequence was compared to a T1-weighted dark-fluid fluid-attenuated inversion-recovery (FLAIR) BLADE sequence for qualitative and quantitative criteria (image artifacts, image quality, lesion detectability) by two experienced radiologists. Imaging protocols were matched for imaging parameters. Reader agreement was assessed using the exact Bowker test. BLADE images showed significantly less pulsation and motion artifacts than the standard T1-weighted spin-echo sequence scan. BLADE images showed statistically significant lower signal-to-noise ratio but higher contrast-to-noise ratios with superior gray-white matter contrast. All lesions were demonstrated on FLAIR BLADE imaging, and one false-positive lesion was visible in spin-echo sequence images. BLADE MR imaging at 1.5 T is applicable for central nervous system imaging of the unsedated pediatric patient, reduces motion and pulsation artifacts, and minimizes the need for sedation or general anesthesia without loss of relevant diagnostic information.

Eye-motion-corrected optical coherence tomography angiography using Lissajous scanning.

PubMed

Chen, Yiwei; Hong, Young-Joo; Makita, Shuichi; Yasuno, Yoshiaki

2018-03-01

To correct eye motion artifacts in en face optical coherence tomography angiography (OCT-A) images, a Lissajous scanning method with subsequent software-based motion correction is proposed. The standard Lissajous scanning pattern is modified to be compatible with OCT-A and a corresponding motion correction algorithm is designed. The effectiveness of our method was demonstrated by comparing en face OCT-A images with and without motion correction. The method was further validated by comparing motion-corrected images with scanning laser ophthalmoscopy images, and the repeatability of the method was evaluated using a checkerboard image. A motion-corrected en face OCT-A image from a blinking case is presented to demonstrate the ability of the method to deal with eye blinking. Results show that the method can produce accurate motion-free en face OCT-A images of the posterior segment of the eye in vivo .

Real-time out-of-plane artifact subtraction tomosynthesis imaging using prior CT for scanning beam digital x-ray system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Meng, E-mail: mengwu@stanford.edu; Fahrig, Rebecca

2014-11-01

Purpose: The scanning beam digital x-ray system (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real-time tomosynthesis in multiple planes. This system could be used for image guidance during lung nodule biopsy. However, the reconstructed images suffer from strong out-of-plane artifact due to the small tomographic angle of the system. Methods: The authors propose an out-of-plane artifact subtraction tomosynthesis (OPAST) algorithm that utilizes a prior CT volume to augment the run-time image processing. A blur-and-add (BAA) analytical model, derived from the project-to-backproject physical model, permits the generation of tomosynthesis images thatmore » are a good approximation to the shift-and-add (SAA) reconstructed image. A computationally practical algorithm is proposed to simulate images and out-of-plane artifacts from patient-specific prior CT volumes using the BAA model. A 3D image registration algorithm to align the simulated and reconstructed images is described. The accuracy of the BAA analytical model and the OPAST algorithm was evaluated using three lung cancer patients’ CT data. The OPAST and image registration algorithms were also tested with added nonrigid respiratory motions. Results: Image similarity measurements, including the correlation coefficient, mean squared error, and structural similarity index, indicated that the BAA model is very accurate in simulating the SAA images from the prior CT for the SBDX system. The shift-variant effect of the BAA model can be ignored when the shifts between SBDX images and CT volumes are within ±10 mm in the x and y directions. The nodule visibility and depth resolution are improved by subtracting simulated artifacts from the reconstructions. The image registration and OPAST are robust in the presence of added respiratory motions. The dominant artifacts in the subtraction images are caused by the mismatches between the real object and the prior CT volume. Conclusions: Their proposed prior CT-augmented OPAST reconstruction algorithm improves lung nodule visibility and depth resolution for the SBDX system.« less

Use of High Resolution 3D Diffusion Tensor Imaging to Study Brain White Matter Development in Live Neonatal Rats

PubMed Central

Cai, Yu; McMurray, Matthew S.; Oguz, Ipek; Yuan, Hong; Styner, Martin A.; Lin, Weili; Johns, Josephine M.; An, Hongyu

2011-01-01

High resolution diffusion tensor imaging (DTI) can provide important information on brain development, yet it is challenging in live neonatal rats due to the small size of neonatal brain and motion-sensitive nature of DTI. Imaging in live neonatal rats has clear advantages over fixed brain scans, as longitudinal and functional studies would be feasible to understand neuro-developmental abnormalities. In this study, we developed imaging strategies that can be used to obtain high resolution 3D DTI images in live neonatal rats at postnatal day 5 (PND5) and PND14, using only 3 h of imaging acquisition time. An optimized 3D DTI pulse sequence and appropriate animal setup to minimize physiological motion artifacts are the keys to successful high resolution 3D DTI imaging. Thus, a 3D rapid acquisition relaxation enhancement DTI sequence with twin navigator echoes was implemented to accelerate imaging acquisition time and minimize motion artifacts. It has been suggested that neonatal mammals possess a unique ability to tolerate mild-to-moderate hypothermia and hypoxia without long term impact. Thus, we additionally utilized this ability to minimize motion artifacts in magnetic resonance images by carefully suppressing the respiratory rate to around 15/min for PND5 and 30/min for PND14 using mild-to-moderate hypothermia. These imaging strategies have been successfully implemented to study how the effect of cocaine exposure in dams might affect brain development in their rat pups. Image quality resulting from this in vivo DTI study was comparable to ex vivo scans. fractional anisotropy values were also similar between the live and fixed brain scans. The capability of acquiring high quality in vivo DTI imaging offers a valuable opportunity to study many neurological disorders in brain development in an authentic living environment. PMID:22013426

Edge enhancement algorithm for low-dose X-ray fluoroscopic imaging.

PubMed

Lee, Min Seok; Park, Chul Hee; Kang, Moon Gi

2017-12-01

Low-dose X-ray fluoroscopy has continually evolved to reduce radiation risk to patients during clinical diagnosis and surgery. However, the reduction in dose exposure causes quality degradation of the acquired images. In general, an X-ray device has a time-average pre-processor to remove the generated quantum noise. However, this pre-processor causes blurring and artifacts within the moving edge regions, and noise remains in the image. During high-pass filtering (HPF) to enhance edge detail, this noise in the image is amplified. In this study, a 2D edge enhancement algorithm comprising region adaptive HPF with the transient improvement (TI) method, as well as artifacts and noise reduction (ANR), was developed for degraded X-ray fluoroscopic images. The proposed method was applied in a static scene pre-processed by a low-dose X-ray fluoroscopy device. First, the sharpness of the X-ray image was improved using region adaptive HPF with the TI method, which facilitates sharpening of edge details without overshoot problems. Then, an ANR filter that uses an edge directional kernel was developed to remove the artifacts and noise that can occur during sharpening, while preserving edge details. The quantitative and qualitative results obtained by applying the developed method to low-dose X-ray fluoroscopic images and visually and numerically comparing the final images with images improved using conventional edge enhancement techniques indicate that the proposed method outperforms existing edge enhancement methods in terms of objective criteria and subjective visual perception of the actual X-ray fluoroscopic image. The developed edge enhancement algorithm performed well when applied to actual low-dose X-ray fluoroscopic images, not only by improving the sharpness, but also by removing artifacts and noise, including overshoot. Copyright © 2017 Elsevier B.V. All rights reserved.

Constraining earthquake source inversions with GPS data: 1. Resolution-based removal of artifacts

USGS Publications Warehouse

Page, M.T.; Custodio, S.; Archuleta, R.J.; Carlson, J.M.

2009-01-01

We present a resolution analysis of an inversion of GPS data from the 2004 Mw 6.0 Parkfield earthquake. This earthquake was recorded at thirteen 1-Hz GPS receivers, which provides for a truly coseismic data set that can be used to infer the static slip field. We find that the resolution of our inverted slip model is poor at depth and near the edges of the modeled fault plane that are far from GPS receivers. The spatial heterogeneity of the model resolution in the static field inversion leads to artifacts in poorly resolved areas of the fault plane. These artifacts look qualitatively similar to asperities commonly seen in the final slip models of earthquake source inversions, but in this inversion they are caused by a surplus of free parameters. The location of the artifacts depends on the station geometry and the assumed velocity structure. We demonstrate that a nonuniform gridding of model parameters on the fault can remove these artifacts from the inversion. We generate a nonuniform grid with a grid spacing that matches the local resolution length on the fault and show that it outperforms uniform grids, which either generate spurious structure in poorly resolved regions or lose recoverable information in well-resolved areas of the fault. In a synthetic test, the nonuniform grid correctly averages slip in poorly resolved areas of the fault while recovering small-scale structure near the surface. Finally, we present an inversion of the Parkfield GPS data set on the nonuniform grid and analyze the errors in the final model. Copyright 2009 by the American Geophysical Union.

An image-based approach to understanding the physics of MR artifacts.

PubMed

Morelli, John N; Runge, Val M; Ai, Fei; Attenberger, Ulrike; Vu, Lan; Schmeets, Stuart H; Nitz, Wolfgang R; Kirsch, John E

2011-01-01

As clinical magnetic resonance (MR) imaging becomes more versatile and more complex, it is increasingly difficult to develop and maintain a thorough understanding of the physical principles that govern the changing technology. This is particularly true for practicing radiologists, whose primary obligation is to interpret clinical images and not necessarily to understand complex equations describing the underlying physics. Nevertheless, the physics of MR imaging plays an important role in clinical practice because it determines image quality, and suboptimal image quality may hinder accurate diagnosis. This article provides an image-based explanation of the physics underlying common MR imaging artifacts, offering simple solutions for remedying each type of artifact. Solutions that have emerged from recent technologic advances with which radiologists may not yet be familiar are described in detail. Types of artifacts discussed include those resulting from voluntary and involuntary patient motion, magnetic susceptibility, magnetic field inhomogeneities, gradient nonlinearity, standing waves, aliasing, chemical shift, and signal truncation. With an improved awareness and understanding of these artifacts, radiologists will be better able to modify MR imaging protocols so as to optimize clinical image quality, allowing greater confidence in diagnosis. Copyright © RSNA, 2011.

Multiresolution image registration in digital x-ray angiography with intensity variation modeling.

PubMed

Nejati, Mansour; Pourghassem, Hossein

2014-02-01

Digital subtraction angiography (DSA) is a widely used technique for visualization of vessel anatomy in diagnosis and treatment. However, due to unavoidable patient motions, both externally and internally, the subtracted angiography images often suffer from motion artifacts that adversely affect the quality of the medical diagnosis. To cope with this problem and improve the quality of DSA images, registration algorithms are often employed before subtraction. In this paper, a novel elastic registration algorithm for registration of digital X-ray angiography images, particularly for the coronary location, is proposed. This algorithm includes a multiresolution search strategy in which a global transformation is calculated iteratively based on local search in coarse and fine sub-image blocks. The local searches are accomplished in a differential multiscale framework which allows us to capture both large and small scale transformations. The local registration transformation also explicitly accounts for local variations in the image intensities which incorporated into our model as a change of local contrast and brightness. These local transformations are then smoothly interpolated using thin-plate spline interpolation function to obtain the global model. Experimental results with several clinical datasets demonstrate the effectiveness of our algorithm in motion artifact reduction.

Quantifying the effect of disruptions to temporal coherence on the intelligibility of compressed American Sign Language video

NASA Astrophysics Data System (ADS)

Ciaramello, Frank M.; Hemami, Sheila S.

2009-02-01

Communication of American Sign Language (ASL) over mobile phones would be very beneficial to the Deaf community. ASL video encoded to achieve the rates provided by current cellular networks must be heavily compressed and appropriate assessment techniques are required to analyze the intelligibility of the compressed video. As an extension to a purely spatial measure of intelligibility, this paper quantifies the effect of temporal compression artifacts on sign language intelligibility. These artifacts can be the result of motion-compensation errors that distract the observer or frame rate reductions. They reduce the the perception of smooth motion and disrupt the temporal coherence of the video. Motion-compensation errors that affect temporal coherence are identified by measuring the block-level correlation between co-located macroblocks in adjacent frames. The impact of frame rate reductions was quantified through experimental testing. A subjective study was performed in which fluent ASL participants rated the intelligibility of sequences encoded at a range of 5 different frame rates and with 3 different levels of distortion. The subjective data is used to parameterize an objective intelligibility measure which is highly correlated with subjective ratings at multiple frame rates.

New techniques for motion-artifact-free in vivo cardiac microscopy

PubMed Central

Vinegoni, Claudio; Lee, Sungon; Aguirre, Aaron D.; Weissleder, Ralph

2015-01-01

Intravital imaging microscopy (i.e., imaging in live animals at microscopic resolution) has become an indispensable tool for studying the cellular micro-dynamics in cancer, immunology and neurobiology. High spatial and temporal resolution, combined with large penetration depth and multi-reporter visualization capability make fluorescence intravital microscopy compelling for heart imaging. However, tissue motion caused by cardiac contraction and respiration critically limits its use. As a result, in vitro cell preparations or non-contracting explanted heart models are more commonly employed. Unfortunately, these approaches fall short of understanding the more complex host physiology that may be dynamic and occur over longer periods of time. In this review, we report on novel technologies, which have been recently developed by our group and others, aimed at overcoming motion-induced artifacts and capable of providing in vivo subcellular resolution imaging in the beating mouse heart. The methods are based on mechanical stabilization, image processing algorithms, gated/triggered acquisition schemes or a combination of both. We expect that in the immediate future all these methodologies will have considerable applications in expanding our understanding of the cardiac biology, elucidating cardiomyocyte function and interactions within the organism in vivo, and ultimately improving the treatment of cardiac diseases. PMID:26029116

New prospective 4D-CT for mitigating the effects of irregular respiratory motion

NASA Astrophysics Data System (ADS)

Pan, Tinsu; Martin, Rachael M.; Luo, Dershan

2017-08-01

Artifact caused by irregular respiration is a major source of error in 4D-CT imaging. We propose a new prospective 4D-CT to mitigate this source of error without new hardware, software or off-line data-processing on the GE CT scanner. We utilize the cine CT scan in the design of the new prospective 4D-CT. The cine CT scan at each position can be stopped by the operator when an irregular respiration occurs, and resumed when the respiration becomes regular. This process can be repeated at one or multiple scan positions. After the scan, a retrospective reconstruction is initiated on the CT console to reconstruct only the images corresponding to the regular respiratory cycles. The end result is a 4D-CT free of irregular respiration. To prove feasibility, we conducted a phantom and six patient studies. The artifacts associated with the irregular respiratory cycles could be removed from both the phantom and patient studies. A new prospective 4D-CT scanning and processing technique to mitigate the impact of irregular respiration in 4D-CT has been demonstrated. This technique can save radiation dose because the repeat scans are only at the scan positions where an irregular respiration occurs. Current practice is to repeat the scans at all positions. There is no cost to apply this technique because it is applicable on the GE CT scanner without new hardware, software or off-line data-processing.