Improvement in cognitive and psychosocial functioning and self image among adolescent inpatient suicide attempters.

PubMed

Hintikka, Ulla; Marttunen, Mauri; Pelkonen, Mirjami; Laukkanen, Eila; Viinamäki, Heimo; Lehtonen, Johannes

2006-12-29

Psychiatric treatment of suicidal youths is often difficult and non-compliance in treatment is a significant problem. This prospective study compared characteristics and changes in cognitive functioning, self image and psychosocial functioning among 13 to 18 year-old adolescent psychiatric inpatients with suicide attempts (n = 16) and with no suicidality (n = 39) The two-group pre-post test prospective study design included assessments by a psychiatrist, a psychologist and medical staff members as well as self-rated measures. DSM-III-R diagnoses were assigned using the SCID and thereafter transformed to DSM-IV diagnoses. Staff members assessed psychosocial functioning using the Global Assessment Scale (GAS). Cognitive performance was assessed using the Wechsler Adult Intelligence Scale, while the Offer Self-Image Questionnaire (OSIQ) was used to assess the subjects' self-image. ANCOVA with repeated measures was used to test changes from entry to discharge among the suicide attempters and non suicidal patients. Logistic regression modeling was used to assess variables associated with an improvement of 10 points or more in the GAS score. Among suicide attempter patients, psychosocial functioning, cognitive performance and both the psychological self and body-image improved during treatment and their treatment compliance and outcome were as good as that of the non-suicidal patients. Suicidal ideation and hopelessness declined, and psychosocial functioning improved. Changes in verbal cognitive performance were more pronounced among the suicide attempters. Having an improved body-image associated with a higher probability of improvement in psychosocial functioning while higher GAS score at entry was associated with lower probability of functional improvement in both patient groups. These findings illustrate that a multimodal treatment program seems to improve psychosocial functioning and self-image among severely disordered suicidal adolescent inpatients. There were no changes in familial relationships, possibly indicating a need for more intensive family interventions when treating suicidal youths. Multimodal inpatient treatment including an individual therapeutic relationship seems recommendable for severely impaired psychiatric inpatients tailored to the suicidal adolescent's needs.

Blurred image restoration using knife-edge function and optimal window Wiener filtering.

PubMed

Wang, Min; Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

PubMed Central

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

Multifunction Imaging and Spectroscopic Instrument

NASA Technical Reports Server (NTRS)

Mouroulis, Pantazis

2004-01-01

A proposed optoelectronic instrument would perform several different spectroscopic and imaging functions that, heretofore, have been performed by separate instruments. The functions would be reflectance, fluorescence, and Raman spectroscopies; variable-color confocal imaging at two different resolutions; and wide-field color imaging. The instrument was conceived for use in examination of minerals on remote planets. It could also be used on Earth to characterize material specimens. The conceptual design of the instrument emphasizes compactness and economy, to be achieved largely through sharing of components among subsystems that perform different imaging and spectrometric functions. The input optics for the various functions would be mounted in a single optical head. With the exception of a targeting lens, the input optics would all be aimed at the same spot on a specimen, thereby both (1) eliminating the need to reposition the specimen to perform different imaging and/or spectroscopic observations and (2) ensuring that data from such observations can be correlated with respect to known positions on the specimen. The figure schematically depicts the principal components and subsystems of the instrument. The targeting lens would collect light into a multimode optical fiber, which would guide the light through a fiber-selection switch to a reflection/ fluorescence spectrometer. The switch would have four positions, enabling selection of spectrometer input from the targeting lens, from either of one or two multimode optical fibers coming from a reflectance/fluorescence- microspectrometer optical head, or from a dark calibration position (no fiber). The switch would be the only moving part within the instrument.

Endoscopic device for functional imaging of the retina

NASA Astrophysics Data System (ADS)

Barriga, Simon; Lohani, Sweyta; Martell, Bret; Soliz, Peter; Ts'o, Dan

2011-03-01

Non-invasive imaging of retinal function based on the recording of spatially distributed reflectance changes evoked by visual stimuli has to-date been performed primarily using modified commercial fundus cameras. We have constructed a prototype retinal functional imager, using a commercial endoscope (Storz) for the frontend optics, and a low-cost back-end that includes the needed dichroic beam splitter to separate the stimulus path from the imaging path. This device has been tested to demonstrate its performance for the delivery of adequate near infrared (NIR) illumination, intensity of the visual stimulus and reflectance return in the imaging path. The current device was found to be capable of imaging reflectance changes of 0.1%, similar to that observable using the modified commercial fundus camera approach. The visual stimulus (a 505nm spot of 0.5secs) was used with an interrogation illumination of 780nm, and a sequence of imaged captured. At each pixel, the imaged signal was subtracted and normalized by the baseline reflectance, so that the measurement was ΔR/R. The typical retinal activity signal observed had a ΔR/R of 0.3-1.0%. The noise levels were measured when no stimulus was applied and found to vary between +/- 0.05%. Functional imaging has been suggested as a means to provide objective information on retina function that may be a preclinical indicator of ocular diseases, such as age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy. The endoscopic approach promises to yield a significantly more economical retinal functional imaging device that would be clinically important.

A noncoherent optical analog image processor.

PubMed

Swindell, W

1970-11-01

The description of a machine that performs a variety of image processing operations is given, together with a theoretical discussion of its operation. Spatial processing is performed by corrective convolution techniques. Density processing is achieved by means of an electrical transfer function generator included in the video circuit. Examples of images processed for removal of image motion blur, defocus, and atmospheric seeing blur are shown.

Enhancement of brain tumor MR images based on intuitionistic fuzzy sets

NASA Astrophysics Data System (ADS)

Deng, Wankai; Deng, He; Cheng, Lifang

2015-12-01

Brain tumor is one of the most fatal cancers, especially high-grade gliomas are among the most deadly. However, brain tumor MR images usually have the disadvantages of low resolution and contrast when compared with the optical images. Consequently, we present a novel adaptive intuitionistic fuzzy enhancement scheme by combining a nonlinear fuzzy filtering operation with fusion operators, for the enhancement of brain tumor MR images in this paper. The presented scheme consists of the following six steps: Firstly, the image is divided into several sub-images. Secondly, for each sub-image, object and background areas are separated by a simple threshold. Thirdly, respective intuitionistic fuzzy generators of object and background areas are constructed based on the modified restricted equivalence function. Fourthly, different suitable operations are performed on respective membership functions of object and background areas. Fifthly, the membership plane is inversely transformed into the image plane. Finally, an enhanced image is obtained through fusion operators. The comparison and evaluation of enhancement performance demonstrate that the presented scheme is helpful to determine the abnormal functional areas, guide the operation, judge the prognosis, and plan the radiotherapy by enhancing the fine detail of MR images.

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

Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance andmore » diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.« less

A MAP blind image deconvolution algorithm with bandwidth over-constrained

NASA Astrophysics Data System (ADS)

Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong

2018-03-01

We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.

Dual-modality imaging of function and physiology

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce H.; Iwata, Koji; Wong, Kenneth H.; Wu, Max C.; Da Silva, Angela; Tang, Hamilton R.; Barber, William C.; Hwang, Andrew B.; Sakdinawat, Anne E.

2002-04-01

Dual-modality imaging is a technique where computed tomography or magnetic resonance imaging is combined with positron emission tomography or single-photon computed tomography to acquire structural and functional images with an integrated system. The data are acquired during a single procedure with the patient on a table viewed by both detectors to facilitate correlation between the structural and function images. The resulting data can be useful for localization for more specific diagnosis of disease. In addition, the anatomical information can be used to compensate the correlated radionuclide data for physical perturbations such as photon attenuation, scatter radiation, and partial volume errors. Thus, dual-modality imaging provides a priori information that can be used to improve both the visual quality and the quantitative accuracy of the radionuclide images. Dual-modality imaging systems also are being developed for biological research that involves small animals. The small-animal dual-modality systems offer advantages for measurements that currently are performed invasively using autoradiography and tissue sampling. By acquiring the required data noninvasively, dual-modality imaging has the potential to allow serial studies in a single animal, to perform measurements with fewer animals, and to improve the statistical quality of the data.

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) spectrometer design and performance

NASA Technical Reports Server (NTRS)

Macenka, Steven A.; Chrisp, Michael P.

1987-01-01

The development of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been completed at JPL. This paper outlines the functional requirements of the spectrometer optics subsystem, and describes the spectrometer optical design. The optical subsystem performance is shown in terms of spectral modulation transfer functions, radial energy distributions, and system transmission at selected wavelengths for the four spectrometers. An outline of the spectrometer alignment is included.

Imaging quality analysis of multi-channel scanning radiometer

NASA Astrophysics Data System (ADS)

Fan, Hong; Xu, Wujun; Wang, Chengliang

2008-03-01

Multi-channel scanning radiometer, on boarding FY-2 geostationary meteorological satellite, plays a key role in remote sensing because of its wide field of view and continuous multi-spectral images acquirements. It is significant to evaluate image quality after performance parameters of the imaging system are validated. Several methods of evaluating imaging quality are discussed. Of these methods, the most fundamental is the MTF. The MTF of photoelectric scanning remote instrument, in the scanning direction, is the multiplication of optics transfer function (OTF), detector transfer function (DTF) and electronics transfer function (ETF). For image motion compensation, moving speed of scanning mirror should be considered. The optical MTF measurement is performed in both the EAST/WEST and NORTH/SOUTH direction, whose values are used for alignment purposes and are used to determine the general health of the instrument during integration and testing. Imaging systems cannot perfectly reproduce what they see and end up "blurring" the image. Many parts of the imaging system can cause blurring. Among these are the optical elements, the sampling of the detector itself, post-processing, or the earth's atmosphere for systems that image through it. Through theory calculation and actual measurement, it is proved that DTF and ETF are the main factors of system MTF and the imaging quality can satisfy the requirement of instrument design.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

NASA Astrophysics Data System (ADS)

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

PubMed Central

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system. PMID:28106129

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2012-10-01

In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.

Dynamic chest radiography: flat-panel detector (FPD) based functional X-ray imaging.

PubMed

Tanaka, Rie

2016-07-01

Dynamic chest radiography is a flat-panel detector (FPD)-based functional X-ray imaging, which is performed as an additional examination in chest radiography. The large field of view (FOV) of FPDs permits real-time observation of the entire lungs and simultaneous right-and-left evaluation of diaphragm kinetics. Most importantly, dynamic chest radiography provides pulmonary ventilation and circulation findings as slight changes in pixel value even without the use of contrast media; the interpretation is challenging and crucial for a better understanding of pulmonary function. The basic concept was proposed in the 1980s; however, it was not realized until the 2010s because of technical limitations. Dynamic FPDs and advanced digital image processing played a key role for clinical application of dynamic chest radiography. Pulmonary ventilation and circulation can be quantified and visualized for the diagnosis of pulmonary diseases. Dynamic chest radiography can be deployed as a simple and rapid means of functional imaging in both routine and emergency medicine. Here, we focus on the evaluation of pulmonary ventilation and circulation. This review article describes the basic mechanism of imaging findings according to pulmonary/circulation physiology, followed by imaging procedures, analysis method, and diagnostic performance of dynamic chest radiography.

Performance measurement of commercial electronic still picture cameras

NASA Astrophysics Data System (ADS)

Hsu, Wei-Feng; Tseng, Shinn-Yih; Chiang, Hwang-Cheng; Cheng, Jui-His; Liu, Yuan-Te

1998-06-01

Commercial electronic still picture cameras need a low-cost, systematic method for evaluating the performance. In this paper, we present a measurement method to evaluating the dynamic range and sensitivity by constructing the opto- electronic conversion function (OECF), the fixed pattern noise by the peak S/N ratio (PSNR) and the image shading function (ISF), and the spatial resolution by the modulation transfer function (MTF). The evaluation results of individual color components and the luminance signal from a PC camera using SONY interlaced CCD array as the image sensor are then presented.

Application of information theory to the design of line-scan imaging systems

NASA Technical Reports Server (NTRS)

Huck, F. O.; Park, S. K.; Halyo, N.; Stallman, S.

1981-01-01

Information theory is used to formulate a single figure of merit for assessing the performance of line scan imaging systems as a function of their spatial response (point spread function or modulation transfer function), sensitivity, sampling and quantization intervals, and the statistical properties of a random radiance field. Computational results for the information density and efficiency (i.e., the ratio of information density to data density) are intuitively satisfying and compare well with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV systems.

Distorted images of one's own body activates the prefrontal cortex and limbic/paralimbic system in young women: a functional magnetic resonance imaging study.

PubMed

Kurosaki, Mitsuhaya; Shirao, Naoko; Yamashita, Hidehisa; Okamoto, Yasumasa; Yamawaki, Shigeto

2006-02-15

Our aim was to study the gender differences in brain activation upon viewing visual stimuli of distorted images of one's own body. We performed functional magnetic resonance imaging on 11 healthy young men and 11 healthy young women using the "body image tasks" which consisted of fat, real, and thin shapes of the subject's own body. Comparison of the brain activation upon performing the fat-image task versus real-image task showed significant activation of the bilateral prefrontal cortex and left parahippocampal area including the amygdala in the women, and significant activation of the right occipital lobe including the primary and secondary visual cortices in the men. Comparison of brain activation upon performing the thin-image task versus real-image task showed significant activation of the left prefrontal cortex, left limbic area including the cingulate gyrus and paralimbic area including the insula in women, and significant activation of the occipital lobe including the left primary and secondary visual cortices in men. These results suggest that women tend to perceive distorted images of their own bodies by complex cognitive processing of emotion, whereas men tend to perceive distorted images of their own bodies by object visual processing and spatial visual processing.

THz optical design considerations and optimization for medical imaging applications

NASA Astrophysics Data System (ADS)

Sung, Shijun; Garritano, James; Bajwa, Neha; Nowroozi, Bryan; Llombart, Nuria; Grundfest, Warren; Taylor, Zachary D.

2014-09-01

THz imaging system design will play an important role making possible imaging of targets with arbitrary properties and geometries. This study discusses design consideration and imaging performance optimization techniques in THz quasioptical imaging system optics. Analysis of field and polarization distortion by off-axis parabolic (OAP) mirrors in THz imaging optics shows how distortions are carried in a series of mirrors while guiding the THz beam. While distortions of the beam profile by individual mirrors are not significant, these effects are compounded by a series of mirrors in antisymmetric orientation. It is shown that symmetric orientation of the OAP mirror effectively cancels this distortion to recover the original beam profile. Additionally, symmetric orientation can correct for some geometrical off-focusing due to misalignment. We also demonstrate an alternative method to test for overall system optics alignment by investigating the imaging performance of the tilted target plane. Asymmetric signal profile as a function of the target plane's tilt angle indicates when one or more imaging components are misaligned, giving a preferred tilt direction. Such analysis can offer additional insight into often elusive source device misalignment at an integrated system. Imaging plane tilting characteristics are representative of a 3-D modulation transfer function of the imaging system. A symmetric tilted plane is preferred to optimize imaging performance.

GUI for Coordinate Measurement of an Image for the Estimation of Geometric Distortion of an Opto-electronic Display System

NASA Astrophysics Data System (ADS)

Saini, Surender Singh; Sardana, Harish Kumar; Pattnaik, Shyam Sundar

2017-06-01

Conventional image editing software in combination with other techniques are not only difficult to apply to an image but also permits a user to perform some basic functions one at a time. However, image processing algorithms and photogrammetric systems are developed in the recent past for real-time pattern recognition applications. A graphical user interface (GUI) is developed which can perform multiple functions simultaneously for the analysis and estimation of geometric distortion in an image with reference to the corresponding distorted image. The GUI measure, record, and visualize the performance metric of X/Y coordinates of one image over the other. The various keys and icons provided in the utility extracts the coordinates of distortion free reference image and the image with geometric distortion. The error between these two corresponding points gives the measure of distortion and also used to evaluate the correction parameters for image distortion. As the GUI interface minimizes human interference in the process of geometric correction, its execution just requires use of icons and keys provided in the utility; this technique gives swift and accurate results as compared to other conventional methods for the measurement of the X/Y coordinates of an image.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

Tc-NGA imaging in liver transplantation: preliminary clinical experience

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

Woodle, E.S.; Ward, R.E.; Stadalnik, R.C.

1989-03-01

Technetium-99m galactosyl-neoglycoalbumin (Tc-NGA) is a new liver imaging agent that binds to hepatic-binding protein, a hepatocyte-specific membrane receptor. The purpose of this study was to determine the potential of Tc-NGA imaging in clinical liver transplantation. A total of 25 studies were performed in nine patients. Imaging studies performed in the early posttransplant period in patients with good hepatic allograft function revealed diffuse patchiness in tracer distribution, a manifestation of preservation damage. Left lobar infarction was demonstrated within a few hours of ischemic injury. Right posterior segmental infarction was seen in another patient. Comparison of kinetic, clinical, and biochemical data revealedmore » good correlation between hepatic allograft function and Tc-NGA kinetics. Major kinetic alterations were noted during periods of preservation injury, hepatic infarction, and acute rejection. These studies indicate: (1) major alterations in Tc-NGA kinetics occur during preservation injury, hepatic infarction, and acute rejection, and (2) Tc-NGA kinetic data appear to provide an accurate reflection of hepatic allograft function. Tc-NGA imaging has the advantages of being noninvasive and of utilizing standard nuclear medicine instrumentation, including portable imaging devices. In conclusion, Tc-NGA imaging provides a promising noninvasive approach for evaluation of liver function in patients undergoing hepatic transplantation.« less

Attentional performance is correlated with the local regional efficiency of intrinsic brain networks.

PubMed

Xu, Junhai; Yin, Xuntao; Ge, Haitao; Han, Yan; Pang, Zengchang; Tang, Yuchun; Liu, Baolin; Liu, Shuwei

2015-01-01

Attention is a crucial brain function for human beings. Using neuropsychological paradigms and task-based functional brain imaging, previous studies have indicated that widely distributed brain regions are engaged in three distinct attention subsystems: alerting, orienting and executive control (EC). Here, we explored the potential contribution of spontaneous brain activity to attention by examining whether resting-state activity could account for individual differences of the attentional performance in normal individuals. The resting-state functional images and behavioral data from attention network test (ANT) task were collected in 59 healthy subjects. Graph analysis was conducted to obtain the characteristics of functional brain networks and linear regression analyses were used to explore their relationships with behavioral performances of the three attentional components. We found that there was no significant relationship between the attentional performance and the global measures, while the attentional performance was associated with specific local regional efficiency. These regions related to the scores of alerting, orienting and EC largely overlapped with the regions activated in previous task-related functional imaging studies, and were consistent with the intrinsic dorsal and ventral attention networks (DAN/VAN). In addition, the strong associations between the attentional performance and specific regional efficiency suggested that there was a possible relationship between the DAN/VAN and task performances in the ANT. We concluded that the intrinsic activity of the human brain could reflect the processing efficiency of the attention system. Our findings revealed a robust evidence for the functional significance of the efficiently organized intrinsic brain network for highly productive cognitions and the hypothesized role of the DAN/VAN at rest.

The Relationship Between Body Image and Sexual Function in Middle-Aged Women.

PubMed

Afshari, Poorandokht; Houshyar, Zeinab; Javadifar, Nahid; Pourmotahari, Fatemeh; Jorfi, Maryam

2016-11-01

An individual's social and marital function, interpersonal relationships, and quality of life may, sometimes be affected by negative body image. This study is aimed at determining the relationship between body image and sexual function in middle-aged women. In this cross-sectional study, 437 middle-aged women, who were referred to various public healthcare centers in Ahvaz, Iran during 2014-2015, were selected. The Female Sexual Function Index (FSFI) and Body Shape Questionnaire (BSQ) were used for data collection. Chi-square, one-way analysis of variance, Spearman's correlation test, and logistic regression analysis were performed for statistical analysis. Approximately 58% of the participants expressed satisfaction with their body image, 35% were mildly dissatisfied, and 7% were moderately dissatisfied with their body image. Body image had a significant negative relationship with sexual satisfaction and sexual function (p=0.005). Furthermore, there was a significant relationship between body image and sexual desire (p=0.022), pain (p=0.001), sexual arousal (p<0.0005), sexual orgasm (p=0.001), and sexual satisfaction (p<0.0005). As the results indicated, body image is an important aspect of sexual health. In this study, women with a positive body image had higher sexual function valuation, compared to women with a negative body image. Also, body shape satisfaction was a predictor of sexual function.

Quantitative Pulmonary Imaging Using Computed Tomography and Magnetic Resonance Imaging

PubMed Central

Washko, George R.; Parraga, Grace; Coxson, Harvey O.

2011-01-01

Measurements of lung function, including spirometry and body plethesmography, are easy to perform and are the current clinical standard for assessing disease severity. However, these lung functional techniques do not adequately explain the observed variability in clinical manifestations of disease and offer little insight into the relationship of lung structure and function. Lung imaging and the image based assessment of lung disease has matured to the extent that it is common for clinical, epidemiologic, and genetic investigation to have a component dedicated to image analysis. There are several exciting imaging modalities currently being used for the non-invasive study of lung anatomy and function. In this review we will focus on two of them, x-ray computed tomography and magnetic resonance imaging. Following a brief introduction of each method we detail some of the most recent work being done to characterize smoking-related lung disease and the clinical applications of such knowledge. PMID:22142490

Open framework for management and processing of multi-modality and multidimensional imaging data for analysis and modelling muscular function

NASA Astrophysics Data System (ADS)

García Juan, David; Delattre, Bénédicte M. A.; Trombella, Sara; Lynch, Sean; Becker, Matthias; Choi, Hon Fai; Ratib, Osman

2014-03-01

Musculoskeletal disorders (MSD) are becoming a big healthcare economical burden in developed countries with aging population. Classical methods like biopsy or EMG used in clinical practice for muscle assessment are invasive and not accurately sufficient for measurement of impairments of muscular performance. Non-invasive imaging techniques can nowadays provide effective alternatives for static and dynamic assessment of muscle function. In this paper we present work aimed toward the development of a generic data structure for handling n-dimensional metabolic and anatomical data acquired from hybrid PET/MR scanners. Special static and dynamic protocols were developed for assessment of physical and functional images of individual muscles of the lower limb. In an initial stage of the project a manual segmentation of selected muscles was performed on high-resolution 3D static images and subsequently interpolated to full dynamic set of contours from selected 2D dynamic images across different levels of the leg. This results in a full set of 4D data of lower limb muscles at rest and during exercise. These data can further be extended to a 5D data by adding metabolic data obtained from PET images. Our data structure and corresponding image processing extension allows for better evaluation of large volumes of multidimensional imaging data that are acquired and processed to generate dynamic models of the moving lower limb and its muscular function.

Structural and functional correlates for language efficiency in auditory word processing.

PubMed

Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.

Structural and functional correlates for language efficiency in auditory word processing

PubMed Central

Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503

Architecture for a PACS primary diagnosis workstation

NASA Astrophysics Data System (ADS)

Shastri, Kaushal; Moran, Byron

1990-08-01

A major factor in determining the overall utility of a medical Picture Archiving and Communications (PACS) system is the functionality of the diagnostic workstation. Meyer-Ebrecht and Wendler [1] have proposed a modular picture computer architecture with high throughput and Perry et.al [2] have defined performance requirements for radiology workstations. In order to be clinically useful, a primary diagnosis workstation must not only provide functions of current viewing systems (e.g. mechanical alternators [3,4]) such as acceptable image quality, simultaneous viewing of multiple images, and rapid switching of image banks; but must also provide a diagnostic advantage over the current systems. This includes window-level functions on any image, simultaneous display of multi-modality images, rapid image manipulation, image processing, dynamic image display (cine), electronic image archival, hardcopy generation, image acquisition, network support, and an easy user interface. Implementation of such a workstation requires an underlying hardware architecture which provides high speed image transfer channels, local storage facilities, and image processing functions. This paper describes the hardware architecture of the Siemens Diagnostic Reporting Console (DRC) which meets these requirements.

Functional Magnetic Resonance Imaging Correlates of First-Episode Psychoses during Attentional and Memory Task Performance.

PubMed

Del Casale, Antonio; Kotzalidis, Georgios D; Rapinesi, Chiara; Sorice, Serena; Girardi, Nicoletta; Ferracuti, Stefano; Girardi, Paolo

2016-01-01

The nature of the alteration of the response to cognitive tasks in first-episode psychosis (FEP) still awaits clarification. We used activation likelihood estimation, an increasingly used method in evaluating normal and pathological brain function, to identify activation changes in functional magnetic resonance imaging (fMRI) studies of FEP during attentional and memory tasks. We included 11 peer-reviewed fMRI studies assessing FEP patients versus healthy controls (HCs) during performance of attentional and memory tasks. Our database comprised 290 patients with FEP, matched with 316 HCs. Between-group analyses showed that HCs, compared to FEP patients, exhibited hyperactivation of the right middle frontal gyrus (Brodmann area, BA, 9), right inferior parietal lobule (BA 40), and right insula (BA 13) during attentional task performances and hyperactivation of the left insula (BA 13) during memory task performances. Right frontal, parietal, and insular dysfunction during attentional task performance and left insular dysfunction during memory task performance are significant neural functional FEP correlates. © 2016 S. Karger AG, Basel.

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Gender differences in the content of cognitive distraction during sex.

PubMed

Meana, Marta; Nunnink, Sarah E

2006-02-01

This study compared 220 college men and 237 college women on two types of self-reported cognitive distraction during sex, performance- and appearance-based. Affect, psychological distress, sexual knowledge, attitudes, fantasies, experiences, body image, satisfaction, and sexual function were assessed with the Derogatis Sexual Functioning Inventory and the Sexual History Form to determine associations with distraction. Between-gender analyses revealed that women reported higher levels of overall and appearance-based distraction than did men, but similar levels of performance-based distraction. Within-gender analyses revealed that women reported as much of one type of distraction as the other, while men reported more performance- than appearance-based distraction. In women, appearance-based distraction was predicted by negative body image, psychological distress, and not being in a relationship, while performance-based distraction was predicted by negative body image, psychological distress, and sexual dissatisfaction. In men, appearance-based distraction was predicted by negative body image, sexual dissatisfaction and not being in a relationship, while performance-based distraction was predicted by negative body image and sexual dissatisfaction. Investigating the content of cognitive distraction may be useful in understanding gender differences in sexual experience and in refining cognitive components of sex therapy.

Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

PubMed

Sim, K S; Lim, M S; Yeap, Z X

2016-07-01

A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Point spread function engineering for iris recognition system design.

PubMed

Ashok, Amit; Neifeld, Mark A

2010-04-01

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

Aberrant Functional Activation in School Age Children At-Risk for Mathematical Disability: A Functional Imaging Study of Simple Arithmetic Skill

ERIC Educational Resources Information Center

Davis, Nicole; Cannistraci, Christopher J.; Rogers, Baxter P.; Gatenby, J. Christopher; Fuchs, Lynn S.; Anderson, Adam W.; Gore, John C.

2009-01-01

We used functional magnetic resonance imaging (fMRI) to explore the patterns of brain activation associated with different levels of performance in exact and approximate calculation tasks in well-defined cohorts of children with mathematical calculation difficulties (MD) and typically developing controls. Both groups of children activated the same…

Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy.

PubMed

Chang, Yu-Hsuan A; Kemmotsu, Nobuko; Leyden, Kelly M; Kucukboyaci, N Erkut; Iragui, Vicente J; Tecoma, Evelyn S; Kansal, Leena; Norman, Marc A; Compton, Rachelle; Ehrlich, Tobin J; Uttarwar, Vedang S; Reyes, Anny; Paul, Brianna M; McDonald, Carrie R

2017-07-01

This study explored the relationships among multimodal imaging, clinical features, and language impairment in patients with left temporal lobe epilepsy (LTLE). Fourteen patients with LTLE and 26 controls underwent structural MRI, functional MRI, diffusion tensor imaging, and neuropsychological language tasks. Laterality indices were calculated for each imaging modality and a principal component (PC) was derived from language measures. Correlations were performed among imaging measures, as well as to the language PC. In controls, better language performance was associated with stronger left-lateralized temporo-parietal and temporo-occipital activations. In LTLE, better language performance was associated with stronger right-lateralized inferior frontal, temporo-parietal, and temporo-occipital activations. These right-lateralized activations in LTLE were associated with right-lateralized arcuate fasciculus fractional anisotropy. These data suggest that interhemispheric language reorganization in LTLE is associated with alterations to perisylvian white matter. These concurrent structural and functional shifts from left to right may help to mitigate language impairment in LTLE. Copyright © 2017 Elsevier Inc. All rights reserved.

Modulation transfer function cascade model for a sampled IR imaging system.

PubMed

de Luca, L; Cardone, G

1991-05-01

The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

Single-shot spiral imaging at 7 T.

PubMed

Engel, Maria; Kasper, Lars; Barmet, Christoph; Schmid, Thomas; Vionnet, Laetitia; Wilm, Bertram; Pruessmann, Klaas P

2018-03-25

The purpose of this work is to explore the feasibility and performance of single-shot spiral MRI at 7 T, using an expanded signal model for reconstruction. Gradient-echo brain imaging is performed on a 7 T system using high-resolution single-shot spiral readouts and half-shot spirals that perform dual-image acquisition after a single excitation. Image reconstruction is based on an expanded signal model including the encoding effects of coil sensitivity, static off-resonance, and magnetic field dynamics. The latter are recorded concurrently with image acquisition, using NMR field probes. The resulting image resolution is assessed by point spread function analysis. Single-shot spiral imaging is achieved at a nominal resolution of 0.8 mm, using spiral-out readouts of 53-ms duration. High depiction fidelity is achieved without conspicuous blurring or distortion. Effective resolutions are assessed as 0.8, 0.94, and 0.98 mm in CSF, gray matter and white matter, respectively. High image quality is also achieved with half-shot acquisition yielding image pairs at 1.5-mm resolution. Use of an expanded signal model enables single-shot spiral imaging at 7 T with unprecedented image quality. Single-shot and half-shot spiral readouts deploy the sensitivity benefit of high field for rapid high-resolution imaging, particularly for functional MRI and arterial spin labeling. © 2018 International Society for Magnetic Resonance in Medicine.

Neural mechanisms of working memory in ecstasy (MDMA) users who continue or discontinue ecstasy and amphetamine use: evidence from an 18-month longitudinal functional magnetic resonance imaging study.

PubMed

Daumann, Jörg; Fischermann, Thomas; Heekeren, Karsten; Thron, Armin; Gouzoulis-Mayfrank, Euphrosyne

2004-09-01

Working memory processing in ecstasy (3,4-methylenedioxymethamphetamine) users is associated with neural alterations as measured by functional magnetic resonance imaging. Here, we examined whether cortical activation patterns change after prolonged periods of continued use or abstinence from ecstasy and amphetamine. We used an n-back task and functional magnetic resonance imaging in 17 ecstasy users at baseline (t(1)) and after 18 months (t(2)). Based on the reported drug use at t(2) we separated subjects with continued ecstasy and amphetamine use from subjects reporting abstinence during the follow-up period (n = 9 and n = 8, respectively). At baseline both groups had similar task performance and similar cortical activation patterns. Task performance remained unchanged in both groups. Furthermore, there were no detectable functional magnetic resonance imaging signal changes from t(1) to t(2) in the follow-up abstinent group. However, the continuing users showed a dose-dependent increased parietal activation for the 2-back task after the follow-up period. Our data suggest that ecstasy use, particularly in high doses, is associated with greater parietal activation during working memory performance. An altered activation pattern might appear before changes in cognitive performance become apparent and, hence, may reflect an early stage of neuronal injury from the neurotoxic drug ecstasy.

Neural Correlates of Symptom Dimensions in Pediatric Obsessive-Compulsive Disorder: A Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Gilbert, Andrew R.; Akkal, Dalila; Almeida, Jorge R. C.; Mataix-Cols, David; Kalas, Catherine; Devlin, Bernie; Birmaher, Boris; Phillips, Mary L.

2009-01-01

The use of functional magnetic resonance imaging on a group of pediatric subjects with obsessive compulsive disorder reveals that this group has reduced activity in neural regions underlying emotional processing, cognitive processing, and motor performance as compared to control subjects.

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

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

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Initial evaluation of discrete orthogonal basis reconstruction of ECT images

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

Moody, E.B.; Donohue, K.D.

1996-12-31

Discrete orthogonal basis restoration (DOBR) is a linear, non-iterative, and robust method for solving inverse problems for systems characterized by shift-variant transfer functions. This simulation study evaluates the feasibility of using DOBR for reconstructing emission computed tomographic (ECT) images. The imaging system model uses typical SPECT parameters and incorporates the effects of attenuation, spatially-variant PSF, and Poisson noise in the projection process. Sample reconstructions and statistical error analyses for a class of digital phantoms compare the DOBR performance for Hartley and Walsh basis functions. Test results confirm that DOBR with either basis set produces images with good statistical properties. Nomore » problems were encountered with reconstruction instability. The flexibility of the DOBR method and its consistent performance warrants further investigation of DOBR as a means of ECT image reconstruction.« less

Edge Probability and Pixel Relativity-Based Speckle Reducing Anisotropic Diffusion.

PubMed

Mishra, Deepak; Chaudhury, Santanu; Sarkar, Mukul; Soin, Arvinder Singh; Sharma, Vivek

2018-02-01

Anisotropic diffusion filters are one of the best choices for speckle reduction in the ultrasound images. These filters control the diffusion flux flow using local image statistics and provide the desired speckle suppression. However, inefficient use of edge characteristics results in either oversmooth image or an image containing misinterpreted spurious edges. As a result, the diagnostic quality of the images becomes a concern. To alleviate such problems, a novel anisotropic diffusion-based speckle reducing filter is proposed in this paper. A probability density function of the edges along with pixel relativity information is used to control the diffusion flux flow. The probability density function helps in removing the spurious edges and the pixel relativity reduces the oversmoothing effects. Furthermore, the filtering is performed in superpixel domain to reduce the execution time, wherein a minimum of 15% of the total number of image pixels can be used. For performance evaluation, 31 frames of three synthetic images and 40 real ultrasound images are used. In most of the experiments, the proposed filter shows a better performance as compared to the state-of-the-art filters in terms of the speckle region's signal-to-noise ratio and mean square error. It also shows a comparative performance for figure of merit and structural similarity measure index. Furthermore, in the subjective evaluation, performed by the expert radiologists, the proposed filter's outputs are preferred for the improved contrast and sharpness of the object boundaries. Hence, the proposed filtering framework is suitable to reduce the unwanted speckle and improve the quality of the ultrasound images.

Experimental Investigation of the Performance of Image Registration and De-aliasing Algorithms

DTIC Science & Technology

2009-09-01

spread function In the literature these types of algorithms are sometimes hcluded under the broad umbrella of superresolution . However, in the current...We use one of these patterns to visually demonstrate successful de-aliasing 15. SUBJECT TERMS Image de-aliasing Superresolution Microscanning Image...undersampled point spread function. In the literature these types of algorithms are sometimes included under the broad umbrella of superresolution . However, in

Resting-state synchrony between the retrosplenial cortex and anterior medial cortical structures relates to memory complaints in subjective cognitive impairment.

PubMed

Yasuno, Fumihiko; Kazui, Hiroaki; Yamamoto, Akihide; Morita, Naomi; Kajimoto, Katsufumi; Ihara, Masafumi; Taguchi, Akihiko; Matsuoka, Kiwamu; Kosaka, Jun; Tanaka, Toshihisa; Kudo, Takashi; Takeda, Masatoshi; Nagatsuka, Kazuyuki; Iida, Hidehiro; Kishimoto, Toshifumi

2015-06-01

Subjective cognitive impairment (SCI) is a clinical state characterized by subjective cognitive deficits without cognitive impairment. To test the hypothesis that this state might involve dysfunction of self-referential processing mediated by cortical midline structures, we investigated abnormalities of functional connectivity in these structures in individuals with SCI using resting-state functional magnetic resonance imaging. We performed functional connectivity analysis for 23 individuals with SCI and 30 individuals without SCI. To reveal the pathophysiological basis of the functional connectivity change, we performed magnetic resonance-diffusion tensor imaging. Positron emission tomography-amyloid imaging was conducted in 13 SCI and 15 nonSCI subjects. Individuals with SCI showed reduced functional connectivity in cortical midline structures. Reduction in white matter connections was related to reduced functional connectivity, but we found no amyloid deposition in individuals with SCI. The results do not necessarily contradict the possibility that SCI indicates initial cognitive decrements, but imply that reduced functional connectivity in cortical midline structures contributes to overestimation of the experience of forgetfulness. Copyright © 2015 Elsevier Inc. All rights reserved.

MO-FG-202-04: Gantry-Resolved Linac QA for VMAT: A Comprehensive and Efficient System Using An Electronic Portal Imaging Device

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

Zwan, B J; University of Newcastle, Newcastle, NSW; Barnes, M

2016-06-15

Purpose: To automate gantry-resolved linear accelerator (linac) quality assurance (QA) for volumetric modulated arc therapy (VMAT) using an electronic portal imaging device (EPID). Methods: A QA system for VMAT was developed that uses an EPID, frame-grabber assembly and in-house developed image processing software. The system relies solely on the analysis of EPID image frames acquired without the presence of a phantom. Images were acquired at 8.41 frames per second using a frame grabber and ancillary acquisition computer. Each image frame was tagged with a gantry angle from the linac’s on-board gantry angle encoder. Arc-dynamic QA plans were designed to assessmore » the performance of each individual linac component during VMAT. By analysing each image frame acquired during the QA deliveries the following eight machine performance characteristics were measured as a function of gantry angle: MLC positional accuracy, MLC speed constancy, MLC acceleration constancy, MLC-gantry synchronisation, beam profile constancy, dose rate constancy, gantry speed constancy, dose-gantry angle synchronisation and mechanical sag. All tests were performed on a Varian iX linear accelerator equipped with a 120 leaf Millennium MLC and an aS1000 EPID (Varian Medical Systems, Palo Alto, CA, USA). Results: Machine performance parameters were measured as a function of gantry angle using EPID imaging and compared to machine log files and the treatment plan. Data acquisition is currently underway at 3 centres, incorporating 7 treatment units, at 2 weekly measurement intervals. Conclusion: The proposed system can be applied for streamlined linac QA and commissioning for VMAT. The set of test plans developed can be used to assess the performance of each individual components of the treatment machine during VMAT deliveries as a function of gantry angle. The methodology does not require the setup of any additional phantom or measurement equipment and the analysis is fully automated to allow for regular routine testing.« less

A Computational Observer For Performing Contrast-Detail Analysis Of Ultrasound Images

NASA Astrophysics Data System (ADS)

Lopez, H.; Loew, M. H.

1988-06-01

Contrast-Detail (C/D) analysis allows the quantitative determination of an imaging system's ability to display a range of varying-size targets as a function of contrast. Using this technique, a contrast-detail plot is obtained which can, in theory, be used to compare image quality from one imaging system to another. The C/D plot, however, is usually obtained by using data from human observer readings. We have shown earlier(7) that the performance of human observers in the task of threshold detection of simulated lesions embedded in random ultrasound noise is highly inaccurate and non-reproducible for untrained observers. We present an objective, computational method for the determination of the C/D curve for ultrasound images. This method utilizes digital images of the C/D phantom developed at CDRH, and lesion-detection algorithms that simulate the Bayesian approach using the likelihood function for an ideal observer. We present the results of this method, and discuss the relationship to the human observer and to the comparability of image quality between systems.

A Practical and Portable Solids-State Electronic Terahertz Imaging System

PubMed Central

Smart, Ken; Du, Jia; Li, Li; Wang, David; Leslie, Keith; Ji, Fan; Li, Xiang Dong; Zeng, Da Zhang

2016-01-01

A practical compact solid-state terahertz imaging system is presented. Various beam guiding architectures were explored and hardware performance assessed to improve its compactness, robustness, multi-functionality and simplicity of operation. The system performance in terms of image resolution, signal-to-noise ratio, the electronic signal modulation versus optical chopper, is evaluated and discussed. The system can be conveniently switched between transmission and reflection mode according to the application. A range of imaging application scenarios was explored and images of high visual quality were obtained in both transmission and reflection mode. PMID:27110791

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

Sensor image prediction techniques

NASA Astrophysics Data System (ADS)

Stenger, A. J.; Stone, W. R.; Berry, L.; Murray, T. J.

1981-02-01

The preparation of prediction imagery is a complex, costly, and time consuming process. Image prediction systems which produce a detailed replica of the image area require the extensive Defense Mapping Agency data base. The purpose of this study was to analyze the use of image predictions in order to determine whether a reduced set of more compact image features contains enough information to produce acceptable navigator performance. A job analysis of the navigator's mission tasks was performed. It showed that the cognitive and perceptual tasks he performs during navigation are identical to those performed for the targeting mission function. In addition, the results of the analysis of his performance when using a particular sensor can be extended to the analysis of this mission tasks using any sensor. An experimental approach was used to determine the relationship between navigator performance and the type of amount of information in the prediction image. A number of subjects were given image predictions containing varying levels of scene detail and different image features, and then asked to identify the predicted targets in corresponding dynamic flight sequences over scenes of cultural, terrain, and mixed (both cultural and terrain) content.

Image classification at low light levels

NASA Astrophysics Data System (ADS)

Wernick, Miles N.; Morris, G. Michael

1986-12-01

An imaging photon-counting detector is used to achieve automatic sorting of two image classes. The classification decision is formed on the basis of the cross correlation between a photon-limited input image and a reference function stored in computer memory. Expressions for the statistical parameters of the low-light-level correlation signal are given and are verified experimentally. To obtain a correlation-based system for two-class sorting, it is necessary to construct a reference function that produces useful information for class discrimination. An expression for such a reference function is derived using maximum-likelihood decision theory. Theoretically predicted results are used to compare on the basis of performance the maximum-likelihood reference function with Fukunaga-Koontz basis vectors and average filters. For each method, good class discrimination is found to result in milliseconds from a sparse sampling of the input image.

pyBSM: A Python package for modeling imaging systems

NASA Astrophysics Data System (ADS)

LeMaster, Daniel A.; Eismann, Michael T.

2017-05-01

There are components that are common to all electro-optical and infrared imaging system performance models. The purpose of the Python Based Sensor Model (pyBSM) is to provide open source access to these functions for other researchers to build upon. Specifically, pyBSM implements much of the capability found in the ERIM Image Based Sensor Model (IBSM) V2.0 along with some improvements. The paper also includes two use-case examples. First, performance of an airborne imaging system is modeled using the General Image Quality Equation (GIQE). The results are then decomposed into factors affecting noise and resolution. Second, pyBSM is paired with openCV to evaluate performance of an algorithm used to detect objects in an image.

Modeling and performance assessment in QinetiQ of EO and IR airborne reconnaissance systems

NASA Astrophysics Data System (ADS)

Williams, John W.; Potter, Gary E.

2002-11-01

QinetiQ are the technical authority responsible for specifying the performance requirements for the procurement of airborne reconnaissance systems, on behalf of the UK MoD. They are also responsible for acceptance of delivered systems, overseeing and verifying the installed system performance as predicted and then assessed by the contractor. Measures of functional capability are central to these activities. The conduct of these activities utilises the broad technical insight and wide range of analysis tools and models available within QinetiQ. This paper focuses on the tools, methods and models that are applicable to systems based on EO and IR sensors. The tools, methods and models are described, and representative output for systems that QinetiQ has been responsible for is presented. The principle capability applicable to EO and IR airborne reconnaissance systems is the STAR (Simulation Tools for Airborne Reconnaissance) suite of models. STAR generates predictions of performance measures such as GRD (Ground Resolved Distance) and GIQE (General Image Quality) NIIRS (National Imagery Interpretation Rating Scales). It also generates images representing sensor output, using the scene generation software CAMEO-SIM and the imaging sensor model EMERALD. The simulated image 'quality' is fully correlated with the predicted non-imaging performance measures. STAR also generates image and table data that is compliant with STANAG 7023, which may be used to test ground station functionality.

Characterizing populations and searching for diagnostics via elastic registration of MRI images

NASA Astrophysics Data System (ADS)

Pettey, David; Gee, James C.

2001-07-01

Given image data from two distinct populations and a family of functions, we find the scalar discriminant function which best discriminates between the populations. The goals are two-fold: first, to construct a discriminant function which can accurately and reliably classify subjects via the image data. Second, the best discriminant allows us to see which features in the images distinguish between the populations; these features can guide us to finding characteristic differences between the two groups even if these differences are not sufficient to perform classification. We apply our method to mid-sagittal MRI sections of the corpus callosum from 34 males and 52 females. While we are not certain of the ability of the derived discriminant function to perform sex classification, we find that regions in the anterior of the corpus callosum do appear to be more important for the discriminant function than other regions. This indicates there may be significant differences in the relative size of the splenium in males and females, as has been reported elsewhere. More notably, we applied previous methods which support this view on our larger data set, but found that these methods no longer show statistically significant differences between the male and female splenium.

Design and performance evaluation of the imaging payload for a remote sensing satellite

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Abbasi-Moghadam, Dariush

2012-11-01

In this paper an analysis method and corresponding analytical tools for design of the experimental imaging payload (IMPL) of a remote sensing satellite (SINA-1) are presented. We begin with top-level customer system performance requirements and constraints and derive the critical system and component parameters, then analyze imaging payload performance until a preliminary design that meets customer requirements. We consider system parameters and components composing the image chain for imaging payload system which includes aperture, focal length, field of view, image plane dimensions, pixel dimensions, detection quantum efficiency, and optical filter requirements. The performance analysis is accomplished by calculating the imaging payload's SNR (signal-to-noise ratio), and imaging resolution. The noise components include photon noise due to signal scene and atmospheric background, cold shield, out-of-band optical filter leakage and electronic noise. System resolution is simulated through cascaded modulation transfer functions (MTFs) and includes effects due to optics, image sampling, and system motion. Calculations results for the SINA-1 satellite are also presented.

Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging

PubMed Central

Khan, Bilal; Chand, Pankaj; Alexandrakis, George

2011-01-01

Functional near infrared (fNIR) imaging was used to identify spatiotemporal relations between spatially distinct cortical regions activated during various hand and arm motion protocols. Imaging was performed over a field of view (FOV, 12 x 8.4 cm) including the secondary motor, primary sensorimotor, and the posterior parietal cortices over a single brain hemisphere. This is a more extended FOV than typically used in current fNIR studies. Three subjects performed four motor tasks that induced activation over this extended FOV. The tasks included card flipping (pronation and supination) that, to our knowledge, has not been performed in previous functional magnetic resonance imaging (fMRI) or fNIR studies. An earlier rise and a longer duration of the hemodynamic activation response were found in tasks requiring increased physical or mental effort. Additionally, analysis of activation images by cluster component analysis (CCA) demonstrated that cortical regions can be grouped into clusters, which can be adjacent or distant from each other, that have similar temporal activation patterns depending on whether the performed motor task is guided by visual or tactile feedback. These analyses highlight the future potential of fNIR imaging to tackle clinically relevant questions regarding the spatiotemporal relations between different sensorimotor cortex regions, e.g. ones involved in the rehabilitation response to motor impairments. PMID:22162826

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

PubMed Central

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2012-01-01

This research examines whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In three experiments, participants learned four-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the maps from imagined perspectives that were either aligned or misaligned with the maps as represented in working memory. Results from Experiments 1 and 2 revealed a highly similar pattern of latencies and errors between visual and haptic conditions. These findings extend the well known alignment biases for visual map learning to haptic map learning, provide further evidence of haptic updating, and most importantly, show that learning from the two modalities yields very similar performance across all conditions. Experiment 3 found the same encoding biases and updating performance with blind individuals, demonstrating that functional equivalence cannot be due to visual recoding and is consistent with an amodal hypothesis of spatial images. PMID:21299331

Towards a clinical implementation of μOCT instrument for in vivo imaging of human airways

NASA Astrophysics Data System (ADS)

Leung, Hui Min; Cui, Dongyao; Ford, Timothy N.; Hyun, Daryl; Dong, Jing; Yin, Biwei; Birket, Susan E.; Solomon, George M.; Liu, Linbo; Rowe, Steven M.; Tearney, Guillermo J.

2017-03-01

High resolution micro-optical coherence tomography (µOCT) technology has been demonstrated to be useful for imaging respiratory epithelial functional microanatomy relevant to the study of pulmonary diseases such as cystic fibrosis and COPD. We previously reported the use of a benchtop μOCT imaging technology to image several relevant respiratory epithelial functional microanatomy at 40 fps and at lateral and axial resolutions of 2 and 1.3μm, respectively. We now present the development of a portable μOCT imaging system with comparable optical and imaging performance, which enables the μOCT technology to be translated to the clinic for in vivo imaging of human airways.

Large Field of View, Modular, Stabilized, Adaptive-Optics-Based Scanning Laser Ophthalmoscope

PubMed Central

Burns, Stephen A.; Tumbar, Remy; Elsner, Ann E.; Ferguson, Daniel; Hammer, Daniel X.

2007-01-01

We describe the design and performance of an adaptive optics retinal imager that is optimized for use during dynamic correction for eye movements. The system incorporates a retinal tracker and stabilizer, a wide field line scan Scanning Laser Ophthalmocsope (SLO), and a high resolution MEMS based adaptive optics SLO. The detection system incorporates selection and positioning of confocal apertures, allowing measurement of images arising from different portions of the double pass retinal point spread function (psf). System performance was excellent. The adaptive optics increased the brightness and contrast for small confocal apertures by more than 2x, and decreased the brightness of images obtained with displaced apertures, confirming the ability of the adaptive optics system to improve the pointspread function. The retinal image was stabilized to within 18 microns 90% of the time. Stabilization was sufficient for cross-correlation techniques to automatically align the images. PMID:17429477

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

Complex-valued multistate associative memory with nonlinear multilevel functions for gray-level image reconstruction.

PubMed

Tanaka, Gouhei; Aihara, Kazuyuki

2009-09-01

A widely used complex-valued activation function for complex-valued multistate Hopfield networks is revealed to be essentially based on a multilevel step function. By replacing the multilevel step function with other multilevel characteristics, we present two alternative complex-valued activation functions. One is based on a multilevel sigmoid function, while the other on a characteristic of a multistate bifurcating neuron. Numerical experiments show that both modifications to the complex-valued activation function bring about improvements in network performance for a multistate associative memory. The advantage of the proposed networks over the complex-valued Hopfield networks with the multilevel step function is more outstanding when a complex-valued neuron represents a larger number of multivalued states. Further, the performance of the proposed networks in reconstructing noisy 256 gray-level images is demonstrated in comparison with other recent associative memories to clarify their advantages and disadvantages.

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

Task-Driven Tube Current Modulation and Regularization Design in Computed Tomography with Penalized-Likelihood Reconstruction.

PubMed

Gang, G J; Siewerdsen, J H; Stayman, J W

2016-02-01

This work applies task-driven optimization to design CT tube current modulation and directional regularization in penalized-likelihood (PL) reconstruction. The relative performance of modulation schemes commonly adopted for filtered-backprojection (FBP) reconstruction were also evaluated for PL in comparison. We adopt a task-driven imaging framework that utilizes a patient-specific anatomical model and information of the imaging task to optimize imaging performance in terms of detectability index ( d' ). This framework leverages a theoretical model based on implicit function theorem and Fourier approximations to predict local spatial resolution and noise characteristics of PL reconstruction as a function of the imaging parameters to be optimized. Tube current modulation was parameterized as a linear combination of Gaussian basis functions, and regularization was based on the design of (directional) pairwise penalty weights for the 8 in-plane neighboring voxels. Detectability was optimized using a covariance matrix adaptation evolutionary strategy algorithm. Task-driven designs were compared to conventional tube current modulation strategies for a Gaussian detection task in an abdomen phantom. The task-driven design yielded the best performance, improving d' by ~20% over an unmodulated acquisition. Contrary to FBP, PL reconstruction using automatic exposure control and modulation based on minimum variance (in FBP) performed worse than the unmodulated case, decreasing d' by 16% and 9%, respectively. This work shows that conventional tube current modulation schemes suitable for FBP can be suboptimal for PL reconstruction. Thus, the proposed task-driven optimization provides additional opportunities for improved imaging performance and dose reduction beyond that achievable with conventional acquisition and reconstruction.

Digital Imaging

NASA Technical Reports Server (NTRS)

1986-01-01

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images

PubMed Central

Dai, Weiying; Soman, Salil; Hackney, David B.; Wong, Eric T.; Robson, Philip M.; Alsop, David C.

2017-01-01

Functional imaging provides hemodynamic and metabolic information and is increasingly being incorporated into clinical diagnostic and research studies. Typically functional images have reduced signal-to-noise ratio and spatial resolution compared to other non-functional cross sectional images obtained as part of a routine clinical protocol. We hypothesized that enhancing visualization and interpretation of functional images with anatomic information could provide preferable quality and superior diagnostic value. In this work, we implemented five methods (frequency addition, frequency multiplication, wavelet transform, non-subsampled contourlet transform and intensity-hue-saturation) and a newly proposed ShArpening by Local Similarity with Anatomic images (SALSA) method to enhance the visualization of functional images, while preserving the original functional contrast and quantitative signal intensity characteristics over larger spatial scales. Arterial spin labeling blood flow MR images of the brain were visualization enhanced using anatomic images with multiple contrasts. The algorithms were validated on a numerical phantom and their performance on images of brain tumor patients were assessed by quantitative metrics and neuroradiologist subjective ratings. The frequency multiplication method had the lowest residual error for preserving the original functional image contrast at larger spatial scales (55%–98% of the other methods with simulated data and 64%–86% with experimental data). It was also significantly more highly graded by the radiologists (p<0.005 for clear brain anatomy around the tumor). Compared to other methods, the SALSA provided 11%–133% higher similarity with ground truth images in the simulation and showed just slightly lower neuroradiologist grading score. Most of these monochrome methods do not require any prior knowledge about the functional and anatomic image characteristics, except the acquired resolution. Hence, automatic implementation on clinical images should be readily feasible. PMID:27723582

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T

PubMed Central

Lei, Hongxia; Mlynárik, Vladimir; Just, Nathalie; Gruetter, Rolf

2009-01-01

With improved B0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B0 inhomogeneities, especially second-order shim terms, a 200×200 μm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set. PMID:18486393

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications.

PubMed

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-12-29

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors' architecture on the basis of the type of electric measurement or imaging functionalities.

Self-calibrated correlation imaging with k-space variant correlation functions.

PubMed

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

When the oocyte becomes an embryo. The social life of an ambiguous scientific image in Italian newspapers (1996-2007).

PubMed

Beltrame, Lorenzo; Giovanetti, Silvia

2009-01-01

This paper analyses the social life of a scientific image frequently used in media coverage of human genetic and biotechnology issues. The expression "social life of an image" refers to the set of functions performed in the public sphere and the relations interweaved with narratives and discourses. This paper starts from the assumption that the sense of an image is reflexive to its local contexts of use. Therefore, the social meaning of an image relies on the web of discursive links which constitute its social life. The paper explores the functions performed by a photograph of a fertilized oocyte in Italian media coverage of human genetic issues. We conclude asserting that such an image: (a) acts as a visual link between several controversial issues; (b) it has become the icon of a general master-frame of human genetics issues and (c) it takes a not neutral part in the debates over these issues.

Positron emission tomography with [ 18F]-FDG in oncology

NASA Astrophysics Data System (ADS)

Talbot, J. N.; Petegnief, Y.; Kerrou, K.; Montravers, F.; Grahek, D.; Younsi, N.

2003-05-01

Positron Emission Tomography (PET) is a several decade old imaging technique that has more recently demonstrated its utility in clinical applications. The imaging agents used for PET contain a positron emmiter coupled to a molecule that drives the radionuclide to target organs or to tissues performing the targetted biological function. PET is then part of functional imaging. As compared to conventional scintigraphy that uses gamma photons, the coincidence emission of two 511 keV annihilation photons in opposite direction that finally results from by beta plus decay makes it possible for PET to get rid of the collimators that greatly contribute to the poor resolution of scintigraphy. In this article, the authors describe the basics of physics for PET imaging and report on the clinical performances of the most commonly used PET tracer: [ 18F]-fluorodeoxyglucose (FDG). A recent and promising development in this field is fusion of images coming from different imaging modalities. New PET machines now include a CT and this fusion is therefore much easier.

Robust w-Estimators for Cryo-EM Class Means

PubMed Central

Huang, Chenxi; Tagare, Hemant D.

2016-01-01

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the “class mean”, improves the signal-to-noise ratio in single particle reconstruction (SPR). The averaging step is often compromised because of outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods is done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a “w-estimator” of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions (CTFs) is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers. PMID:26841397

Robust w-Estimators for Cryo-EM Class Means.

PubMed

Huang, Chenxi; Tagare, Hemant D

2016-02-01

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the class mean, improves the signal-to-noise ratio in single-particle reconstruction. The averaging step is often compromised because of the outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods are done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a w-estimator of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers.

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention

PubMed Central

Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L.

2012-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. Previous findings by our group strongly suggested that the changes in neural activity observed during increased cholinergic function may reflect an increase in neural efficiency that leads to improved task performance. The current study was designed to assess the effects of cholinergic enhancement on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover functional magnetic resonance imaging (fMRI) study. Following an infusion of physostigmine (1mg/hr) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions was reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Cholinergic enhancement also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus processing regions provide further support to the hypothesis that cholinergic augmentation results in enhanced neural efficiency. PMID:22906685

Analyzing microtomography data with Python and the scikit-image library.

PubMed

Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan

2017-01-01

The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

Laterality in Metaphor Processing: Lack of Evidence from Functional Magnetic Resonance Imaging for the Right Hemisphere Theory

ERIC Educational Resources Information Center

Rapp, Alexander M.; Leube, Dirk T.; Erb, Michael; Grodd, Wolfgang; Kircher, Tilo T. J.

2007-01-01

We investigated processing of metaphoric sentences using event-related functional magnetic resonance imaging (fMRI). Seventeen healthy subjects (6 female, 11 male) read 60 novel short German sentence pairs with either metaphoric or literal meaning and performed two different tasks: judging the metaphoric content and judging whether the sentence…

Radiation Hardened Low Power Digital Signal Processor

DTIC Science & Technology

2005-04-15

Image Figure 53.0 Point Spread Function PSF Figure 54.0 Restored Image and Restored PSF Figure 55.0 Newly Created Array Figure 56.0 Deblurred Image and... noise and interference rejection. WOA’s of 32-taps and greater are easily managed by the TCSP. An architecture that could efficiently perform filter...to quickly calculate a Remez filter impulse response to be used in place of the window function. Using the Remez exchange algorithm to calculate the

Laser applications and system considerations in ocular imaging

PubMed Central

Elsner, Ann E.; Muller, Matthew S.

2009-01-01

We review laser applications for primarily in vivo ocular imaging techniques, describing their constraints based on biological tissue properties, safety, and the performance of the imaging system. We discuss the need for cost effective sources with practical wavelength tuning capabilities for spectral studies. Techniques to probe the pathological changes of layers beneath the highly scattering retina and diagnose the onset of various eye diseases are described. The recent development of several optical coherence tomography based systems for functional ocular imaging is reviewed, as well as linear and nonlinear ocular imaging techniques performed with ultrafast lasers, emphasizing recent source developments and methods to enhance imaging contrast. PMID:21052482

Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

PubMed

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

More than looking good: impact on quality of life moderates the relationship between functional body image and physical activity in men with SCI.

PubMed

Bassett, R L; Martin Ginis, K A

2009-03-01

Cross-sectional. To examine the relationship between body image and leisure time physical activity (LTPA) among men with spinal cord injury (SCI). Specifically, to examine the moderating function of the perceived impact of body image on quality of life (QOL). Ontario, Canada. Men with SCI (N=50, 50% paraplegic) reported, (a) their functional and appearance body image (Adult Body Satisfaction Questionnaire), (b) their perceived impact of body image on QOL and (c) LTPA performed over the previous 3 days. Body image was in the 'normal' range compared with the general population. Linear regression analysis found a significant LTPA x body image impact on QOL interaction beta=0.39, P<0.05. Post hoc analysis showed that among individuals who reported a negative effect of body image on QOL, those who engaged in LTPA were less satisfied with their physical function than those who did not. For those who did not perceive their body image to negatively impact their QOL, there was generally no difference in functional body image between those who engaged in LTPA and those who did not. Appearance body image is not related to LTPA for men with SCI. It has been suggested that body dissatisfaction may motivate some individuals to engage in LTPA. However, for men living with SCI, functional body image may be associated with LTPA only when a negative effect on QOL is perceived. Future research should consider the moderating function of the perceived impact of body image on QOL when examining the relationship between LTPA and body image among men living with SCI.

Image enhancement software for underwater recovery operations: User's manual

NASA Astrophysics Data System (ADS)

Partridge, William J.; Therrien, Charles W.

1989-06-01

This report describes software for performing image enhancement on live or recorded video images. The software was developed for operational use during underwater recovery operations at the Naval Undersea Warfare Engineering Station. The image processing is performed on an IBM-PC/AT compatible computer equipped with hardware to digitize and display video images. The software provides the capability to provide contrast enhancement and other similar functions in real time through hardware lookup tables, to automatically perform histogram equalization, to capture one or more frames and average them or apply one of several different processing algorithms to a captured frame. The report is in the form of a user manual for the software and includes guided tutorial and reference sections. A Digital Image Processing Primer in the appendix serves to explain the principle concepts that are used in the image processing.

Leveraging simulation to evaluate system performance in presence of fixed pattern noise

NASA Astrophysics Data System (ADS)

Teaney, Brian P.

2017-05-01

The development of image simulation techniques which map the effects of a notional, modeled sensor system onto an existing image can be used to evaluate the image quality of camera systems prior to the development of prototype systems. In addition, image simulation or `virtual prototyping' can be utilized to reduce the time and expense associated with conducting extensive field trials. In this paper we examine the development of a perception study designed to assess the performance of the NVESD imager performance metrics as a function of fixed pattern noise. This paper discusses the development of the model theory and the implementation and execution of the perception study. In addition, other applications of the image simulation component including the evaluation of limiting resolution and other test targets is provided.

Information theoretic analysis of linear shift-invariant edge-detection operators

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2012-06-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

Evaluation of Language Function under Awake Craniotomy

PubMed Central

KANNO, Aya; MIKUNI, Nobuhiro

2015-01-01

Awake craniotomy is the only established way to assess patients’ language functions intraoperatively and to contribute to their preservation, if necessary. Recent guidelines have enabled the approach to be used widely, effectively, and safely. Non-invasive brain functional imaging techniques, including functional magnetic resonance imaging and diffusion tensor imaging, have been used preoperatively to identify brain functional regions corresponding to language, and their accuracy has increased year by year. In addition, the use of neuronavigation that incorporates this preoperative information has made it possible to identify the positional relationships between the lesion and functional regions involved in language, conduct functional brain mapping in the awake state with electrical stimulation, and intraoperatively assess nerve function in real time when resecting the lesion. This article outlines the history of awake craniotomy, the current state of pre- and intraoperative evaluation of language function, and the clinical usefulness of such functional evaluation. When evaluating patients’ language functions during awake craniotomy, given the various intraoperative stresses involved, it is necessary to carefully select the tasks to be undertaken, quickly perform all examinations, and promptly evaluate the results. As language functions involve both input and output, they are strongly affected by patients’ preoperative cognitive function, degree of intraoperative wakefulness and fatigue, the ability to produce verbal articulations and utterances, as well as perform synergic movement. Therefore, it is essential to appropriately assess the reproducibility of language function evaluation using awake craniotomy techniques. PMID:25925758

Evaluation of Language Function under Awake Craniotomy.

PubMed

Kanno, Aya; Mikuni, Nobuhiro

2015-01-01

Awake craniotomy is the only established way to assess patients' language functions intraoperatively and to contribute to their preservation, if necessary. Recent guidelines have enabled the approach to be used widely, effectively, and safely. Non-invasive brain functional imaging techniques, including functional magnetic resonance imaging and diffusion tensor imaging, have been used preoperatively to identify brain functional regions corresponding to language, and their accuracy has increased year by year. In addition, the use of neuronavigation that incorporates this preoperative information has made it possible to identify the positional relationships between the lesion and functional regions involved in language, conduct functional brain mapping in the awake state with electrical stimulation, and intraoperatively assess nerve function in real time when resecting the lesion. This article outlines the history of awake craniotomy, the current state of pre- and intraoperative evaluation of language function, and the clinical usefulness of such functional evaluation. When evaluating patients' language functions during awake craniotomy, given the various intraoperative stresses involved, it is necessary to carefully select the tasks to be undertaken, quickly perform all examinations, and promptly evaluate the results. As language functions involve both input and output, they are strongly affected by patients' preoperative cognitive function, degree of intraoperative wakefulness and fatigue, the ability to produce verbal articulations and utterances, as well as perform synergic movement. Therefore, it is essential to appropriately assess the reproducibility of language function evaluation using awake craniotomy techniques.

Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM.

PubMed

Razifar, Pasha; Sandström, Mattias; Schnieder, Harald; Långström, Bengt; Maripuu, Enn; Bengtsson, Ewert; Bergström, Mats

2005-08-25

Positron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone. Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT. Experiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images. The most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images. The combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

An image mosaic method based on corner

NASA Astrophysics Data System (ADS)

Jiang, Zetao; Nie, Heting

2015-08-01

In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

Hybrid reflecting objectives for functional multiphoton microscopy in turbid media

PubMed Central

Vučinić, Dejan; Bartol, Thomas M.; Sejnowski, Terrence J.

2010-01-01

Most multiphoton imaging of biological specimens is performed using microscope objectives optimized for high image quality under wide-field illumination. We present a class of objectives designed de novo without regard for these traditional constraints, driven exclusively by the needs of fast multiphoton imaging in turbid media: the delivery of femtosecond pulses without dispersion and the efficient collection of fluorescence. We model the performance of one such design optimized for a typical brain-imaging setup and show that it can greatly outperform objectives commonly used for this task. PMID:16880851

Longitudinal timed function tests in Duchenne muscular dystrophy: ImagingDMD cohort natural history.

PubMed

Arora, Harneet; Willcocks, Rebecca J; Lott, Donovan J; Harrington, Ann T; Senesac, Claudia R; Zilke, Kirsten L; Daniels, Michael J; Xu, Dandan; Tennekoon, Gihan I; Finanger, Erika L; Russman, Barry S; Finkel, Richard S; Triplett, William T; Byrne, Barry J; Walter, Glenn A; Sweeney, H Lee; Vandenborne, Krista

2018-05-09

Tests of ambulatory function are common clinical trial endpoints in Duchenne muscular dystrophy (DMD). The ImagingDMD study has generated a large data set using these tests, which can describe the contemporary natural history of DMD in 5-12.9 year olds. 92 corticosteroid treated boys with DMD and 45 controls participated in this longitudinal study. Subjects performed the 6 minute walk test (6MWT) and timed function tests (TFTs: 10m walk/run, 4 stairs, supine to stand). Boys with DMD had impaired functional performance even at 5-6.9 years. Boys older than 7 had significant declines in function over 1 year for 10m walk/run and 6MWT. 80% of subjects could perform all functional tests at 9 years old. TFTs appear to be slightly more responsive and predictive of disease progression than 6MWT in 7-12.9 year olds. This study provides insight into the contemporary natural history of key functional endpoints in DMD. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang- Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang-Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Fuzzy membership functions for analysis of high-resolution CT images of diffuse pulmonary diseases.

PubMed

Almeida, Eliana; Rangayyan, Rangaraj M; Azevedo-Marques, Paulo M

2015-08-01

We propose the use of fuzzy membership functions to analyze images of diffuse pulmonary diseases (DPDs) based on fractal and texture features. The features were extracted from preprocessed regions of interest (ROIs) selected from high-resolution computed tomography images. The ROIs represent five different patterns of DPDs and normal lung tissue. A Gaussian mixture model (GMM) was constructed for each feature, with six Gaussians modeling the six patterns. Feature selection was performed and the GMMs of the five significant features were used. From the GMMs, fuzzy membership functions were obtained by a probability-possibility transformation and further statistical analysis was performed. An average classification accuracy of 63.5% was obtained for the six classes. For four of the six classes, the classification accuracy was superior to 65%, and the best classification accuracy was 75.5% for one class. The use of fuzzy membership functions to assist in pattern classification is an alternative to deterministic approaches to explore strategies for medical diagnosis.

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption

NASA Astrophysics Data System (ADS)

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-01

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information.

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption

PubMed Central

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-01

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information. PMID:26823196

Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption.

PubMed

Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min

2016-01-29

Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information.

Blind identification of image manipulation type using mixed statistical moments

NASA Astrophysics Data System (ADS)

Jeong, Bo Gyu; Moon, Yong Ho; Eom, Il Kyu

2015-01-01

We present a blind identification of image manipulation types such as blurring, scaling, sharpening, and histogram equalization. Motivated by the fact that image manipulations can change the frequency characteristics of an image, we introduce three types of feature vectors composed of statistical moments. The proposed statistical moments are generated from separated wavelet histograms, the characteristic functions of the wavelet variance, and the characteristic functions of the spatial image. Our method can solve the n-class classification problem. Through experimental simulations, we demonstrate that our proposed method can achieve high performance in manipulation type detection. The average rate of the correctly identified manipulation types is as high as 99.22%, using 10,800 test images and six manipulation types including the authentic image.

Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

PubMed

Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

2013-01-01

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.

Cerebral networks of sustained attention and working memory: a functional magnetic resonance imaging study based on the Continuous Performance Test.

PubMed

Bartés-Serrallonga, M; Adan, A; Solé-Casals, J; Caldú, X; Falcón, C; Pérez-Pàmies, M; Bargalló, N; Serra-Grabulosa, J M

2014-04-01

One of the most used paradigms in the study of attention is the Continuous Performance Test (CPT). The identical pairs version (CPT-IP) has been widely used to evaluate attention deficits in developmental, neurological and psychiatric disorders. However, the specific locations and the relative distribution of brain activation in networks identified with functional imaging, varies significantly with differences in task design. To design a task to evaluate sustained attention using functional magnetic resonance imaging (fMRI), and thus to provide data for research concerned with the role of these functions. Forty right-handed, healthy students (50% women; age range: 18-25 years) were recruited. A CPT-IP implemented as a block design was used to assess sustained attention during the fMRI session. The behavioural results from the CPT-IP task showed a good performance in all subjects, higher than 80% of hits. fMRI results showed that the used CPT-IP task activates a network of frontal, parietal and occipital areas, and that these are related to executive and attentional functions. In relation to the use of the CPT to study of attention and working memory, this task provides normative data in healthy adults, and it could be useful to evaluate disorders which have attentional and working memory deficits.

A Method for the Alignment of Heterogeneous Macromolecules from Electron Microscopy

PubMed Central

Shatsky, Maxim; Hall, Richard J.; Brenner, Steven E.; Glaeser, Robert M.

2009-01-01

We propose a feature-based image alignment method for single-particle electron microscopy that is able to accommodate various similarity scoring functions while efficiently sampling the two-dimensional transformational space. We use this image alignment method to evaluate the performance of a scoring function that is based on the Mutual Information (MI) of two images rather than one that is based on the cross-correlation function. We show that alignment using MI for the scoring function has far less model-dependent bias than is found with cross-correlation based alignment. We also demonstrate that MI improves the alignment of some types of heterogeneous data, provided that the signal to noise ratio is relatively high. These results indicate, therefore, that use of MI as the scoring function is well suited for the alignment of class-averages computed from single particle images. Our method is tested on data from three model structures and one real dataset. PMID:19166941

New Developments in Observer Performance Methodology in Medical Imaging

PubMed Central

Chakraborty, Dev P.

2011-01-01

A common task in medical imaging is assessing whether a new imaging system, or a variant of an existing one, is an improvement over an existing imaging technology. Imaging systems are generally quite complex, consisting of several components – e.g., image acquisition hardware, image processing and display hardware and software, and image interpretation by radiologists– each of which can affect performance. While it may appear odd to include the radiologist as a “component” of the imaging chain, since the radiologist’s decision determines subsequent patient care, the effect of the human interpretation has to be included. Physical measurements like modulation transfer function, signal to noise ratio, etc., are useful for characterizing the non-human parts of the imaging chain under idealized and often unrealistic conditions, such as uniform background phantoms, target objects with sharp edges, etc. Measuring the effect on performance of the entire imaging chain, including the radiologist, and using real clinical images, requires different methods that fall under the rubric of observer performance methods or “ROC analysis”. The purpose of this paper is to review recent developments in this field, particularly with respect to the free-response method. PMID:21978444

Adaptive iterated function systems filter for images highly corrupted with fixed - Value impulse noise

NASA Astrophysics Data System (ADS)

Shanmugavadivu, P.; Eliahim Jeevaraj, P. S.

2014-06-01

The Adaptive Iterated Functions Systems (AIFS) Filter presented in this paper has an outstanding potential to attenuate the fixed-value impulse noise in images. This filter has two distinct phases namely noise detection and noise correction which uses Measure of Statistics and Iterated Function Systems (IFS) respectively. The performance of AIFS filter is assessed by three metrics namely, Peak Signal-to-Noise Ratio (PSNR), Mean Structural Similarity Index Matrix (MSSIM) and Human Visual Perception (HVP). The quantitative measures PSNR and MSSIM endorse the merit of this filter in terms of degree of noise suppression and details/edge preservation respectively, in comparison with the high performing filters reported in the recent literature. The qualitative measure HVP confirms the noise suppression ability of the devised filter. This computationally simple noise filter broadly finds application wherein the images are highly degraded by fixed-value impulse noise.

Neural Substrates for Processing Task-Irrelevant Sad Images in Adolescents

ERIC Educational Resources Information Center

Wang, Lihong; Huettel, Scott; De Bellis, Michael D.

2008-01-01

Neural systems related to cognitive and emotional processing were examined in adolescents using event-related functional magnetic resonance imaging (fMRI). Ten healthy adolescents performed an emotional oddball task. Subjects detected infrequent circles (targets) within a continual stream of phase-scrambled images (standards). Sad and neutral…

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

ERIC Educational Resources Information Center

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2011-01-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the…

Early Functional Connectome Integrity and 1-Year Recovery in Comatose Survivors of Cardiac Arrest.

PubMed

Sair, Haris I; Hannawi, Yousef; Li, Shanshan; Kornbluth, Joshua; Demertzi, Athena; Di Perri, Carol; Chabanne, Russell; Jean, Betty; Benali, Habib; Perlbarg, Vincent; Pekar, James; Luyt, Charles-Edouard; Galanaud, Damien; Velly, Lionel; Puybasset, Louis; Laureys, Steven; Caffo, Brian; Stevens, Robert D

2018-04-01

Purpose To assess whether early brain functional connectivity is associated with functional recovery 1 year after cardiac arrest (CA). Materials and Methods Enrolled in this prospective multicenter cohort were 46 patients who were comatose after CA. Principal outcome was cerebral performance category at 12 months, with favorable outcome (FO) defined as cerebral performance category 1 or 2. All participants underwent multiparametric structural and functional magnetic resonance (MR) imaging less than 4 weeks after CA. Within- and between-network connectivity was measured in dorsal attention network (DAN), default-mode network (DMN), salience network (SN), and executive control network (ECN) by using seed-based analysis of resting-state functional MR imaging data. Structural changes identified with fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were analyzed by using validated morphologic scales. The association between connectivity measures, structural changes, and the principal outcome was explored with multivariable modeling. Results Patients underwent MR imaging a mean 12.6 days ± 5.6 (standard deviation) after CA. At 12 months, 11 patients had an FO. Patients with FO had higher within-DMN connectivity and greater anticorrelation between SN and DMN and between SN and ECN compared with patients with unfavorable outcome, an effect that was maintained after multivariable adjustment. Anticorrelation of SN-DMN predicted outcomes with higher accuracy than fluid-attenuated inversion recovery or diffusion-weighted imaging scores (area under the receiver operating characteristic curves, respectively, 0.88, 0.74, and 0.71). Conclusion MR imaging-based measures of cerebral functional network connectivity obtained in the acute phase of CA were independently associated with FO at 1 year, warranting validation as early markers of long-term recovery potential in patients with anoxic-ischemic encephalopathy. © RSNA, 2017.

The Montreal Imaging Stress Task: using functional imaging to investigate the effects of perceiving and processing psychosocial stress in the human brain

PubMed Central

Dedovic, Katarina; Renwick, Robert; Mahani, Najmeh Khalili; Engert, Veronika; Lupien, Sonia J.; Pruessner, Jens C.

2005-01-01

Objective We developed a protocol for inducing moderate psychologic stress in a functional imaging setting and evaluated the effects of stress on physiology and brain activation. Methods The Montreal Imaging Stress Task (MIST), derived from the Trier Mental Challenge Test, consists of a series of computerized mental arithmetic challenges, along with social evaluative threat components that are built into the program or presented by the investigator. To allow the effects of stress and mental arithmetic to be investigated separately, the MIST has 3 test conditions (rest, control and experimental), which can be presented in either a block or an event-related design, for use with functional magnetic resonance imaging (fMRI) or positron emission tomography (PET). In the rest condition, subjects look at a static computer screen on which no tasks are shown. In the control condition, a series of mental arithmetic tasks are displayed on the computer screen, and subjects submit their answers by means of a response interface. In the experimental condition, the difficulty and time limit of the tasks are manipulated to be just beyond the individual's mental capacity. In addition, in this condition the presentation of the mental arithmetic tasks is supplemented by a display of information on individual and average performance, as well as expected performance. Upon completion of each task, the program presents a performance evaluation to further increase the social evaluative threat of the situation. Results In 2 independent studies using PET and a third independent study using fMRI, with a total of 42 subjects, levels of salivary free cortisol for the whole group were significantly increased under the experimental condition, relative to the control and rest conditions. Performing mental arithmetic was linked to activation of motor and visual association cortices, as well as brain structures involved in the performance of these tasks (e.g., the angular gyrus). Conclusions We propose the MIST as a tool for investigating the effects of perceiving and processing psychosocial stress in functional imaging studies. PMID:16151536

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications

PubMed Central

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-01-01

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors’ architecture on the basis of the type of electric measurement or imaging functionalities. PMID:28879978

Filter Function for Wavefront Sensing Over a Field of View

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A filter function has been derived as a means of optimally weighting the wavefront estimates obtained in image-based phase retrieval performed at multiple points distributed over the field of view of a telescope or other optical system. When the data obtained in wavefront sensing and, more specifically, image-based phase retrieval, are used for controlling the shape of a deformable mirror or other optic used to correct the wavefront, the control law obtained by use of the filter function gives a more balanced optical performance over the field of view than does a wavefront-control law obtained by use of a wavefront estimate obtained from a single point in the field of view.

Light-Field Imaging Toolkit

NASA Astrophysics Data System (ADS)

Bolan, Jeffrey; Hall, Elise; Clifford, Chris; Thurow, Brian

The Light-Field Imaging Toolkit (LFIT) is a collection of MATLAB functions designed to facilitate the rapid processing of raw light field images captured by a plenoptic camera. An included graphical user interface streamlines the necessary post-processing steps associated with plenoptic images. The generation of perspective shifted views and computationally refocused images is supported, in both single image and animated formats. LFIT performs necessary calibration, interpolation, and structuring steps to enable future applications of this technology.

Expanding the PACS archive to support clinical review, research, and education missions

NASA Astrophysics Data System (ADS)

Honeyman-Buck, Janice C.; Frost, Meryll M.; Drane, Walter E.

1999-07-01

Designing an image archive and retrieval system that supports multiple users with many different requirements and patterns of use without compromising the performance and functionality required by diagnostic radiology is an intellectual and technical challenge. A diagnostic archive, optimized for performance when retrieving diagnostic images for radiologists needed to be expanded to support a growing clinical review network, the University of Florida Brain Institute's demands for neuro-imaging, Biomedical Engineering's imaging sciences, and an electronic teaching file. Each of the groups presented a different set of problems for the designers of the system. In addition, the radiologists did not want to see nay loss of performance as new users were added.

3D image restoration for confocal microscopy: toward a wavelet deconvolution for the study of complex biological structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, Jacques; Le Calvez, Sophie; Ulfendahl, Mats

2000-05-01

Image restoration algorithms provide efficient tools for recovering part of the information lost in the imaging process of a microscope. We describe recent progress in the application of deconvolution to confocal microscopy. The point spread function of a Biorad-MRC1024 confocal microscope was measured under various imaging conditions, and used to process 3D-confocal images acquired in an intact preparation of the inner ear developed at Karolinska Institutet. Using these experiments we investigate the application of denoising methods based on wavelet analysis as a natural regularization of the deconvolution process. Within the Bayesian approach to image restoration, we compare wavelet denoising with the use of a maximum entropy constraint as another natural regularization method. Numerical experiments performed with test images show a clear advantage of the wavelet denoising approach, allowing to `cool down' the image with respect to the signal, while suppressing much of the fine-scale artifacts appearing during deconvolution due to the presence of noise, incomplete knowledge of the point spread function, or undersampling problems. We further describe a natural development of this approach, which consists of performing the Bayesian inference directly in the wavelet domain.

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

Characterizing Density and Complexity of Imported Cargos

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

Birrer, Nathaniel; Divin, Charles; Glenn, Steven

X-ray inspection systems are used to detect radiological and nuclear threats in imported cargo. In order to better understand performance of these systems, system imaging capabilities and the characteristics of imported cargo need to be determined. This project involved calculation of the modulation transfer function as a metric of system imaging performance and a study of the density and inhomogeneity of imported cargos, which have been shown to correlate with human analysts, threat detection performance.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

PubMed Central

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

PubMed

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Development of a 750x750 pixels CMOS imager sensor for tracking applications

NASA Astrophysics Data System (ADS)

Larnaudie, Franck; Guardiola, Nicolas; Saint-Pé, Olivier; Vignon, Bruno; Tulet, Michel; Davancens, Robert; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Estribeau, Magali

2017-11-01

Solid-state optical sensors are now commonly used in space applications (navigation cameras, astronomy imagers, tracking sensors...). Although the charge-coupled devices are still widely used, the CMOS image sensor (CIS), which performances are continuously improving, is a strong challenger for Guidance, Navigation and Control (GNC) systems. This paper describes a 750x750 pixels CMOS image sensor that has been specially designed and developed for star tracker and tracking sensor applications. Such detector, that is featuring smart architecture enabling very simple and powerful operations, is built using the AMIS 0.5μm CMOS technology. It contains 750x750 rectangular pixels with 20μm pitch. The geometry of the pixel sensitive zone is optimized for applications based on centroiding measurements. The main feature of this device is the on-chip control and timing function that makes the device operation easier by drastically reducing the number of clocks to be applied. This powerful function allows the user to operate the sensor with high flexibility: measurement of dark level from masked lines, direct access to the windows of interest… A temperature probe is also integrated within the CMOS chip allowing a very precise measurement through the video stream. A complete electro-optical characterization of the sensor has been performed. The major parameters have been evaluated: dark current and its uniformity, read-out noise, conversion gain, Fixed Pattern Noise, Photo Response Non Uniformity, quantum efficiency, Modulation Transfer Function, intra-pixel scanning. The characterization tests are detailed in the paper. Co60 and protons irradiation tests have been also carried out on the image sensor and the results are presented. The specific features of the 750x750 image sensor such as low power CMOS design (3.3V, power consumption<100mW), natural windowing (that allows efficient and robust tracking algorithms), simple proximity electronics (because of the on-chip control and timing function) enabling a high flexibility architecture, make this imager a good candidate for high performance tracking applications.

X-ray phase imaging-From static observation to dynamic observation-

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

Momose, A.; Yashiro, W.; Olbinado, M. P.

2012-07-31

We are attempting to expand the technology of X-ray grating phase imaging/tomography to enable dynamic observation. X-ray phase imaging has been performed mainly for static cases, and this challenge is significant since properties of materials (and hopefully their functions) would be understood by observing their dynamics in addition to their structure, which is an inherent advantage of X-ray imaging. Our recent activities in combination with white synchrotron radiation for this purpose are described. Taking advantage of the fact that an X-ray grating interferometer functions with X-rays of a broad energy bandwidth (and therefore high flux), movies of differential phase imagesmore » and visibility images are obtained with a time resolution of a millisecond. The time resolution of X-ray phase tomography can therefore be a second. This study is performed as a part of a project to explore X-ray grating interferometry, and our other current activities are also briefly outlined.« less

Bayesian image reconstruction for improving detection performance of muon tomography.

PubMed

Wang, Guobao; Schultz, Larry J; Qi, Jinyi

2009-05-01

Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet.

PubMed

Mariappan, Leo; Hu, Gang; He, Bin

2014-02-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

Real-time landmark-based unrestrained animal tracking system for motion-corrected PET/SPECT imaging

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

J.S. Goddard; S.S. Gleason; M.J. Paulus

2003-08-01

Oak Ridge National Laboratory (ORNL) and Jefferson Lab and are collaborating to develop a new high-resolution single photon emission tomography (SPECT) instrument to image unrestrained laboratory animals. This technology development will allow functional imaging studies to be performed on the animals without the use of anesthetic agents. This technology development could have eventual clinical applications for performing functional imaging studies on patients that cannot remain still (Parkinson's patients, Alzheimer's patients, small children, etc.) during a PET or SPECT scan. A key component of this new device is the position tracking apparatus. The tracking apparatus is an integral part of themore » gantry and designed to measure the spatial position of the animal at a rate of 10-15 frames per second with sub-millimeter accuracy. Initial work focuses on brain studies where anesthetic agents or physical restraint can significantly impact physiologic processes.« less

Echocardiographic Evaluation of Left Atrial Mechanics: Function, History, Novel Techniques, Advantages, and Pitfalls.

PubMed

Leischik, Roman; Littwitz, Henning; Dworrak, Birgit; Garg, Pankaj; Zhu, Meihua; Sahn, David J; Horlitz, Marc

2015-01-01

Left atrial (LA) functional analysis has an established role in assessing left ventricular diastolic function. The current standard echocardiographic parameters used to study left ventricular diastolic function include pulsed-wave Doppler mitral inflow analysis, tissue Doppler imaging measurements, and LA dimension estimation. However, the above-mentioned parameters do not directly quantify LA performance. Deformation studies using strain and strain-rate imaging to assess LA function were validated in previous research, but this technique is not currently used in routine clinical practice. This review discusses the history, importance, and pitfalls of strain technology for the analysis of LA mechanics.

Perceptual Optimization of DCT Color Quantization Matrices

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Statler, Irving C. (Technical Monitor)

1994-01-01

Many image compression schemes employ a block Discrete Cosine Transform (DCT) and uniform quantization. Acceptable rate/distortion performance depends upon proper design of the quantization matrix. In previous work, we showed how to use a model of the visibility of DCT basis functions to design quantization matrices for arbitrary display resolutions and color spaces. Subsequently, we showed how to optimize greyscale quantization matrices for individual images, for optimal rate/perceptual distortion performance. Here we describe extensions of this optimization algorithm to color images.

Photodiode area effect on performance of X-ray CMOS active pixel sensors

NASA Astrophysics Data System (ADS)

Kim, M. S.; Kim, Y.; Kim, G.; Lim, K. T.; Cho, G.; Kim, D.

2018-02-01

Compared to conventional TFT-based X-ray imaging devices, CMOS-based X-ray imaging sensors are considered next generation because they can be manufactured in very small pixel pitches and can acquire high-speed images. In addition, CMOS-based sensors have the advantage of integration of various functional circuits within the sensor. The image quality can also be improved by the high fill-factor in large pixels. If the size of the subject is small, the size of the pixel must be reduced as a consequence. In addition, the fill factor must be reduced to aggregate various functional circuits within the pixel. In this study, 3T-APS (active pixel sensor) with photodiodes of four different sizes were fabricated and evaluated. It is well known that a larger photodiode leads to improved overall performance. Nonetheless, if the size of the photodiode is > 1000 μm2, the degree to which the sensor performance increases as the photodiode size increases, is reduced. As a result, considering the fill factor, pixel-pitch > 32 μm is not necessary to achieve high-efficiency image quality. In addition, poor image quality is to be expected unless special sensor-design techniques are included for sensors with a pixel pitch of 25 μm or less.

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

PubMed Central

Kelley, Brian J.; Harel, Noam Y.; Kim, Chang-Yeon; Papademetris, Xenophon; Coman, Daniel; Wang, Xingxing; Hasan, Omar; Kaufman, Adam; Globinsky, Ronen; Staib, Lawrence H.; Cafferty, William B.J.; Hyder, Fahmeed

2014-01-01

Abstract Traumatic spinal cord injury (SCI) causes long-term disability with limited functional recovery linked to the extent of axonal connectivity. Quantitative diffusion tensor imaging (DTI) of axonal integrity has been suggested as a potential biomarker for prognostic and therapeutic evaluation after trauma, but its correlation with functional outcomes has not been clearly defined. To examine this application, female Sprague-Dawley rats underwent midthoracic laminectomy followed by traumatic spinal cord contusion of differing severities or laminectomy without contusion. Locomotor scores and hindlimb kinematic data were collected for 4 weeks post-injury. Ex vivo DTI was then performed to assess axonal integrity using tractography and fractional anisotropy (FA), a numerical measure of relative white matter integrity, at the injury epicenter and at specific intervals rostral and caudal to the injury site. Immunohistochemistry for tissue sparing was also performed. Statistical correlation between imaging data and functional performance was assessed as the primary outcome. All injured animals showed some recovery of locomotor function, while hindlimb kinematics revealed graded deficits consistent with injury severity. Standard T2 magnetic resonance sequences illustrated conventional spinal cord morphology adjacent to contusions while corresponding FA maps indicated graded white matter pathology within these adjacent regions. Positive correlations between locomotor (Basso, Beattie, and Bresnahan score and gait kinematics) and imaging (FA values) parameters were also observed within these adjacent regions, most strongly within caudal segments beyond the lesion. Evaluation of axonal injury by DTI provides a mechanism for functional recovery assessment in a rodent SCI model. These findings suggest that focused DTI analysis of caudal spinal cord should be studied in human cases in relationship to motor outcome to augment outcome biomarkers for clinical cases. PMID:24779685

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

Gnuastro: GNU Astronomy Utilities

NASA Astrophysics Data System (ADS)

Akhlaghi, Mohammad

2018-01-01

Gnuastro (GNU Astronomy Utilities) manipulates and analyzes astronomical data. It is an official GNU package of a large collection of programs and C/C++ library functions. Command-line programs perform arithmetic operations on images, convert FITS images to common types like JPG or PDF, convolve an image with a given kernel or matching of kernels, perform cosmological calculations, crop parts of large images (possibly in multiple files), manipulate FITS extensions and keywords, and perform statistical operations. In addition, it contains programs to make catalogs from detection maps, add noise, make mock profiles with a variety of radial functions using monte-carlo integration for their centers, match catalogs, and detect objects in an image among many other operations. The command-line programs share the same basic command-line user interface for the comfort of both the users and developers. Gnuastro is written to comply fully with the GNU coding standards and integrates well with all Unix-like operating systems. This enables astronomers to expect a fully familiar experience in the source code, building, installing and command-line user interaction that they have seen in all the other GNU software that they use. Gnuastro's extensive library is included for users who want to build their own unique programs.

Uncooled thermal imaging and image analysis

NASA Astrophysics Data System (ADS)

Wang, Shiyun; Chang, Benkang; Yu, Chunyu; Zhang, Junju; Sun, Lianjun

2006-09-01

Thermal imager can transfer difference of temperature to difference of electric signal level, so can be application to medical treatment such as estimation of blood flow speed and vessel 1ocation [1], assess pain [2] and so on. With the technology of un-cooled focal plane array (UFPA) is grown up more and more, some simple medical function can be completed with un-cooled thermal imager, for example, quick warning for fever heat with SARS. It is required that performance of imaging is stabilization and spatial and temperature resolution is high enough. In all performance parameters, noise equivalent temperature difference (NETD) is often used as the criterion of universal performance. 320 x 240 α-Si micro-bolometer UFPA has been applied widely presently for its steady performance and sensitive responsibility. In this paper, NETD of UFPA and the relation between NETD and temperature are researched. several vital parameters that can affect NETD are listed and an universal formula is presented. Last, the images from the kind of thermal imager are analyzed based on the purpose of detection persons with fever heat. An applied thermal image intensification method is introduced.

3D deformable image matching: a hierarchical approach over nested subspaces

NASA Astrophysics Data System (ADS)

Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

2000-06-01

This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

Cingulum correlates of cognitive functions in patients with mild cognitive impairment and early Alzheimer's disease: a diffusion spectrum imaging study.

PubMed

Lin, Yi-Cheng; Shih, Yao-Chia; Tseng, Wen-Yih I; Chu, Yu-Hsiu; Wu, Meng-Tien; Chen, Ta-Fu; Tang, Pei-Fang; Chiu, Ming-Jang

2014-05-01

Diffusion spectrum imaging (DSI) of MRI can detect neural fiber tract changes. We investigated integrity of cingulum bundle (CB) in patients with mild cognitive impairment (MCI) and early Alzheimer's disease (EAD) using DSI tractography and explored its relationship with cognitive functions. We recruited 8 patients with MCI, 9 with EAD and 15 healthy controls (HC). All subjects received a battery of neuropsychological tests to access their executive, memory and language functions. We used a 3.0-tesla MRI scanner to obtain T1- and T2-weighted images for anatomy and used a pulsed gradient twice-refocused spin-echo diffusion echo-planar imaging sequence to acquire DSI. Patients with EAD performed significantly poorer than the HC on most tests in executive and memory functions. Significantly smaller general fractional anisotropy (GFA) values were found in the posterior and inferior segments of left CB and of the anterior segment of right CB of the EAD compared with those of the HC. Spearman's correlation on the patient groups showed that GFA values of the posterior segment of the left CB were significantly negatively associated with the time used to complete Color Trails Test Part II and positively correlated with performance of the logical memory and visual reproduction. GFA values of inferior segment of bilateral CB were positively associated with the performance of visual recognition. DSI tractography demonstrates significant preferential degeneration of the CB on the left side in patients with EAD. The location-specific degeneration is associated with corresponding declines in both executive and memory functions.

From nociception to pain perception: imaging the spinal and supraspinal pathways

PubMed Central

Brooks, Jonathan; Tracey, Irene

2005-01-01

Functional imaging techniques have allowed researchers to look within the brain, and revealed the cortical representation of pain. Initial experiments, performed in the early 1990s, revolutionized pain research, as they demonstrated that pain was not processed in a single cortical area, but in several distributed brain regions. Over the last decade, the roles of these pain centres have been investigated and a clearer picture has emerged of the medial and lateral pain system. In this brief article, we review the imaging literature to date that has allowed these advances to be made, and examine the new frontiers for pain imaging research: imaging the brainstem and other structures involved in the descending control of pain; functional and anatomical connectivity studies of pain processing brain regions; imaging models of neuropathic pain-like states; and going beyond the brain to image spinal function. The ultimate goal of such research is to take these new techniques into the clinic, to investigate and provide new remedies for chronic pain sufferers. PMID:16011543

A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

PubMed

Tang, Jian; Jiang, Xiaoliang

2017-01-01

Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

PubMed

Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

2007-01-01

Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology.

Changes in Regional Ventilation During Treatment and Dosimetric Advantages of CT Ventilation Image Guided Radiation Therapy for Locally Advanced Lung Cancer.

PubMed

Yamamoto, Tokihiro; Kabus, Sven; Bal, Matthieu; Bzdusek, Karl; Keall, Paul J; Wright, Cari; Benedict, Stanley H; Daly, Megan E

2018-05-04

Lung functional image guided radiation therapy (RT) that avoids irradiating highly functional regions has potential to reduce pulmonary toxicity following RT. Tumor regression during RT is common, leading to recovery of lung function. We hypothesized that computed tomography (CT) ventilation image-guided treatment planning reduces the functional lung dose compared to standard anatomic image-guided planning in 2 different scenarios with or without plan adaptation. CT scans were acquired before RT and during RT at 2 time points (16-20 Gy and 30-34 Gy) for 14 patients with locally advanced lung cancer. Ventilation images were calculated by deformable image registration of four-dimensional CT image data sets and image analysis. We created 4 treatment plans at each time point for each patient: functional adapted, anatomic adapted, functional unadapted, and anatomic unadapted plans. Adaptation was performed at 2 time points. Deformable image registration was used for accumulating dose and calculating a composite of dose-weighted ventilation used to quantify the lung accumulated dose-function metrics. The functional plans were compared with the anatomic plans for each scenario separately to investigate the hypothesis at a significance level of 0.05. Tumor volume was significantly reduced by 20% after 16 to 20 Gy (P = .02) and by 32% after 30 to 34 Gy (P < .01) on average. In both scenarios, the lung accumulated dose-function metrics were significantly lower in the functional plans than in the anatomic plans without compromising target volume coverage and adherence to constraints to critical structures. For example, functional planning significantly reduced the functional mean lung dose by 5.0% (P < .01) compared to anatomic planning in the adapted scenario and by 3.6% (P = .03) in the unadapted scenario. This study demonstrated significant reductions in the accumulated dose to the functional lung with CT ventilation image-guided planning compared to anatomic image-guided planning for patients showing tumor regression and changes in regional ventilation during RT. Copyright © 2018 Elsevier Inc. All rights reserved.

Edge analyzing properties of center/surround response functions in cybernetic vision

NASA Technical Reports Server (NTRS)

Jobson, D. J.

1984-01-01

The ability of center/surround response functions to make explicit high resolution spatial information in optical images was investigated by performing convolutions of two dimensional response functions and image intensity functions (mainly edges). The center/surround function was found to have the unique property of separating edge contrast from shape variations and of providing a direct basis for determining contrast and subsequently shape of edges in images. Computationally simple measures of contrast and shape were constructed for potential use in cybernetic vision systems. For one class of response functions these measures were found to be reasonably resilient for a range of scan direction and displacements of the response functions relative to shaped edges. A pathological range of scan directions was also defined and methods for detecting and handling these cases were developed. The relationship of these results to biological vision is discussed speculatively.

Estimation of signal-dependent noise level function in transform domain via a sparse recovery model.

PubMed

Yang, Jingyu; Gan, Ziqiao; Wu, Zhaoyang; Hou, Chunping

2015-05-01

This paper proposes a novel algorithm to estimate the noise level function (NLF) of signal-dependent noise (SDN) from a single image based on the sparse representation of NLFs. Noise level samples are estimated from the high-frequency discrete cosine transform (DCT) coefficients of nonlocal-grouped low-variation image patches. Then, an NLF recovery model based on the sparse representation of NLFs under a trained basis is constructed to recover NLF from the incomplete noise level samples. Confidence levels of the NLF samples are incorporated into the proposed model to promote reliable samples and weaken unreliable ones. We investigate the behavior of the estimation performance with respect to the block size, sampling rate, and confidence weighting. Simulation results on synthetic noisy images show that our method outperforms existing state-of-the-art schemes. The proposed method is evaluated on real noisy images captured by three types of commodity imaging devices, and shows consistently excellent SDN estimation performance. The estimated NLFs are incorporated into two well-known denoising schemes, nonlocal means and BM3D, and show significant improvements in denoising SDN-polluted images.

Effects of atmospheric turbulence on the imaging performance of optical system

NASA Astrophysics Data System (ADS)

Al-Hamadani, Ali H.; Zainulabdeen, Faten Sh.; Karam, Ghada Sabah; Nasir, Eman Yousif; Al-Saedi, Abaas

2018-05-01

Turbulent effects are very complicated and still not entirely understood. Light waves from an astronomical object are distorted as they pass through the atmosphere. The refractive index fluctuations in the turbulent atmosphere induce an optical path difference (OPD) between different parts of the wavefront, distorted wavefronts produce low-quality images and degrade the image beyond the diffraction limit. In this paper the image degradation due to 2-D Gaussian atmospheric turbulence is considered in terms of the point spread function (PSF), and Strehl ratio as an image quality criteria for imaging systems with different apertures using the pupil function teqneque. A general expression for the degraded PSF in the case of circular and square apertures (with half diagonal = √{π/2 } , and 1) diffraction limited and defocused optical system is considered. Based on the derived formula, the effect of the Gaussian atmospheric turbulence on circular and square pupils has been studied with details. Numerical results show that the performance of optical systems with square aperture is more efficient at high levels of atmospheric turbulence than the other apertures.

The practical application of signal detection theory to image quality assessment in x-ray image intensifier-TV fluoroscopy.

PubMed

Marshall, N W

2001-06-01

This paper applies a published version of signal detection theory to x-ray image intensifier fluoroscopy data and compares the results with more conventional subjective image quality measures. An eight-bit digital framestore was used to acquire temporally contiguous frames of fluoroscopy data from which the modulation transfer function (MTF(u)) and noise power spectrum were established. These parameters were then combined to give detective quantum efficiency (DQE(u)) and used in conjunction with signal detection theory to calculate contrast-detail performance. DQE(u) was found to lie between 0.1 and 0.5 for a range of fluoroscopy systems. Two separate image quality experiments were then performed in order to assess the correspondence between the objective and subjective methods. First, image quality for a given fluoroscopy system was studied as a function of doserate using objective parameters and a standard subjective contrast-detail method. Following this, the two approaches were used to assess three different fluoroscopy units. Agreement between objective and subjective methods was good; doserate changes were modelled correctly while both methods ranked the three systems consistently.

Radar Imaging of Spheres in 3D using MUSIC

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

Chambers, D H; Berryman, J G

2003-01-21

We have shown that multiple spheres can be imaged by linear and planar EM arrays using only one component of polarization. The imaging approach involves calculating the SVD of the scattering response matrix, selecting a subset of singular values that represents noise, and evaluating the MUSIC functional. The noise threshold applied to the spectrum of singular values for optimal performance is typically around 1%. The resulting signal subspace includes more than one singular value per sphere. The presence of reflections from the ground improves height localization, even for a linear array parallel to the ground. However, the interference between directmore » and reflected energy modulates the field, creating periodic nulls that can obscure targets in typical images. These nulls are largely eliminated by normalizing the MUSIC functional with the broadside beam pattern of the array. The resulting images show excellent localization for 1 and 2 spheres. The performance for the 3 sphere configurations are complicated by shadowing effects and the greater range of the 3rd sphere in case 2. Two of the three spheres are easily located by MUSIC but the third is difficult to distinguish from other local maxima of the complex imaging functional. Improvement is seen when the linear array is replace with a planar array, which increases the effective aperture height. Further analysis of the singular values and their relationship to modes of scattering from the spheres, as well as better ways to exploit polarization, should improve performance. Work along these lines is currently being pursued by the authors.« less

Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment

PubMed Central

Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann

2010-01-01

Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782

User-oriented evaluation of a medical image retrieval system for radiologists.

PubMed

Markonis, Dimitrios; Holzer, Markus; Baroz, Frederic; De Castaneda, Rafael Luis Ruiz; Boyer, Célia; Langs, Georg; Müller, Henning

2015-10-01

This article reports the user-oriented evaluation of a text- and content-based medical image retrieval system. User tests with radiologists using a search system for images in the medical literature are presented. The goal of the tests is to assess the usability of the system, identify system and interface aspects that need improvement and useful additions. Another objective is to investigate the system's added value to radiology information retrieval. The study provides an insight into required specifications and potential shortcomings of medical image retrieval systems through a concrete methodology for conducting user tests. User tests with a working image retrieval system of images from the biomedical literature were performed in an iterative manner, where each iteration had the participants perform radiology information seeking tasks and then refining the system as well as the user study design itself. During these tasks the interaction of the users with the system was monitored, usability aspects were measured, retrieval success rates recorded and feedback was collected through survey forms. In total, 16 radiologists participated in the user tests. The success rates in finding relevant information were on average 87% and 78% for image and case retrieval tasks, respectively. The average time for a successful search was below 3 min in both cases. Users felt quickly comfortable with the novel techniques and tools (after 5 to 15 min), such as content-based image retrieval and relevance feedback. User satisfaction measures show a very positive attitude toward the system's functionalities while the user feedback helped identifying the system's weak points. The participants proposed several potentially useful new functionalities, such as filtering by imaging modality and search for articles using image examples. The iterative character of the evaluation helped to obtain diverse and detailed feedback on all system aspects. Radiologists are quickly familiar with the functionalities but have several comments on desired functionalities. The analysis of the results can potentially assist system refinement for future medical information retrieval systems. Moreover, the methodology presented as well as the discussion on the limitations and challenges of such studies can be useful for user-oriented medical image retrieval evaluation, as user-oriented evaluation of interactive system is still only rarely performed. Such interactive evaluations can be limited in effort if done iteratively and can give many insights for developing better systems. Copyright © 2015. Published by Elsevier Ireland Ltd.

Introduction to the in orbit test and its performance of the first meteorological imager of the Communication, Ocean, and Meteorological Satellite

NASA Astrophysics Data System (ADS)

Kim, D.; Ahn, M. H.

2013-12-01

The first geostationary earth observation satellite of Korea, named Communication, Ocean, and Meteorological Satellite (COMS), is successfully launched on 27 June 2010 in Korea Standard Time. After arrival of its operational orbit, the satellite underwent in orbit test (IOT) lasting for about 8 months. During the IOT period, the meteorological imager went through tests for its functional and performance demonstration. With the successful acquisition of the first visible channel image, signal chain from the payload to satellite bus and to the ground is also verified. While waiting for the outgassing operation, several functional tests for the payload are also performed. By taking an observation of different sizes of image, of various object targets such as the Sun, moon, and internal calibration target, it has been demonstrated that the payload performs as commanded, satisfying its functional requirements. After successful operation of outgassing which lasted about 40 days, the first set of infrared images is also successfully acquired and the full performance test started. The radiometric performance of the meteorological imager is tested by signal to noise ratio (SNR) for the visible channel, noise equivalent differential temperature (NEdT) for the infrared channels, and pixel to pixel non-uniformity. In case of the visible channel, SNR of all 8 detectors are obtained using the ground measured parameters and background signals obtained in orbit and are larger than 26 at 5% albedo, exceeding the user requirement value of 10 with a significant margin. The values at 100% albedo also meet the user requirements. Also, the relative variability of detector responsivity among the 8 visible channels meets the user requirement, showing values of about 10% of the user requrirement. For the infrared channels, the NEdT of each detector is well within the user requirement and is comparable with or better than the legacy instruments, except the water vapor channel which is slightly noisier than the legacy instruments. The variability of detector responsivity of infrared channels is also below the user requirement, within 40% of the requirement except shortwave infrared channel. The improved performance result is partly due to the stable and low detector temperature obtained with the spacecraft design, by installing a single solar panel to the opposite side of the meteorological imager.

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.

PubMed

Zhou, Yujia; Yap, Pew-Thian; Zhang, Han; Zhang, Lichi; Feng, Qianjin; Shen, Dinggang

2017-09-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Functional MR imaging or Wada test: which is the better predictor of individual postoperative memory outcome?

PubMed

Dupont, Sophie; Duron, Emmanuelle; Samson, Séverine; Denos, Marisa; Volle, Emmanuelle; Delmaire, Christine; Navarro, Vincent; Chiras, Jacques; Lehéricy, Stéphane; Samson, Yves; Baulac, Michel

2010-04-01

To retrospectively determine whether blood oxygen level-dependent functional magnetic resonance (MR) imaging can aid prediction of postoperative memory changes in epileptic patients after temporal lobe surgery. This study was approved by the local ethics committee, and informed consent was obtained from all patients. Data were analyzed from 25 patients (12 women, 13 men; age range, 19-52 years) with refractory epilepsy in whom temporal lobe surgery was performed after they underwent preoperative functional MR imaging, the Wada test, and neuropsychological testing. The functional MR imaging protocol included three different memory tasks (24-hour delayed recognition, encoding, and immediate recognition). Individual activations were measured in medial temporal lobe (MTL) regions of both hemispheres. The prognostic accuracy of functional MR imaging for prediction of postoperative memory changes was compared with the accuracy of the Wada test and preoperative neuropsychological testing by using a backward multiple regression analysis. An equation that was based on left functional MR imaging MTL activation during delayed recognition, side of the epileptic focus, and preoperative global verbal memory score was used to correctly predict worsening of verbal memory in 90% of patients. The right functional MR imaging MTL activation did not substantially correlate with the nonverbal memory outcome, which was only predicted by using the preoperative nonverbal global score. Wada test data were not good predictors of changes in either verbal or nonverbal memory. Findings suggest that functional MR imaging activation during a delayed-recognition task is a better predictor of individual postoperative verbal memory outcome than is the Wada test. RSNA, 2010

Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

PubMed Central

Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

2015-01-01

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

Load Modulation of BOLD Response and Connectivity Predicts Working Memory Performance in Younger and Older Adults

ERIC Educational Resources Information Center

Nagel, Irene E.; Preuschhof, Claudia; Li, Shu-Chen; Nyberg, Lars; Backman, Lars; Lindenberger, Ulman; Heekeren, Hauke R.

2011-01-01

Individual differences in working memory (WM) performance have rarely been related to individual differences in the functional responsivity of the WM brain network. By neglecting person-to-person variation, comparisons of network activity between younger and older adults using functional imaging techniques often confound differences in activity…

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Smart image sensors: an emerging key technology for advanced optical measurement and microsystems

NASA Astrophysics Data System (ADS)

Seitz, Peter

1996-08-01

Optical microsystems typically include photosensitive devices, analog preprocessing circuitry and digital signal processing electronics. The advances in semiconductor technology have made it possible today to integrate all photosensitive and electronical devices on one 'smart image sensor' or photo-ASIC (application-specific integrated circuits containing photosensitive elements). It is even possible to provide each 'smart pixel' with additional photoelectronic functionality, without compromising the fill factor substantially. This technological capability is the basis for advanced cameras and optical microsystems showing novel on-chip functionality: Single-chip cameras with on- chip analog-to-digital converters for less than $10 are advertised; image sensors have been developed including novel functionality such as real-time selectable pixel size and shape, the capability of performing arbitrary convolutions simultaneously with the exposure, as well as variable, programmable offset and sensitivity of the pixels leading to image sensors with a dynamic range exceeding 150 dB. Smart image sensors have been demonstrated offering synchronous detection and demodulation capabilities in each pixel (lock-in CCD), and conventional image sensors are combined with an on-chip digital processor for complete, single-chip image acquisition and processing systems. Technological problems of the monolithic integration of smart image sensors include offset non-uniformities, temperature variations of electronic properties, imperfect matching of circuit parameters, etc. These problems can often be overcome either by designing additional compensation circuitry or by providing digital correction routines. Where necessary for technological or economic reasons, smart image sensors can also be combined with or realized as hybrids, making use of commercially available electronic components. It is concluded that the possibilities offered by custom smart image sensors will influence the design and the performance of future electronic imaging systems in many disciplines, reaching from optical metrology to machine vision on the factory floor and in robotics applications.

The Pan-STARRS PS1 Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Magnier, E.

The Pan-STARRS PS1 Image Processing Pipeline (IPP) performs the image processing and data analysis tasks needed to enable the scientific use of the images obtained by the Pan-STARRS PS1 prototype telescope. The primary goals of the IPP are to process the science images from the Pan-STARRS telescopes and make the results available to other systems within Pan-STARRS. It also is responsible for combining all of the science images in a given filter into a single representation of the non-variable component of the night sky defined as the "Static Sky". To achieve these goals, the IPP also performs other analysis functions to generate the calibrations needed in the science image processing, and to occasionally use the derived data to generate improved astrometric and photometric reference catalogs. It also provides the infrastructure needed to store the incoming data and the resulting data products. The IPP inherits lessons learned, and in some cases code and prototype code, from several other astronomy image analysis systems, including Imcat (Kaiser), the Sloan Digital Sky Survey (REF), the Elixir system (Magnier & Cuillandre), and Vista (Tonry). Imcat and Vista have a large number of robust image processing functions. SDSS has demonstrated a working analysis pipeline and large-scale databasesystem for a dedicated project. The Elixir system has demonstrated an automatic image processing system and an object database system for operational usage. This talk will present an overview of the IPP architecture, functional flow, code development structure, and selected analysis algorithms. Also discussed is the HW highly parallel HW configuration necessary to support PS1 operational requirements. Finally, results are presented of the processing of images collected during PS1 early commissioning tasks utilizing the Pan-STARRS Test Camera #3.

Low-dose 4D cardiac imaging in small animals using dual source micro-CT

NASA Astrophysics Data System (ADS)

Holbrook, M.; Clark, D. P.; Badea, C. T.

2018-01-01

Micro-CT is widely used in preclinical studies, generating substantial interest in extending its capabilities in functional imaging applications such as blood perfusion and cardiac function. However, imaging cardiac structure and function in mice is challenging due to their small size and rapid heart rate. To overcome these challenges, we propose and compare improvements on two strategies for cardiac gating in dual-source, preclinical micro-CT: fast prospective gating (PG) and uncorrelated retrospective gating (RG). These sampling strategies combined with a sophisticated iterative image reconstruction algorithm provide faster acquisitions and high image quality in low-dose 4D (i.e. 3D  +  Time) cardiac micro-CT. Fast PG is performed under continuous subject rotation which results in interleaved projection angles between cardiac phases. Thus, fast PG provides a well-sampled temporal average image for use as a prior in iterative reconstruction. Uncorrelated RG incorporates random delays during sampling to prevent correlations between heart rate and sampling rate. We have performed both simulations and animal studies to validate these new sampling protocols. Sampling times for 1000 projections using fast PG and RG were 2 and 3 min, respectively, and the total dose was 170 mGy each. Reconstructions were performed using a 4D iterative reconstruction technique based on the split Bregman method. To examine undersampling robustness, subsets of 500 and 250 projections were also used for reconstruction. Both sampling strategies in conjunction with our iterative reconstruction method are capable of resolving cardiac phases and provide high image quality. In general, for equal numbers of projections, fast PG shows fewer errors than RG and is more robust to undersampling. Our results indicate that only 1000-projection based reconstruction with fast PG satisfies a 5% error criterion in left ventricular volume estimation. These methods promise low-dose imaging with a wide range of preclinical applications in cardiac imaging.

Imaging strategies using focusing functions with applications to a North Sea field

NASA Astrophysics Data System (ADS)

da Costa Filho, C. A.; Meles, G. A.; Curtis, A.; Ravasi, M.; Kritski, A.

2018-04-01

Seismic methods are used in a wide variety of contexts to investigate subsurface Earth structures, and to explore and monitor resources and waste-storage reservoirs in the upper ˜100 km of the Earth's subsurface. Reverse-time migration (RTM) is one widely used seismic method which constructs high-frequency images of subsurface structures. Unfortunately, RTM has certain disadvantages shared with other conventional single-scattering-based methods, such as not being able to correctly migrate multiply scattered arrivals. In principle, the recently developed Marchenko methods can be used to migrate all orders of multiples correctly. In practice however, using Marchenko methods are costlier to compute than RTM—for a single imaging location, the cost of performing the Marchenko method is several times that of standard RTM, and performing RTM itself requires dedicated use of some of the largest computers in the world for individual data sets. A different imaging strategy is therefore required. We propose a new set of imaging methods which use so-called focusing functions to obtain images with few artifacts from multiply scattered waves, while greatly reducing the number of points across the image at which the Marchenko method need be applied. Focusing functions are outputs of the Marchenko scheme: they are solutions of wave equations that focus in time and space at particular surface or subsurface locations. However, they are mathematical rather than physical entities, being defined only in reference media that equal to the true Earth above their focusing depths but are homogeneous below. Here, we use these focusing functions as virtual source/receiver surface seismic surveys, the upgoing focusing function being the virtual received wavefield that is created when the downgoing focusing function acts as a spatially distributed source. These source/receiver wavefields are used in three imaging schemes: one allows specific individual reflectors to be selected and imaged. The other two schemes provide either targeted or complete images with distinct advantages over current RTM methods, such as fewer artifacts and artifacts that occur in different locations. The latter property allows the recently published `combined imaging' method to remove almost all artifacts. We show several examples to demonstrate the methods: acoustic 1-D and 2-D synthetic examples, and a 2-D line from an ocean bottom cable field data set. We discuss an extension to elastic media, which is illustrated by a 1.5-D elastic synthetic example.

Functional Trajectories, Cognition, and Subclinical Cerebrovascular Disease.

PubMed

Dhamoon, Mandip S; Cheung, Ying-Kuen; Gutierrez, Jose; Moon, Yeseon P; Sacco, Ralph L; Elkind, Mitchell S V; Wright, Clinton B

2018-03-01

Cognition and education influence functional trajectories, but whether associations differ with subclinical brain infarcts (SBI) or white matter hyperintensity volume (WMHV) is unknown. We hypothesized that SBI and WMHV moderated relationships between cognitive performance and education and functional trajectories. A total of 1290 stroke-free individuals underwent brain magnetic resonance imaging and were followed for 7.3 years (mean) with annual functional assessments with the Barthel index (range, 0-100). Magnetic resonance imaging measurements included pathology-informed SBI (PI-SBI) and WMHV (% total cranial volume). Generalized estimating equation models tested associations between magnetic resonance imaging variables and baseline Barthel index and change in Barthel index, adjusting for demographic, vascular, cognitive, and social risk factors, and stroke and myocardial infarction during follow-up. We tested interactions among education level, baseline cognitive performance (Mini-Mental State score), and functional trajectories and ran models stratified by levels of magnetic resonance imaging variables. Mean age was 70.6 (SD, 9.0) years; 19% had PI-SBI, and mean WMHV was 0.68%. Education did not modify associations between cognition and functional trajectories. PI-SBI modified associations between cognition and functional trajectories ( P =0.04) with a significant protective effect of better cognition on functional decline seen only in those without PI-SBI. There was no significant interaction for WMHV ( P =0.8). PI-SBI, and greater WMHV, were associated with 2- to 3-fold steeper functional decline, holding cognition constant. PI-SBI moderated the association between cognition and functional trajectories, with 3-fold greater decline among those with PI-SBI (compared with no PI-SBI) and normal baseline cognition. This highlights the strong and independent association between subclinical markers and patient-centered trajectories over time. © 2018 American Heart Association, Inc.

Image quality enhancement method for on-orbit remote sensing cameras using invariable modulation transfer function.

PubMed

Li, Jin; Liu, Zilong

2017-07-24

Remote sensing cameras in the visible/near infrared range are essential tools in Earth-observation, deep-space exploration, and celestial navigation. Their imaging performance, i.e. image quality here, directly determines the target-observation performance of a spacecraft, and even the successful completion of a space mission. Unfortunately, the camera itself, such as a optical system, a image sensor, and a electronic system, limits the on-orbit imaging performance. Here, we demonstrate an on-orbit high-resolution imaging method based on the invariable modulation transfer function (IMTF) of cameras. The IMTF, which is stable and invariable to the changing of ground targets, atmosphere, and environment on orbit or on the ground, depending on the camera itself, is extracted using a pixel optical focal-plane (PFP). The PFP produces multiple spatial frequency targets, which are used to calculate the IMTF at different frequencies. The resulting IMTF in combination with a constrained least-squares filter compensates for the IMTF, which represents the removal of the imaging effects limited by the camera itself. This method is experimentally confirmed. Experiments on an on-orbit panchromatic camera indicate that the proposed method increases 6.5 times of the average gradient, 3.3 times of the edge intensity, and 1.56 times of the MTF value compared to the case when IMTF is not used. This opens a door to push the limitation of a camera itself, enabling high-resolution on-orbit optical imaging.

Practical implementation of channelized hotelling observers: effect of ROI size

NASA Astrophysics Data System (ADS)

Ferrero, Andrea; Favazza, Christopher P.; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

2017-03-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

Practical implementation of Channelized Hotelling Observers: Effect of ROI size.

PubMed

Ferrero, Andrea; Favazza, Christopher P; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H

2017-03-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

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

Samei, Ehsan, E-mail: samei@duke.edu; Richard, Samuel

2015-01-15

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD,more » Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.« less

Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

PubMed

Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer

2014-01-01

Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

Hard copies for digital medical images: an overview

NASA Astrophysics Data System (ADS)

Blume, Hartwig R.; Muka, Edward

1995-04-01

This paper is a condensed version of an invited overview on the technology of film hard-copies used in radiology. Because the overview was given to an essentially nonmedical audience, the reliance on film hard-copies in radiology is outlined in greater detail. The overview is concerned with laser image recorders generating monochrome prints on silver-halide films. The basic components of laser image recorders are sketched. The paper concentrates on the physical parameters - characteristic function, dynamic range, digitization resolution, modulation transfer function, and noise power spectrum - which define image quality and information transfer capability of the printed image. A preliminary approach is presented to compare the printed image quality with noise in the acquired image as well as with the noise of state-of- the-art cathode-ray-tube display systems. High-performance laser-image- recorder/silver-halide-film/light-box systems are well capable of reproducing acquired radiologic information. Most recently development was begun toward a display function standard for soft-copy display systems to facilitate similarity of image presentation between different soft-copy displays as well as between soft- and hard-copy displays. The standard display function is based on perceptional linearization. The standard is briefly reviewed to encourage the printer industry to adopt it, too.

Stripe nonuniformity correction for infrared imaging system based on single image optimization

NASA Astrophysics Data System (ADS)

Hua, Weiping; Zhao, Jufeng; Cui, Guangmang; Gong, Xiaoli; Ge, Peng; Zhang, Jiang; Xu, Zhihai

2018-06-01

Infrared imaging is often disturbed by stripe nonuniformity noise. Scene-based correction method can effectively reduce the impact of stripe noise. In this paper, a stripe nonuniformity correction method based on differential constraint is proposed. Firstly, the gray distribution of stripe nonuniformity is analyzed and the penalty function is constructed by the difference of horizontal gradient and vertical gradient. With the weight function, the penalty function is optimized to obtain the corrected image. Comparing with other single-frame approaches, experiments show that the proposed method performs better in both subjective and objective analysis, and does less damage to edge and detail. Meanwhile, the proposed method runs faster. We have also discussed the differences between the proposed idea and multi-frame methods. Our method is finally well applied in hardware system.

Visually enhanced CCTV digital surveillance utilizing Intranet and Internet.

PubMed

Ozaki, Nobuyuki

2002-07-01

This paper describes a solution for integrated plant supervision utilizing closed circuit television (CCTV) digital surveillance. Three basic requirements are first addressed as the platform of the system, with discussion on the suitable video compression. The system configuration is described in blocks. The system provides surveillance functionality: real-time monitoring, and process analysis functionality: a troubleshooting tool. This paper describes the formulation of practical performance design for determining various encoder parameters. It also introduces image processing techniques for enhancing the original CCTV digital image to lessen the burden on operators. Some screenshots are listed for the surveillance functionality. For the process analysis, an image searching filter supported by image processing techniques is explained with screenshots. Multimedia surveillance, which is the merger with process data surveillance, or the SCADA system, is also explained.

Blind deconvolution of astronomical images with band limitation determined by optical system parameters

NASA Astrophysics Data System (ADS)

Luo, L.; Fan, M.; Shen, M. Z.

2007-07-01

Atmospheric turbulence greatly limits the spatial resolution of astronomical images acquired by the large ground-based telescope. The record image obtained from telescope was thought as a convolution result of the object function and the point spread function. The statistic relationship of the images measured data, the estimated object and point spread function was in accord with the Bayes conditional probability distribution, and the maximum-likelihood formulation was found. A blind deconvolution approach based on the maximum-likelihood estimation technique with real optical band limitation constraint is presented for removing the effect of atmospheric turbulence on this class images through the minimization of the convolution error function by use of the conjugation gradient optimization algorithm. As a result, the object function and the point spread function could be estimated from a few record images at the same time by the blind deconvolution algorithm. According to the principle of Fourier optics, the relationship between the telescope optical system parameters and the image band constraint in the frequency domain was formulated during the image processing transformation between the spatial domain and the frequency domain. The convergence of the algorithm was increased by use of having the estimated function variable (also is the object function and the point spread function) nonnegative and the point-spread function band limited. Avoiding Fourier transform frequency components beyond the cut off frequency lost during the image processing transformation when the size of the sampled image data, image spatial domain and frequency domain were the same respectively, the detector element (e.g. a pixels in the CCD) should be less than the quarter of the diffraction speckle diameter of the telescope for acquiring the images on the focal plane. The proposed method can easily be applied to the case of wide field-view turbulent-degraded images restoration because of no using the object support constraint in the algorithm. The performance validity of the method is examined by the computer simulation and the restoration of the real Alpha Psc astronomical image data. The results suggest that the blind deconvolution with the real optical band constraint can remove the effect of the atmospheric turbulence on the observed images and the spatial resolution of the object image can arrive at or exceed the diffraction-limited level.

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

PubMed

Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

2017-12-01

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

Reliability of functional MR imaging with word-generation tasks for mapping Broca's area.

PubMed

Brannen, J H; Badie, B; Moritz, C H; Quigley, M; Meyerand, M E; Haughton, V M

2001-10-01

Functional MR (fMR) imaging of word generation has been used to map Broca's area in some patients selected for craniotomy. The purpose of this study was to measure the reliability, precision, and accuracy of word-generation tasks to identify Broca's area. The Brodmann areas activated during performance of word-generation tasks were tabulated in 34 consecutive patients referred for fMR imaging mapping of language areas. In patients performing two iterations of the letter word-generation tasks, test-retest reliability was quantified by using the concurrence ratio (CR), or the number of voxels activated by each iteration in proportion to the average number of voxels activated from both iterations of the task. Among patients who also underwent category or antonym word generation or both, the similarity of the activation from each task was assessed with the CR. In patients who underwent electrocortical stimulation (ECS) mapping of speech function during craniotomy while awake, the sites with speech function were compared with the locations of activation found during fMR imaging of word generation. In 31 of 34 patients, activation was identified in the inferior frontal gyri or middle frontal gyri or both in Brodmann areas 9, 44, 45, or 46, unilaterally or bilaterally, with one or more of the tasks. Activation was noted in the same gyri when the patient performed a second iteration of the letter word-generation task or second task. The CR for pixel precision in a single section averaged 49%. In patients who underwent craniotomy while awake, speech areas located with ECS coincided with areas of the brain activated during a word-generation task. fMR imaging with word-generation tasks produces technically satisfactory maps of Broca's area, which localize the area accurately and reliably.

COBRA: A prospective multimodal imaging study of dopamine, brain structure and function, and cognition.

PubMed

Nevalainen, N; Riklund, K; Andersson, M; Axelsson, J; Ögren, M; Lövdén, M; Lindenberger, U; Bäckman, L; Nyberg, L

2015-07-01

Cognitive decline is a characteristic feature of normal human aging. Previous work has demonstrated marked interindividual variability in onset and rate of decline. Such variability has been linked to factors such as maintenance of functional and structural brain integrity, genetics, and lifestyle. Still, few, if any, studies have combined a longitudinal design with repeated multimodal imaging and a comprehensive assessment of cognition as well as genetic and lifestyle factors. The present paper introduces the Cognition, Brain, and Aging (COBRA) study, in which cognitive performance and brain structure and function are measured in a cohort of 181 older adults aged 64 to 68 years at baseline. Participants will be followed longitudinally over a 10-year period, resulting in a total of three equally spaced measurement occasions. The measurement protocol at each occasion comprises a comprehensive set of behavioral and imaging measures. Cognitive performance is evaluated via computerized testing of working memory, episodic memory, perceptual speed, motor speed, implicit sequence learning, and vocabulary. Brain imaging is performed using positron emission tomography with [(11)C]-raclopride to assess dopamine D2/D3 receptor availability. Structural magnetic resonance imaging (MRI) is used for assessment of white and gray-matter integrity and cerebrovascular perfusion, and functional MRI maps brain activation during rest and active task conditions. Lifestyle descriptives are collected, and blood samples are obtained and stored for future evaluation. Here, we present selected results from the baseline assessment along with a discussion of sample characteristics and methodological considerations that determined the design of the study. This article is part of a Special Issue entitled SI: Memory & Aging. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Concurrent application of TMS and near-infrared optical imaging: methodological considerations and potential artifacts

PubMed Central

Parks, Nathan A.

2013-01-01

The simultaneous application of transcranial magnetic stimulation (TMS) with non-invasive neuroimaging provides a powerful method for investigating functional connectivity in the human brain and the causal relationships between areas in distributed brain networks. TMS has been combined with numerous neuroimaging techniques including, electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). Recent work has also demonstrated the feasibility and utility of combining TMS with non-invasive near-infrared optical imaging techniques, functional near-infrared spectroscopy (fNIRS) and the event-related optical signal (EROS). Simultaneous TMS and optical imaging affords a number of advantages over other neuroimaging methods but also involves a unique set of methodological challenges and considerations. This paper describes the methodology of concurrently performing optical imaging during the administration of TMS, focusing on experimental design, potential artifacts, and approaches to controlling for these artifacts. PMID:24065911

Fourier analysis: from cloaking to imaging

NASA Astrophysics Data System (ADS)

Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping

2016-04-01

Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

Attentional and physiological processing of food images in functional dyspepsia patients: A pilot study.

PubMed

Lee, In-Seon; Preissl, Hubert; Giel, Katrin; Schag, Kathrin; Enck, Paul

2018-01-23

The food-related behavior of functional dyspepsia has been attracting more interest of late. This pilot study aims to provide evidence of the physiological, emotional, and attentional aspects of food processing in functional dyspepsia patients. The study was performed in 15 functional dyspepsia patients and 17 healthy controls after a standard breakfast. We measured autonomic nervous system activity using skin conductance response and heart rate variability, emotional response using facial electromyography, and visual attention using eyetracking during the visual stimuli of food/non-food images. In comparison to healthy controls, functional dyspepsia patients showed a greater craving for food, a decreased intake of food, more dyspeptic symptoms, lower pleasantness rating of food images (particularly of high fat), decreased low frequency/high frequency ratio of heart rate variability, and suppressed total processing time of food images. There were no significant differences of skin conductance response and facial electromyography data between groups. The results suggest that high level cognitive functions rather than autonomic and emotional mechanisms are more liable to function differently in functional dyspepsia patients. Abnormal dietary behavior, reduced subjective rating of pleasantness and visual attention to food should be considered as important pathophysiological characteristics in functional dyspepsia.

The potential of multiparametric MRI of the breast

PubMed Central

Pinker, Katja; Helbich, Thomas H

2017-01-01

MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5–7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer. PMID:27805423

Brain structure and executive functions in children with cerebral palsy: a systematic review.

PubMed

Weierink, Lonneke; Vermeulen, R Jeroen; Boyd, Roslyn N

2013-05-01

This systematic review aimed to establish the current knowledge about brain structure and executive function (EF) in children with cerebral palsy (CP). Five databases were searched (up till July 2012). Six articles met the inclusion criteria, all included structural brain imaging though no functional brain imaging. Study quality was assessed using the STROBE checklist. All articles scored between 58.7% and 70.5% for quality (100% is the maximum score). The included studies all reported poorer performance on EF tasks for children with CP compared to children without CP. For the selected EF measures non-significant effect sizes were found for the CP group compared to a semi-control group (children without cognitive deficits but not included in a control group). This could be due to the small sample sizes, group heterogeneity and lack of comparison of the CP group to typically developing children. The included studies did not consider specific brain areas associated with EF performance. To conclude, there is a paucity of brain imaging studies focused on EF in children with CP, especially of studies that include functional brain imaging. Outcomes of the present studies are difficult to compare as each study included different EF measures and cortical abnormality measures. Copyright © 2013 Elsevier Ltd. All rights reserved.

The use of algorithmic behavioural transfer functions in parametric EO system performance models

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.

2015-10-01

The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach and architecture are described in detail, and example results based on a practical application are then given which illustrate the performance benefits. Finally, conclusions are drawn and comments given regarding the benefits and uses of the new approach.

An integral design strategy combining optical system and image processing to obtain high resolution images

NASA Astrophysics Data System (ADS)

Wang, Jiaoyang; Wang, Lin; Yang, Ying; Gong, Rui; Shao, Xiaopeng; Liang, Chao; Xu, Jun

2016-05-01

In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.

Unsupervised texture image segmentation by improved neural network ART2

NASA Technical Reports Server (NTRS)

Wang, Zhiling; Labini, G. Sylos; Mugnuolo, R.; Desario, Marco

1994-01-01

We here propose a segmentation algorithm of texture image for a computer vision system on a space robot. An improved adaptive resonance theory (ART2) for analog input patterns is adapted to classify the image based on a set of texture image features extracted by a fast spatial gray level dependence method (SGLDM). The nonlinear thresholding functions in input layer of the neural network have been constructed by two parts: firstly, to reduce the effects of image noises on the features, a set of sigmoid functions is chosen depending on the types of the feature; secondly, to enhance the contrast of the features, we adopt fuzzy mapping functions. The cluster number in output layer can be increased by an autogrowing mechanism constantly when a new pattern happens. Experimental results and original or segmented pictures are shown, including the comparison between this approach and K-means algorithm. The system written in C language is performed on a SUN-4/330 sparc-station with an image board IT-150 and a CCD camera.

Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis

NASA Astrophysics Data System (ADS)

Ikejimba, Lynda; Kiarashi, Nooshin; Lin, Yuan; Chen, Baiyu; Ghate, Sujata V.; Zerhouni, Moustafa; Samei, Ehsan; Lo, Joseph Y.

2012-03-01

Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique that provides 3D structural information of the breast. In contrast to 2D mammography, DBT minimizes tissue overlap potentially improving cancer detection and reducing number of unnecessary recalls. The addition of a contrast agent to DBT and mammography for lesion enhancement has the benefit of providing functional information of a lesion, as lesion contrast uptake and washout patterns may help differentiate between benign and malignant tumors. This study used a task-based method to determine the optimal imaging approach by analyzing six imaging paradigms in terms of their ability to resolve iodine at a given dose: contrast enhanced mammography and tomosynthesis, temporal subtraction mammography and tomosynthesis, and dual energy subtraction mammography and tomosynthesis. Imaging performance was characterized using a detectability index d', derived from the system task transfer function (TTF), an imaging task, iodine contrast, and the noise power spectrum (NPS). The task modeled a 5 mm lesion containing iodine concentrations between 2.1 mg/cc and 8.6 mg/cc. TTF was obtained using an edge phantom, and the NPS was measured over several exposure levels, energies, and target-filter combinations. Using a structured CIRS phantom, d' was generated as a function of dose and iodine concentration. In general, higher dose gave higher d', but for the lowest iodine concentration and lowest dose, dual energy subtraction tomosynthesis and temporal subtraction tomosynthesis demonstrated the highest performance.

Worsening respiratory function in mechanically ventilated intensive care patients: feasibility and value of xenon-enhanced dual energy CT.

PubMed

Hoegl, Sandra; Meinel, Felix G; Thieme, Sven F; Johnson, Thorsten R C; Eickelberg, Oliver; Zwissler, Bernhard; Nikolaou, Konstantin

2013-03-01

To evaluate the feasibility and incremental diagnostic value of xenon-enhanced dual-energy CT in mechanically ventilated intensive care patients with worsening respiratory function. The study was performed in 13 mechanically ventilated patients with severe pulmonary conditions (acute respiratory distress syndrome (ARDS), n=5; status post lung transplantation, n=5; other, n=3) and declining respiratory function. CT scans were performed using a dual-source CT scanner at an expiratory xenon concentration of 30%. Both ventilation images (Xe-DECT) and standard CT images were reconstructed from a single CT scan. Findings were recorded for Xe-DECT and standard CT images separately. Ventilation defects on xenon images were matched to morphological findings on standard CT images and incremental diagnostic information of xenon ventilation images was recorded if present. Mean xenon consumption was 2.95 l per patient. No adverse events occurred under xenon inhalation. In the visual CT analysis, the Xe-DECT ventilation defects matched with pathologic changes in lung parenchyma seen in the standard CT images in all patients. Xe-DECT provided additional diagnostic findings in 4/13 patients. These included preserved ventilation despite early pneumonia (n=1), more confident discrimination between a large bulla and pneumothorax (n=1), detection of an airway-to-pneumothorax fistula (n=1) and exclusion of a suspected airway-to-mediastinum fistula (n=1). In all 4 patients, the additional findings had a substantial impact on patients' management. Xenon-enhanced DECT is safely feasible and can add relevant diagnostic information in mechanically ventilated intensive care patients with worsening respiratory function. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

An improved artifact removal in exposure fusion with local linear constraints

NASA Astrophysics Data System (ADS)

Zhang, Hai; Yu, Mali

2018-04-01

In exposure fusion, it is challenging to remove artifacts because of camera motion and moving objects in the scene. An improved artifact removal method is proposed in this paper, which performs local linear adjustment in artifact removal progress. After determining a reference image, we first perform high-dynamic-range (HDR) deghosting to generate an intermediate image stack from the input image stack. Then, a linear Intensity Mapping Function (IMF) in each window is extracted based on the intensities of intermediate image and reference image, the intensity mean and variance of reference image. Finally, with the extracted local linear constraints, we reconstruct a target image stack, which can be directly used for fusing a single HDR-like image. Some experiments have been implemented and experimental results demonstrate that the proposed method is robust and effective in removing artifacts especially in the saturated regions of the reference image.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.

PubMed

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-10-01

Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy

PubMed Central

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-01-01

Abstract. Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images. PMID:26157980

Review of free software tools for image analysis of fluorescence cell micrographs.

PubMed

Wiesmann, V; Franz, D; Held, C; Münzenmayer, C; Palmisano, R; Wittenberg, T

2015-01-01

An increasing number of free software tools have been made available for the evaluation of fluorescence cell micrographs. The main users are biologists and related life scientists with no or little knowledge of image processing. In this review, we give an overview of available tools and guidelines about which tools the users should use to segment fluorescence micrographs. We selected 15 free tools and divided them into stand-alone, Matlab-based, ImageJ-based, free demo versions of commercial tools and data sharing tools. The review consists of two parts: First, we developed a criteria catalogue and rated the tools regarding structural requirements, functionality (flexibility, segmentation and image processing filters) and usability (documentation, data management, usability and visualization). Second, we performed an image processing case study with four representative fluorescence micrograph segmentation tasks with figure-ground and cell separation. The tools display a wide range of functionality and usability. In the image processing case study, we were able to perform figure-ground separation in all micrographs using mainly thresholding. Cell separation was not possible with most of the tools, because cell separation methods are provided only by a subset of the tools and are difficult to parametrize and to use. Most important is that the usability matches the functionality of a tool. To be usable, specialized tools with less functionality need to fulfill less usability criteria, whereas multipurpose tools need a well-structured menu and intuitive graphical user interface. © 2014 Fraunhofer-Institute for Integrated Circuits IIS Journal of Microscopy © 2014 Royal Microscopical Society.

Human brain activity with functional NIR optical imager

NASA Astrophysics Data System (ADS)

Luo, Qingming

2001-08-01

In this paper we reviewed the applications of functional near infrared optical imager in human brain activity. Optical imaging results of brain activity, including memory for new association, emotional thinking, mental arithmetic, pattern recognition ' where's Waldo?, occipital cortex in visual stimulation, and motor cortex in finger tapping, are demonstrated. It is shown that the NIR optical method opens up new fields of study of the human population, in adults under conditions of simulated or real stress that may have important effects upon functional performance. It makes practical and affordable for large populations the complex technology of measuring brain function. It is portable and low cost. In cognitive tasks subjects could report orally. The temporal resolution could be millisecond or less in theory. NIR method will have good prospects in exploring human brain secret.

Regularized magnetotelluric inversion based on a minimum support gradient stabilizing functional

NASA Astrophysics Data System (ADS)

Xiang, Yang; Yu, Peng; Zhang, Luolei; Feng, Shaokong; Utada, Hisashi

2017-11-01

Regularization is used to solve the ill-posed problem of magnetotelluric inversion usually by adding a stabilizing functional to the objective functional that allows us to obtain a stable solution. Among a number of possible stabilizing functionals, smoothing constraints are most commonly used, which produce spatially smooth inversion results. However, in some cases, the focused imaging of a sharp electrical boundary is necessary. Although past works have proposed functionals that may be suitable for the imaging of a sharp boundary, such as minimum support and minimum gradient support (MGS) functionals, they involve some difficulties and limitations in practice. In this paper, we propose a minimum support gradient (MSG) stabilizing functional as another possible choice of focusing stabilizer. In this approach, we calculate the gradient of the model stabilizing functional of the minimum support, which affects both the stability and the sharp boundary focus of the inversion. We then apply the discrete weighted matrix form of each stabilizing functional to build a unified form of the objective functional, allowing us to perform a regularized inversion with variety of stabilizing functionals in the same framework. By comparing the one-dimensional and two-dimensional synthetic inversion results obtained using the MSG stabilizing functional and those obtained using other stabilizing functionals, we demonstrate that the MSG results are not only capable of clearly imaging a sharp geoelectrical interface but also quite stable and robust. Overall good performance in terms of both data fitting and model recovery suggests that this stabilizing functional is effective and useful in practical applications.[Figure not available: see fulltext.

Transesophageal Speckle-Tracking Echocardiography Improves Right Ventricular Systolic Function Assessment in the Perioperative Setting.

PubMed

Markin, Nicholas W; Chamsi-Pasha, Mohammed; Luo, Jiangtao; Thomas, Walker R; Brakke, Tara R; Porter, Thomas R; Shillcutt, Sasha K

2017-02-01

Perioperative evaluation of right ventricular (RV) systolic function is important to follow intraoperative changes, but it is often not possible to assess with transthoracic echocardiographic (TTE) imaging, because of surgical field constraints. Echocardiographic RV quantification is most commonly performed using tricuspid annular plane systolic excursion (TAPSE), but it is not clear whether this method works with transesophageal echocardiographic (TEE) imaging. This study was performed to evaluate the relationship between TTE and TEE TAPSE distances measured with M-mode imaging and in comparison with speckle-tracking TTE and TEE measurements. Prospective observational TTE and TEE imaging was performed during elective cardiac surgical procedures in 100 subjects. Speckle-tracking echocardiographic TAPSE distances were determined and compared with the TTE M-mode TAPSE standard. Both an experienced and an inexperienced user of the speckle-tracking echocardiographic software evaluated the images, to enable interobserver assessment in 84 subjects. The comparison between TTE M-mode TAPSE and TEE M-mode TAPSE demonstrated significant variability, with a Spearman correlation of 0.5 and a mean variance in measurement of 6.5 mm. There was equivalence within data pairs and correlations between TTE M-mode TAPSE and both speckle-tracking TTE and speckle-tracking TEE TAPSE, with Spearman correlations of 0.65 and 0.65, respectively. The average variance in measurement was 0.6 mm for speckle-tracking TTE TAPSE and 1.5 mm for speckle-tracking TEE TAPSE. Using TTE M-mode TAPSE as a control, TEE M-mode TAPSE results are not accurate and should not be used clinically to evaluate RV systolic function. The relationship between speckle-tracking echocardiographic TAPSE and TTE M-mode TAPSE suggests that in the perioperative setting, speckle-tracking TEE TAPSE might be used to quantitatively evaluate RV systolic function in the absence of TTE imaging. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

Development of a Mars Surface Imager

NASA Technical Reports Server (NTRS)

Squyres, Steve W.

1994-01-01

The Mars Surface Imager (MSI) is a multispectral, stereoscopic, panoramic imager that allows imaging of the full scene around a Mars lander from the lander body to the zenith. It has two functional components: panoramic imaging and sky imaging. In the most recent version of the MSI, called PIDDP-cam, a very long multi-line color CCD, an innovative high-performance drive system, and a state-of-the-art wavelet image compression code have been integrated into a single package. The requirements for the flight version of the MSI and the current design are presented.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Visual performance-based image enhancement methodology: an investigation of contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Neriani, Kelly E.; Herbranson, Travis J.; Reis, George A.; Pinkus, Alan R.; Goodyear, Charles D.

2006-05-01

While vast numbers of image enhancing algorithms have already been developed, the majority of these algorithms have not been assessed in terms of their visual performance-enhancing effects using militarily relevant scenarios. The goal of this research was to apply a visual performance-based assessment methodology to evaluate six algorithms that were specifically designed to enhance the contrast of digital images. The image enhancing algorithms used in this study included three different histogram equalization algorithms, the Autolevels function, the Recursive Rational Filter technique described in Marsi, Ramponi, and Carrato1 and the multiscale Retinex algorithm described in Rahman, Jobson and Woodell2. The methodology used in the assessment has been developed to acquire objective human visual performance data as a means of evaluating the contrast enhancement algorithms. Objective performance metrics, response time and error rate, were used to compare algorithm enhanced images versus two baseline conditions, original non-enhanced images and contrast-degraded images. Observers completed a visual search task using a spatial-forcedchoice paradigm. Observers searched images for a target (a military vehicle) hidden among foliage and then indicated in which quadrant of the screen the target was located. Response time and percent correct were measured for each observer. Results of the study and future directions are discussed.

Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

PubMed

Weng, Hsu-Huei; Noll, Kyle R; Johnson, Jason M; Prabhu, Sujit S; Tsai, Yuan-Hsiung; Chang, Sheng-Wei; Huang, Yen-Chu; Lee, Jiann-Der; Yang, Jen-Tsung; Yang, Cheng-Ta; Tsai, Ying-Huang; Yang, Chun-Yuh; Hazle, John D; Schomer, Donald F; Liu, Ho-Ling

2018-02-01

Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. © RSNA, 2017 Online supplemental material is available for this article.

Influence of speckle image reconstruction on photometric precision for large solar telescopes

NASA Astrophysics Data System (ADS)

Peck, C. L.; Wöger, F.; Marino, J.

2017-11-01

Context. High-resolution observations from large solar telescopes require adaptive optics (AO) systems to overcome image degradation caused by Earth's turbulent atmosphere. AO corrections are, however, only partial. Achieving near-diffraction limited resolution over a large field of view typically requires post-facto image reconstruction techniques to reconstruct the source image. Aims: This study aims to examine the expected photometric precision of amplitude reconstructed solar images calibrated using models for the on-axis speckle transfer functions and input parameters derived from AO control data. We perform a sensitivity analysis of the photometric precision under variations in the model input parameters for high-resolution solar images consistent with four-meter class solar telescopes. Methods: Using simulations of both atmospheric turbulence and partial compensation by an AO system, we computed the speckle transfer function under variations in the input parameters. We then convolved high-resolution numerical simulations of the solar photosphere with the simulated atmospheric transfer function, and subsequently deconvolved them with the model speckle transfer function to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. Results: The analysis demonstrates that high photometric precision can be obtained for speckle amplitude reconstruction using speckle transfer function models combined with AO-derived input parameters. Additionally, it shows that the reconstruction is most sensitive to the input parameter that characterizes the atmospheric distortion, and sub-2% photometric precision is readily obtained when it is well estimated.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions.

PubMed

Jha, Abhinav K; Barrett, Harrison H; Frey, Eric C; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A

2015-09-21

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions

NASA Astrophysics Data System (ADS)

Jha, Abhinav K.; Barrett, Harrison H.; Frey, Eric C.; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A.

2015-09-01

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

NASA Astrophysics Data System (ADS)

Du, Peijun; Tan, Kun; Xing, Xiaoshi

2010-12-01

Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

Poster - Thur Eve - 16: Four-dimensional x-ray computed tomography and hyperpolarized 3 He magnetic resonance imaging of gas distribution in lung cancer.

PubMed

Mathew, L; Castillo, R; Castillo, E; Yaremko, B; Rodrigues, G; Etemad-Rezai, R; Guerrero, T; Parraga, G

2012-07-01

Dynamic imaging methods such as four-dimensional computed tomography (4DCT) and static imaging methods such as noble gas magnetic resonance imaging (MRI) deliver direct and regional measurements of lung function even in lung cancer patients in whom global lung function measurements are dominated by tumour burden. The purpose of this study was to directly compare quantitative measurements of gas distribution from static hyperpolarized 3 He MRI and dynamic 4DCT in a small group of lung cancer patients. MRI and 4DCT were performed in 11 subjects prior to radiation therapy. MRI was performed at 3.0T in breath-hold after inhalation 1L of hyperpolarized 3 He gas. Gas distribution in 3 He MRI was quantified using a semi-automated segmentation algorithm to generate percent-ventilated volume (PVV), reflecting the volume of gas in the lung normalized to the thoracic cavity volume. 4DCT pulmonary function maps were generated using deformable image registration of six expiratory phase images. The correspondence between identical tissue elements at inspiratory and expiratory phases was used to estimate regional gas distribution and PVV was quantified from these images. After accounting for differences in lung volumes between 3 He MRI (1.9±0.5L ipsilateral, 2.3±0.7 contralateral) and 4DCT (1.2±0.3L ipsilateral, 1.3±0.4L contralateral) during image acquisition, there was no statistically significant difference in PVV between 3 He MRI (72±11% ipsilateral, 79±12% contralateral) and 4DCT (74±3% ipsilateral, 75±4% contralateral). Our results indicate quantitative agreement in the regional distribution of inhaled gas in both static and dynamic imaging methods. PVV may be considered as a regional surrogate measurement of lung function or ventilation. © 2012 American Association of Physicists in Medicine.

Assessment of mass detection performance in contrast enhanced digital mammography

NASA Astrophysics Data System (ADS)

Carton, Ann-Katherine; de Carvalho, Pablo M.; Li, Zhijin; Dromain, Clarisse; Muller, Serge

2015-03-01

We address the detectability of contrast-agent enhancing masses for contrast-agent enhanced spectral mammography (CESM), a dual-energy technique providing functional projection images of breast tissue perfusion and vascularity using simulated CESM images. First, the realism of simulated CESM images from anthropomorphic breast software phantoms generated with a software X-ray imaging platform was validated. Breast texture was characterized by power-law coefficients calculated in data sets of real clinical and simulated images. We also performed a 2-alternative forced choice (2-AFC) psychophysical experiment whereby simulated and real images were presented side-by-side to an experienced radiologist to test if real images could be distinguished from the simulated images. It was found that texture in our simulated CESM images has a fairly realistic appearance. Next, the relative performance of human readers and previously developed mathematical observers was assessed for the detection of iodine-enhancing mass lesions containing different contrast agent concentrations. A four alternative-forced-choice (4 AFC) task was designed; the task for the model and human observer was to detect which one of the four simulated DE recombined images contained an iodineenhancing mass. Our results showed that the NPW and NPWE models largely outperform human performance. After introduction of an internal noise component, both observers approached human performance. The CHO observer performs slightly worse than the average human observer. There is still work to be done in improving model observers as predictors of human-observer performance. Larger trials could also improve our test statistics. We hope that in the future, this framework of software breast phantoms, virtual image acquisition and processing, and mathematical observers can be beneficial to optimize CESM imaging techniques.

Performance evaluation of a compact PET/SPECT/CT tri-modality system for small animal imaging applications

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Wang, Shi; Ma, Tianyu; Wu, Jing; Liu, Hui; Xu, Tianpeng; Xia, Yan; Fan, Peng; Lyu, Zhenlei; Liu, Yaqiang

2015-06-01

PET, SPECT and CT imaging techniques are widely used in preclinical small animal imaging applications. In this paper, we present a compact small animal PET/SPECT/CT tri-modality system. A dual-functional, shared detector design is implemented which enables PET and SPECT imaging with a same LYSO ring detector. A multi-pinhole collimator is mounted on the system and inserted into the detector ring in SPECT imaging mode. A cone-beam CT consisting of a micro focus X-ray tube and a CMOS detector is implemented. The detailed design and the performance evaluations are reported in this paper. In PET imaging mode, the measured NEMA based spatial resolution is 2.12 mm (FWHM), and the sensitivity at the central field of view (CFOV) is 3.2%. The FOV size is 50 mm (∅)×100 mm (L). The SPECT has a spatial resolution of 1.32 mm (FWHM) and an average sensitivity of 0.031% at the center axial, and a 30 mm (∅)×90 mm (L) FOV. The CT spatial resolution is 8.32 lp/mm @10%MTF, and the contrast discrimination function value is 2.06% with 1.5 mm size cubic box object. In conclusion, a compact, tri-modality PET/SPECT/CT system was successfully built with low cost and high performance.

Long ranging swept-source optical coherence tomography-based angiography outperforms its spectral-domain counterpart in imaging human skin microcirculations

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Song, Shaozhen; Men, Shaojie; Wang, Ruikang K.

2017-11-01

There is an increasing demand for imaging tools in clinical dermatology that can perform in vivo wide-field morphological and functional examination from surface to deep tissue regions at various skin sites of the human body. The conventional spectral-domain optical coherence tomography-based angiography (SD-OCTA) system is difficult to meet these requirements due to its fundamental limitations of the sensitivity roll-off, imaging range as well as imaging speed. To mitigate these issues, we demonstrate a swept-source OCTA (SS-OCTA) system by employing a swept source based on a vertical cavity surface-emitting laser. A series of comparisons between SS-OCTA and SD-OCTA are conducted. Benefiting from the high system sensitivity, long imaging range, and superior roll-off performance, the SS-OCTA system is demonstrated with better performance in imaging human skin than the SD-OCTA system. We show that the SS-OCTA permits remarkable deep visualization of both structure and vasculature (up to ˜2 mm penetration) with wide field of view capability (up to 18×18 mm2), enabling a more comprehensive assessment of the morphological features as well as functional blood vessel networks from the superficial epidermal to deep dermal layers. It is expected that the advantages of the SS-OCTA system will provide a ground for clinical translation, benefiting the existing dermatological practice.

Cortical underconnectivity coupled with preserved visuospatial cognition in autism: Evidence from an fMRI study of an embedded figures task.

PubMed

Damarla, Saudamini Roy; Keller, Timothy A; Kana, Rajesh K; Cherkassky, Vladimir L; Williams, Diane L; Minshew, Nancy J; Just, Marcel Adam

2010-10-01

Individuals with high-functioning autism sometimes exhibit intact or superior performance on visuospatial tasks, in contrast to impaired functioning in other domains such as language comprehension, executive tasks, and social functions. The goal of the current study was to investigate the neural bases of preserved visuospatial processing in high-functioning autism from the perspective of the cortical underconnectivity theory. We used a combination of behavioral, functional magnetic resonance imaging, functional connectivity, and corpus callosum morphometric methodological tools. Thirteen participants with high-functioning autism and 13 controls (age-, IQ-, and gender-matched) were scanned while performing an Embedded Figures Task. Despite the ability of the autism group to attain behavioral performance comparable to the control group, the brain imaging results revealed several group differences consistent with the cortical underconnectivity account of autism. First, relative to controls, the autism group showed less activation in the left dorsolateral prefrontal and inferior parietal areas and more activation in visuospatial (bilateral superior parietal extending to inferior parietal and right occipital) areas. Second, the autism group demonstrated lower functional connectivity between higher-order working memory/executive areas and visuospatial regions (between frontal and parietal-occipital). Third, the size of the corpus callosum (an index of anatomical connectivity) was positively correlated with frontal-posterior (parietal and occipital) functional connectivity in the autism group. Thus, even in the visuospatial domain, where preserved performance among people with autism is observed, the neuroimaging signatures of cortical underconnectivity persist.

Cortical underconnectivity coupled with preserved visuospatial cognition in autism: Evidence from an fMRI study of an embedded figures task

PubMed Central

Damarla, Saudamini Roy; Keller, Timothy A.; Kana, Rajesh K.; Cherkassky, Vladimir L.; Williams, Diane L.; Minshew, Nancy J.; Just, Marcel Adam

2010-01-01

Individuals with high-functioning autism sometimes exhibit intact or superior performance on visuospatial tasks, in contrast to impaired functioning in other domains such as language comprehension, executive tasks, and social functions. The goal of the current study was to investigate the neural bases of preserved visuospatial processing in high-functioning autism from the perspective of the cortical underconnectivity theory. We used a combination of behavioral, functional magnetic resonance imaging (fMRI), functional connectivity, and corpus callosum morphometric methodological tools. Thirteen participants with high-functioning autism and thirteen controls (age-, IQ-, and gender-matched) were scanned while performing an Embedded Figures Task (EFT). Despite the ability of the autism group to attain behavioral performance comparable to the control group, the brain imaging results revealed several group differences consistent with the cortical underconnectivity account of autism. First, relative to controls, the autism group showed less activation in left dorsolateral prefrontal and inferior parietal areas and more activation in visuospatial (bilateral superior parietal extending to inferior parietal and right occipital) areas. Second, the autism group demonstrated lower functional connectivity between higher-order working memory/executive areas and visuospatial regions (between frontal and parietal-occipital). Third, the size of the corpus callosum (an index of anatomical connectivity) was positively correlated with frontal-posterior (parietal and occipital) functional connectivity in the autism group. Thus, even in the visuospatial domain, where preserved performance among people with autism is observed, the neuroimaging signatures of cortical underconnectivity persist. PMID:20740492

Parallel algorithm of real-time infrared image restoration based on total variation theory

NASA Astrophysics Data System (ADS)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

Functional Evaluation of Hidden Figures Object Analysis in Children with Autistic Disorder

ERIC Educational Resources Information Center

Malisza, Krisztina L.; Clancy, Christine; Shiloff, Deborah; Foreman, Derek; Holden, Jeanette; Jones, Cheryl; Paulson, K.; Summers, Randy; Yu, C. T.; Chudley, Albert E.

2011-01-01

Functional magnetic resonance imaging (fMRI) during performance of a hidden figures task (HFT) was used to compare differences in brain function in children diagnosed with autism disorder (AD) compared to children with attention-deficit/hyperactivity disorder (ADHD) and typical controls (TC). Overall greater functional MRI activity was observed in…

Assessment of regional lung functional impairment with co-registered respiratory-gated ventilation/perfusion SPET-CT images: initial experiences.

PubMed

Suga, Kazuyoshi; Yasuhiko, Kawakami; Zaki, Mohammed; Yamashita, Tomio; Seto, Aska; Matsumoto, Tsuneo; Matsunaga, Naofumi

2004-02-01

In this study, respiratory-gated ventilation and perfusion single-photon emission tomography (SPET) were used to define regional functional impairment and to obtain reliable co-registration with computed tomography (CT) images in various lung diseases. Using a triple-headed SPET unit and a physiological synchroniser, gated perfusion SPET was performed in a total of 78 patients with different pulmonary diseases, including metastatic nodules (n = 15); in 34 of these patients, it was performed in combination with gated technetium-99m Technegas SPET. Projection data were acquired using 60 stops over 120 degrees for each detector. Gated end-inspiration and ungated images were reconstructed from 1/8 data centered at peak inspiration for each regular respiratory cycle and full respiratory cycle data, respectively. Gated images were registered with tidal inspiration CT images using automated three-dimensional (3D) registration software. Registration mismatch was assessed by measuring 3D distance of the centroid of the nine selected round perfusion-defective nodules. Gated SPET images were completed within 29 min, and increased the number of visible ventilation and perfusion defects by 9.7% and 17.2%, respectively, as compared with ungated images; furthermore, lesion-to-normal lung contrast was significantly higher on gated SPET images. In the nine round perfusion-defective nodules, gated images yielded a significantly better SPET-CT match compared with ungated images (4.9 +/- 3.1 mm vs 19.0 +/- 9.1 mm, P<0.001). The co-registered SPET-CT images allowed accurate perception of the location and extent of each ventilation/perfusion defect on the underlying CT anatomy, and characterised the pathophysiology of the various diseases. By reducing respiratory motion effects and enhancing perfusion/ventilation defect clarity, gated SPET can provide reliable co-registered images with CT images to accurately characterise regional functional impairment in various lung diseases.

Fruit fly optimization based least square support vector regression for blind image restoration

NASA Astrophysics Data System (ADS)

Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

2014-11-01

The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and performs better. Both objective and subjective restoration performances are studied in the comparison experiments.

Technical Note: Image filtering to make computer-aided detection robust to image reconstruction kernel choice in lung cancer CT screening

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

Ohkubo, Masaki, E-mail: mook@clg.niigata-u.ac.jp

Purpose: In lung cancer computed tomography (CT) screening, the performance of a computer-aided detection (CAD) system depends on the selection of the image reconstruction kernel. To reduce this dependence on reconstruction kernels, the authors propose a novel application of an image filtering method previously proposed by their group. Methods: The proposed filtering process uses the ratio of modulation transfer functions (MTFs) of two reconstruction kernels as a filtering function in the spatial-frequency domain. This method is referred to as MTF{sub ratio} filtering. Test image data were obtained from CT screening scans of 67 subjects who each had one nodule. Imagesmore » were reconstructed using two kernels: f{sub STD} (for standard lung imaging) and f{sub SHARP} (for sharp edge-enhancement lung imaging). The MTF{sub ratio} filtering was implemented using the MTFs measured for those kernels and was applied to the reconstructed f{sub SHARP} images to obtain images that were similar to the f{sub STD} images. A mean filter and a median filter were applied (separately) for comparison. All reconstructed and filtered images were processed using their prototype CAD system. Results: The MTF{sub ratio} filtered images showed excellent agreement with the f{sub STD} images. The standard deviation for the difference between these images was very small, ∼6.0 Hounsfield units (HU). However, the mean and median filtered images showed larger differences of ∼48.1 and ∼57.9 HU from the f{sub STD} images, respectively. The free-response receiver operating characteristic (FROC) curve for the f{sub SHARP} images indicated poorer performance compared with the FROC curve for the f{sub STD} images. The FROC curve for the MTF{sub ratio} filtered images was equivalent to the curve for the f{sub STD} images. However, this similarity was not achieved by using the mean filter or median filter. Conclusions: The accuracy of MTF{sub ratio} image filtering was verified and the method was demonstrated to be effective for reducing the kernel dependence of CAD performance.« less

Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images

PubMed Central

Jang, Yeonggul; Jung, Ho Yub; Hong, Youngtaek; Cho, Iksung; Shim, Hackjoon; Chang, Hyuk-Jae

2016-01-01

This paper presents a method for the automatic 3D segmentation of the ascending aorta from coronary computed tomography angiography (CCTA). The segmentation is performed in three steps. First, the initial seed points are selected by minimizing a newly proposed energy function across the Hough circles. Second, the ascending aorta is segmented by geodesic distance transformation. Third, the seed points are effectively transferred through the next axial slice by a novel transfer function. Experiments are performed using a database composed of 10 patients' CCTA images. For the experiment, the ground truths are annotated manually on the axial image slices by a medical expert. A comparative evaluation with state-of-the-art commercial aorta segmentation algorithms shows that our approach is computationally more efficient and accurate under the DSC (Dice Similarity Coefficient) measurements. PMID:26904151

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

PubMed

Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

2018-05-01

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

Ultrahigh speed endoscopic optical coherence tomography for gastroenterology.

PubMed

Tsai, Tsung-Han; Lee, Hsiang-Chieh; Ahsen, Osman O; Liang, Kaicheng; Giacomelli, Michael G; Potsaid, Benjamin M; Tao, Yuankai K; Jayaraman, Vijaysekhar; Figueiredo, Marisa; Huang, Qin; Cable, Alex E; Fujimoto, James; Mashimo, Hiroshi

2014-12-01

We describe an ultrahigh speed endoscopic swept source optical coherence tomography (OCT) system for clinical gastroenterology using a vertical-cavity surface-emitting laser (VCSEL) and micromotor imaging catheter. The system had a 600 kHz axial scan rate and 8 µm axial resolution in tissue. Imaging was performed with a 3.2 mm diameter imaging catheter at 400 frames per second with a 12 µm spot size. Three-dimensional OCT (3D-OCT) imaging was performed in patients with a cross section of pathologies undergoing upper and lower endoscopy. The use of distally actuated imaging catheters enabled OCT imaging with more flexibility, such as volumetric imaging in the small intestine and the assessment of hiatal hernia using retroflex imaging. The high rotational scanning stability of the micromotor enabled 3D volumetric imaging with micron scale volumetric accuracy for both en face OCT and cross-sectional imaging, as well as OCT angiography (OCTA) for 3D visualization of subsurface microvasculature. The ability to perform both structural and functional 3D OCT imaging in the GI tract with microscopic accuracy should enable a wide range of studies and enhance the sensitivity and specificity of OCT for detecting pathology.

Ultrahigh speed endoscopic optical coherence tomography for gastroenterology

PubMed Central

Tsai, Tsung-Han; Lee, Hsiang-Chieh; Ahsen, Osman O.; Liang, Kaicheng; Giacomelli, Michael G.; Potsaid, Benjamin M.; Tao, Yuankai K.; Jayaraman, Vijaysekhar; Figueiredo, Marisa; Huang, Qin; Cable, Alex E.; Fujimoto, James; Mashimo, Hiroshi

2014-01-01

We describe an ultrahigh speed endoscopic swept source optical coherence tomography (OCT) system for clinical gastroenterology using a vertical-cavity surface-emitting laser (VCSEL) and micromotor imaging catheter. The system had a 600 kHz axial scan rate and 8 µm axial resolution in tissue. Imaging was performed with a 3.2 mm diameter imaging catheter at 400 frames per second with a 12 µm spot size. Three-dimensional OCT (3D-OCT) imaging was performed in patients with a cross section of pathologies undergoing upper and lower endoscopy. The use of distally actuated imaging catheters enabled OCT imaging with more flexibility, such as volumetric imaging in the small intestine and the assessment of hiatal hernia using retroflex imaging. The high rotational scanning stability of the micromotor enabled 3D volumetric imaging with micron scale volumetric accuracy for both en face OCT and cross-sectional imaging, as well as OCT angiography (OCTA) for 3D visualization of subsurface microvasculature. The ability to perform both structural and functional 3D OCT imaging in the GI tract with microscopic accuracy should enable a wide range of studies and enhance the sensitivity and specificity of OCT for detecting pathology. PMID:25574446

Objective image characterization of a spectral CT scanner with dual-layer detector

NASA Astrophysics Data System (ADS)

Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

2018-01-01

This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

Leveraging multi-layer imager detector design to improve low-dose performance for megavoltage cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Hu, Yue-Houng; Rottmann, Joerg; Fueglistaller, Rony; Myronakis, Marios; Wang, Adam; Huber, Pascal; Shedlock, Daniel; Morf, Daniel; Baturin, Paul; Star-Lack, Josh; Berbeco, Ross

2018-02-01

While megavoltage cone-beam computed tomography (CBCT) using an electronic portal imaging device (EPID) provides many advantages over kilovoltage (kV) CBCT, clinical adoption is limited by its high doses. Multi-layer imager (MLI) EPIDs increase DQE(0) while maintaining high resolution. However, even well-designed, high-performance MLIs suffer from increased electronic noise from each readout, degrading low-dose image quality. To improve low-dose performance, shift-and-bin addition (ShiBA) imaging is proposed, leveraging the unique architecture of the MLI. ShiBA combines hardware readout-binning and super-resolution concepts, reducing electronic noise while maintaining native image sampling. The imaging performance of full-resolution (FR); standard, aligned binned (BIN); and ShiBA images in terms of noise power spectrum (NPS), electronic NPS, modulation transfer function (MTF), and the ideal observer signal-to-noise ratio (SNR)—the detectability index (d‧)—are compared. The FR 4-layer readout of the prototype MLI exhibits an electronic NPS magnitude 6-times higher than a state-of-the-art single layer (SLI) EPID. Although the MLI is built on the same readout platform as the SLI, with each layer exhibiting equivalent electronic noise, the multi-stage readout of the MLI results in electronic noise 50% higher than simple summation. Electronic noise is mitigated in both BIN and ShiBA imaging, reducing its total by ~12 times. ShiBA further reduces the NPS, effectively upsampling the image, resulting in a multiplication by a sinc2 function. Normalized NPS show that neither ShiBA nor BIN otherwise affects image noise. The LSF shows that ShiBA removes the pixilation artifact of BIN images and mitigates the effect of detector shift, but does not quantifiably improve the MTF. ShiBA provides a pre-sampled representation of the images, mitigating phase dependence. Hardware binning strategies lower the quantum noise floor, with 2  ×  2 implementation reducing the dose at which DQE(0) degrades by 10% from 0.01 MU to 0.004 MU, representing 20% improvement in d‧.

Design Considerations For Imaging Charge-Coupled Device (ICCD) Star Sensors

NASA Astrophysics Data System (ADS)

McAloon, K. J.

1981-04-01

A development program is currently underway to produce a precision star sensor using imaging charge coupled device (ICCD) technology. The effort is the critical component development phase for the Air Force Multi-Mission Attitude Determination and Autonomous Navigation System (MADAN). A number of unique considerations have evolved in designing an arcsecond accuracy sensor around an ICCD detector. Three tiers of performance criteria are involved: at the spacecraft attitude determination system level, at the star sensor level, and at the detector level. Optimum attitude determination system performance involves a tradeoff between Kalman filter iteration time and sensor ICCD integration time. The ICCD star sensor lends itself to the use of a new approach in the functional interface between the attitude determination system and the sensor. At the sensor level image data processing tradeoffs are important for optimum sensor performance. These tradeoffs involve the sensor optic configuration, the optical point spread function (PSF) size and shape, the PSF position locator, and the microprocessor locator algorithm. Performance modelling of the sensor mandates the use of computer simulation programs. Five key performance parameters at the ICCD detector level are defined. ICCD error characteristics have also been isolated to five key parameters.

Microlens performance limits in sub-2mum pixel CMOS image sensors.

PubMed

Huo, Yijie; Fesenmaier, Christian C; Catrysse, Peter B

2010-03-15

CMOS image sensors with smaller pixels are expected to enable digital imaging systems with better resolution. When pixel size scales below 2 mum, however, diffraction affects the optical performance of the pixel and its microlens, in particular. We present a first-principles electromagnetic analysis of microlens behavior during the lateral scaling of CMOS image sensor pixels. We establish for a three-metal-layer pixel that diffraction prevents the microlens from acting as a focusing element when pixels become smaller than 1.4 microm. This severely degrades performance for on and off-axis pixels in red, green and blue color channels. We predict that one-metal-layer or backside-illuminated pixels are required to extend the functionality of microlenses beyond the 1.4 microm pixel node.

Sexual Anatomy and Function in Women With and Without Genital Mutilation: A Cross-Sectional Study.

PubMed

Abdulcadir, Jasmine; Botsikas, Diomidis; Bolmont, Mylène; Bilancioni, Aline; Djema, Dahila Amal; Bianchi Demicheli, Francesco; Yaron, Michal; Petignat, Patrick

2016-02-01

Female genital mutilation (FGM), the partial or total removal of the external genitalia for non-medical reasons, can affect female sexuality. However, only few studies are available, and these have significant methodologic limitations. To understand the impact of FGM on the anatomy of the clitoris and bulbs using magnetic resonance imaging and on sexuality using psychometric instruments and to study whether differences in anatomy after FGM correlate with differences in sexual function, desire, and body image. A cross-sectional study on sexual function and sexual anatomy was performed in women with and without FGM. Fifteen women with FGM involving cutting of the clitoris and 15 uncut women as a control group matched by age and parity were prospectively recruited. Participants underwent pelvic magnetic resonance imaging with vaginal opacification by ultrasound gel and completed validated questionnaires on desire (Sexual Desire Inventory), body image (Questionnaire d'Image Corporelle [Body Image Satisfaction Scale]), and sexual function (Female Sexual Function Index). Primary outcomes were clitoral and bulbar measurements on magnetic resonance images. Secondary outcomes were sexual function, desire, and body image scores. Women with FGM did not have significantly decreased clitoral glans width and body length but did have significantly smaller volume of the clitoris plus bulbs. They scored significantly lower on sexual function and desire than women without FGM. They did not score lower on Female Sexual Function Index sub-scores for orgasm, desire, and satisfaction and on the Questionnaire d'Image Corporelle but did report significantly more dyspareunia. A larger total volume of clitoris and bulbs did not correlate with higher Female Sexual Function Index and Sexual Desire Inventory scores in women with FGM compared with uncut women who had larger total volume that correlated with higher scores. Women with FGM have sexual erectile tissues for sexual arousal, orgasm, and pleasure. Women with sexual dysfunction should be appropriately counseled and treated. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Image quality evaluation of medical color and monochrome displays using an imaging colorimeter

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

2012-10-01

The purpose of this presentation is to demonstrate the means which permit examining the accuracy of Image Quality with respect to MTF (Modulation Transfer Function) and NPS (Noise Power Spectrum) of Color Displays and Monochrome Displays. Indications were in the past that color displays could affect the clinical performance of color displays negatively compared to monochrome displays. Now colorimeters like the PM-1423 are available which have higher sensitivity and color accuracy than the traditional cameras like CCD cameras. Reference (1) was not based on measurements made with a colorimeter. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future SPIE Conference.Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. This paper focuses on the measurements of physical characteristics of the spatial resolution and noise performance of color and monochrome medical displays which were made with a colorimeter and we will after this meeting submit the data to an ROC study so we have again a paper to present at a future Annual SPIE Conference. Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between the two medical displays. The Imaging Colorimeter. Measurement of color image quality needs were done with an imaging colorimeter as it is shown below. Imaging colorimetry is ideally suited to FPD measurement because imaging systems capture spatial data generating millions of data points in a single measurement operation. The imaging colorimeter which was used was the PM-1423 from Radiant Imaging. It uses full-frame CCDs with 100% fill factor which makes it very suitable to measure luminance and chrominance of individual LCD pixels and sub-pixels on an LCD display. The CCDs used are 14-bit thermoelectrically cooled and temperature stabilized , scientific grade.

Positron Emission Tomography of the Heart

DOE R&D Accomplishments Database

Schelbert, H. R.; Phelps, M. E.; Kuhl, D. E.

1979-01-01

Positron emission computed tomography (PCT) represents an important new tool for the noninvasive evaluation and, more importantly, quantification of myocardial performance. Most currently available techniques permit assessment of only one aspect of cardiac function, i.e., myocardial perfusion by gamma scintillation camera imaging with Thallium-201 or left ventricular function by echocardiography or radionuclide angiocardiography. With PCT it may become possible to study all three major segments of myocardial performance, i.e., regional blood flow, mechanical function and, most importantly, myocardial metabolism. Each of these segments can either be evaluated separately or in combination. This report briefly describes the principles and technological advantages of the imaging device, reviews currently available radioactive tracers and how they can be employed for the assessment of flow, function and metabolism; and, lastly, discusses possible applications of PCT for the study of cardiac physiology or its potential role in the diagnosis of cardiac disease.

Procurement specification color graphic camera system

NASA Technical Reports Server (NTRS)

Prow, G. E.

1980-01-01

The performance and design requirements for a Color Graphic Camera System are presented. The system is a functional part of the Earth Observation Department Laboratory System (EODLS) and will be interfaced with Image Analysis Stations. It will convert the output of a raster scan computer color terminal into permanent, high resolution photographic prints and transparencies. Images usually displayed will be remotely sensed LANDSAT imager scenes.

Lens-based wavefront sensorless adaptive optics swept source OCT

NASA Astrophysics Data System (ADS)

Jian, Yifan; Lee, Sujin; Ju, Myeong Jin; Heisler, Morgan; Ding, Weiguang; Zawadzki, Robert J.; Bonora, Stefano; Sarunic, Marinko V.

2016-06-01

Optical coherence tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. Although the axial resolution of OCT system, which is a function of the light source bandwidth, is sufficient to resolve retinal features at a micrometer scale, the lateral resolution is dependent on the delivery optics and is limited by ocular aberrations. Through the combination of wavefront sensorless adaptive optics and the use of dual deformable transmissive optical elements, we present a compact lens-based OCT system at an imaging wavelength of 1060 nm for high resolution retinal imaging. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient’s eyes, and a novel multi-actuator adaptive lens for aberration correction to achieve near diffraction limited imaging performance at the retina. With a parallel processing computational platform, high resolution cross-sectional and en face retinal image acquisition and display was performed in real time. In order to demonstrate the system functionality and clinical utility, we present images of the photoreceptor cone mosaic and other retinal layers acquired in vivo from research subjects.

Coded aperture solution for improving the performance of traffic enforcement cameras

NASA Astrophysics Data System (ADS)

Masoudifar, Mina; Pourreza, Hamid Reza

2016-10-01

A coded aperture camera is proposed for automatic license plate recognition (ALPR) systems. It captures images using a noncircular aperture. The aperture pattern is designed for the rapid acquisition of high-resolution images while preserving high spatial frequencies of defocused regions. It is obtained by minimizing an objective function, which computes the expected value of perceptual deblurring error. The imaging conditions and camera sensor specifications are also considered in the proposed function. The designed aperture improves the depth of field (DoF) and subsequently ALPR performance. The captured images can be directly analyzed by the ALPR software up to a specific depth, which is 13 m in our case, though it is 11 m for the circular aperture. Moreover, since the deblurring results of images captured by our aperture yield fewer artifacts than those captured by the circular aperture, images can be first deblurred and then analyzed by the ALPR software. In this way, the DoF and recognition rate can be improved at the same time. Our case study shows that the proposed camera can improve the DoF up to 17 m while it is limited to 11 m in the conventional aperture.

A Wide-Swath Spaceborne TOPS SAR Image Formation Algorithm Based on Chirp Scaling and Chirp-Z Transform

PubMed Central

Yang, Wei; Chen, Jie; Zeng, Hong Cheng; Wang, Peng Bo; Liu, Wei

2016-01-01

Based on the terrain observation by progressive scans (TOPS) mode, an efficient full-aperture image formation algorithm for focusing wide-swath spaceborne TOPS data is proposed. First, to overcome the Doppler frequency spectrum aliasing caused by azimuth antenna steering, the range-independent derotation operation is adopted, and the signal properties after derotation are derived in detail. Then, the azimuth deramp operation is performed to resolve image folding in azimuth. The traditional dermap function will introduce a time shift, resulting in appearance of ghost targets and azimuth resolution reduction at the scene edge, especially in the wide-swath coverage case. To avoid this, a novel solution is provided using a modified range-dependent deramp function combined with the chirp-z transform. Moreover, range scaling and azimuth scaling are performed to provide the same azimuth and range sampling interval for all sub-swaths, instead of the interpolation operation for the sub-swath image mosaic. Simulation results are provided to validate the proposed algorithm. PMID:27941706

Synthesis and Preclinical Characterization of a Cationic Iodinated Imaging Contrast Agent (CA4+) and Its Use for Quantitative Computed Tomography of Ex Vivo Human Hip Cartilage.

PubMed

Stewart, Rachel C; Patwa, Amit N; Lusic, Hrvoje; Freedman, Jonathan D; Wathier, Michel; Snyder, Brian D; Guermazi, Ali; Grinstaff, Mark W

2017-07-13

Contrast agents that go beyond qualitative visualization and enable quantitative assessments of functional tissue performance represent the next generation of clinically useful imaging tools. An optimized and efficient large-scale synthesis of a cationic iodinated contrast agent (CA4+) is described for imaging articular cartilage. Contrast-enhanced CT (CECT) using CA4+ reveals significantly greater agent uptake of CA4+ in articular cartilage compared to that of similar anionic or nonionic agents, and CA4+ uptake follows Donnan equilibrium theory. The CA4+ CECT attenuation obtained from imaging ex vivo human hip cartilage correlates with the glycosaminoglycan content, equilibrium modulus, and coefficient of friction, which are key indicators of cartilage functional performance and osteoarthritis stage. Finally, preliminary toxicity studies in a rat model show no adverse events, and a pharmacokinetics study documents a peak plasma concentration 30 min after dosing, with the agent no longer present in vivo at 96 h via excretion in the urine.

Practical implementation of Channelized Hotelling Observers: Effect of ROI size

PubMed Central

Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

2017-01-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO’s performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO’s performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies. PMID:28943699

Aging of imaging properties of a CMOS flat-panel detector for dental cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Kim, D. W.; Han, J. C.; Yun, S.; Kim, H. K.

2017-01-01

We have experimentally investigated the long-term stability of imaging properties of a flat-panel detector in conditions used for dental x-ray imaging. The detector consists of a CsI:Tl layer and CMOS photodiode pixel arrays. Aging simulations were carried out using an 80-kVp x-ray beam at an air-kerma rate of approximately 5 mGy s-1 at the entrance surface of the detector with a total air kerma of up to 0.6 kGy. Dark and flood-field images were periodically obtained during irradiation, and the mean signal and noise levels were evaluated for each image. We also evaluated the modulation-transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). The aging simulation showed a decrease in both the signal and noise of the gain-offset-corrected images, but there was negligible change in the signal-to-noise performance as a function of the accumulated dose. The gain-offset correction for analyzing images resulted in negligible changes in MTF, NPS, and DQE results over the total dose. Continuous x-ray exposure to a detector can cause degradation in the physical performance factors such the detector sensitivity, but linear analysis of the gain-offset-corrected images can assure integrity of the imaging properties of a detector during its lifetime.

Central obscuration effects on optical synthetic aperture imaging

NASA Astrophysics Data System (ADS)

Wang, Xue-wen; Luo, Xiao; Zheng, Li-gong; Zhang, Xue-jun

2014-02-01

Due to the central obscuration problem exists in most optical synthetic aperture systems, it is necessary to analyze its effects on their image performance. Based on the incoherent diffraction limited imaging theory, a Golay-3 type synthetic aperture system was used to study the central obscuration effects on the point spread function (PSF) and the modulation transfer function (MTF). It was found that the central obscuration does not affect the width of the central peak of the PSF and the cutoff spatial frequency of the MTF, but attenuate the first sidelobe of the PSF and the midfrequency of the MTF. The imaging simulation of a Golay-3 type synthetic aperture system with central obscuration proved this conclusion. At last, a Wiener Filter restoration algorithm was used to restore the image of this system, the images were obviously better.

Hyperpolarized (3)He magnetic resonance imaging: comparison with four-dimensional x-ray computed tomography imaging in lung cancer.

PubMed

Mathew, Lindsay; Wheatley, Andrew; Castillo, Richard; Castillo, Edward; Rodrigues, George; Guerrero, Thomas; Parraga, Grace

2012-12-01

Pulmonary functional imaging using four-dimensional x-ray computed tomographic (4DCT) imaging and hyperpolarized (3)He magnetic resonance imaging (MRI) provides regional lung function estimates in patients with lung cancer in whom pulmonary function measurements are typically dominated by tumor burden. The aim of this study was to evaluate the quantitative spatial relationship between 4DCT and hyperpolarized (3)He MRI ventilation maps. Eleven patients with lung cancer provided written informed consent to 4DCT imaging and MRI performed within 11 ± 14 days. Hyperpolarized (3)He MRI was acquired in breath-hold after inhalation from functional residual capacity of 1 L hyperpolarized (3)He, whereas 4DCT imaging was acquired over a single tidal breath of room air. For hyperpolarized (3)He MRI, the percentage ventilated volume was generated using semiautomated segmentation; for 4DCT imaging, pulmonary function maps were generated using the correspondence between identical tissue elements at inspiratory and expiratory phases to generate percentage ventilated volume. After accounting for differences in image acquisition lung volumes ((3)He MRI: 1.9 ± 0.5 L ipsilateral, 2.3 ± 0.7 L contralateral; 4DCT imaging: 1.2 ± 0.3 L ipsilateral, 1.3 ± 0.4 L contralateral), there was no significant difference in percentage ventilated volume between hyperpolarized (3)He MRI (72 ± 11% ipsilateral, 79 ± 12% contralateral) and 4DCT imaging (74 ± 3% ipsilateral, 75 ± 4% contralateral). Spatial correspondence between 4DCT and (3)He MRI ventilation was evaluated using the Dice similarity coefficient index (ipsilateral, 86 ± 12%; contralateral, 88 ± 12%). Despite rather large differences in image acquisition breathing maneuvers, good spatial and significant quantitative agreement was observed for ventilation maps on hyperpolarized (3)He MRI and 4DCT imaging, suggesting that pulmonary regions with good lung function are similar between modalities in this small group of patients with lung cancer. Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

Study of spin-scan imaging for outer planets missions: Executive summary

NASA Technical Reports Server (NTRS)

Russell, E. E.; Chandos, R. A.; Kodak, J. C.; Pellicori, S. F.; Tomasko, M. G.

1974-01-01

The development and characteristics of spin-scan imagers for interplanetary exploration are discussed. The spin-scan imaging photopolarimeter instruments of Pioneer 10 and 11 are described. In addition to the imaging function, the instruments are also used in a faint-light mode to take sky maps in both radiance and polarization. The performance of a visible-infrared spin-scan radiometer (VISSR), which operates in both visible and infrared wavelengths, is reported.

Skeleton-based region competition for automated gray matter and white matter segmentation of human brain MR images

NASA Astrophysics Data System (ADS)

Chu, Yong; Chen, Ya-Fang; Su, Min-Ying; Nalcioglu, Orhan

2005-04-01

Image segmentation is an essential process for quantitative analysis. Segmentation of brain tissues in magnetic resonance (MR) images is very important for understanding the structural-functional relationship for various pathological conditions, such as dementia vs. normal brain aging. Different brain regions are responsible for certain functions and may have specific implication for diagnosis. Segmentation may facilitate the analysis of different brain regions to aid in early diagnosis. Region competition has been recently proposed as an effective method for image segmentation by minimizing a generalized Bayes/MDL criterion. However, it is sensitive to initial conditions - the "seeds", therefore an optimal choice of "seeds" is necessary for accurate segmentation. In this paper, we present a new skeleton-based region competition algorithm for automated gray and white matter segmentation. Skeletons can be considered as good "seed regions" since they provide the morphological a priori information, thus guarantee a correct initial condition. Intensity gradient information is also added to the global energy function to achieve a precise boundary localization. This algorithm was applied to perform gray and white matter segmentation using simulated MRI images from a realistic digital brain phantom. Nine different brain regions were manually outlined for evaluation of the performance in these separate regions. The results were compared to the gold-standard measure to calculate the true positive and true negative percentages. In general, this method worked well with a 96% accuracy, although the performance varied in different regions. We conclude that the skeleton-based region competition is an effective method for gray and white matter segmentation.

Information theoretic analysis of edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

Murine fetal echocardiography.

PubMed

Kim, Gene H

2013-02-15

Transgenic mice displaying abnormalities in cardiac development and function represent a powerful tool for the understanding the molecular mechanisms underlying both normal cardiovascular function and the pathophysiological basis of human cardiovascular disease. Fetal and perinatal death is a common feature when studying genetic alterations affecting cardiac development. In order to study the role of genetic or pharmacologic alterations in the early development of cardiac function, ultrasound imaging of the live fetus has become an important tool for early recognition of abnormalities and longitudinal follow-up. Noninvasive ultrasound imaging is an ideal method for detecting and studying congenital malformations and the impact on cardiac function prior to death. It allows early recognition of abnormalities in the living fetus and the progression of disease can be followed in utero with longitudinal studies. Until recently, imaging of fetal mouse hearts frequently involved invasive methods. The fetus had to be sacrificed to perform magnetic resonance microscopy and electron microscopy or surgically delivered for transillumination microscopy. An application of high-frequency probes with conventional 2-D and pulsed-wave Doppler imaging has been shown to provide measurements of cardiac contraction and heart rates during embryonic development with databases of normal developmental changes now available. M-mode imaging further provides important functional data, although, the proper imaging planes are often difficult to obtain. High-frequency ultrasound imaging of the fetus has improved 2-D resolution and can provide excellent information on the early development of cardiac structures.

Intensive care unit referring physician usage of PACS workstation functions based on disease categories

NASA Astrophysics Data System (ADS)

Horii, Steven C.; Kundel, Harold L.; Shile, Peter E.; Carey, Bruce; Seshadri, Sridhar B.; Feingold, Eric R.

1994-05-01

As part of a study of the use of a PACS workstation compared to film in a Medical Intensive Care Unit, logs of workstation activity were maintained. The software for the workstation kept track of the type of user (i.e., intern, resident, fellow, or attending physician) and also of the workstation image manipulation functions used. The functions logged were: no operation, brightness/contrast adjustment, invert video, zoom, and high resolution display (this last function resulted in the display of the full 2 K X 2 K image rather than the usual subsampled 1 K X 1 K image. Associated data collection allows us to obtain the diagnostic category of the examination being viewed (e.g., location of tubes and lines, rule out: pneumonia, congestive heart failure, pneumothorax, and pleural effusion). The diagnostic categories and user type were then correlated with the use of workstation functions during viewing of images. In general, there was an inverse relationship between the level of training and the number of workstation uses. About two-thirds of the time, there was no image manipulation operation performed. Adjustment of brightness/contrast had the highest percentage of use overall, followed by zoom, video invert, and high resolution display.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

PubMed Central

Mariappan, Leo; Hu, Gang; He, Bin

2014-01-01

Purpose: Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. Methods: In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. Results: The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. Conclusions: The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction. PMID:24506649

Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652

Imaging visible light with Medipix2.

PubMed

Mac Raighne, Aaron; Brownlee, Colin; Gebert, Ulrike; Maneuski, Dzmitry; Milnes, James; O'Shea, Val; Rügheimer, Tilman K

2010-11-01

A need exists for high-speed single-photon counting optical imaging detectors. Single-photon counting high-speed detection of x rays is possible by using Medipix2 with pixelated silicon photodiodes. In this article, we report on a device that exploits the Medipix2 chip for optical imaging. The fabricated device is capable of imaging at >3000 frames/s over a 256×256 pixel matrix. The imaging performance of the detector device via the modulation transfer function is measured, and the presence of ion feedback and its degradation of the imaging properties are discussed.

Changes in Serial Optical Topography and TMS during Task Performance after Constraint-Induced Movement Therapy in Stroke: A Case Study

PubMed Central

Park, Si-Woon; Butler, Andrew J.; Cavalheiro, Vanessa; Alberts, Jay L.; Wolf, Steven L.

2013-01-01

The authors examined serial changes in optical topography in a stroke patient performing a functional task, as well as clinical and physiologic measures while undergoing constraint-induced therapy (CIT). A 73-year-old right hemiparetic patient, who had a subcortical stroke 4 months previously, received 2 weeks of CIT. During the therapy, daily optical topography imaging using near-infrared light was measured serially while the participant performed a functional key-turning task. Clinical outcome measures included the Wolf Motor Function Test (WMFT), Motor Activity Log (MAL), and functional key grip test. Transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) were also used to map cortical areas and hemodynamic brain responses, respectively. Optical topography measurement showed an overall decrease in oxy-hemoglobin concentration in both hemispheres as therapy progressed and the laterality index increased toward the contralateral hemisphere. An increased TMS motor map area was observed in the contralateral cortex following treatment. Posttreatment fMRI showed bilateral primary motor cortex activation, although slightly greater in the contralateral hemisphere, during affected hand movement. Clinical scores revealed marked improvement in functional activities. In one patient who suffered a stroke, 2 weeks of CIT led to improved function and cortical reorganization in the hemisphere contralateral to the affected hand. PMID:15228805

Effects of illumination on image reconstruction via Fourier ptychography

NASA Astrophysics Data System (ADS)

Cao, Xinrui; Sinzinger, Stefan

2017-12-01

The Fourier ptychographic microscopy (FPM) technique provides high-resolution images by combining a traditional imaging system, e.g. a microscope or a 4f-imaging system, with a multiplexing illumination system, e.g. an LED array and numerical image processing for enhanced image reconstruction. In order to numerically combine images that are captured under varying illumination angles, an iterative phase-retrieval algorithm is often applied. However, in practice, the performance of the FPM algorithm degrades due to the imperfections of the optical system, the image noise caused by the camera, etc. To eliminate the influence of the aberrations of the imaging system, an embedded pupil function recovery (EPRY)-FPM algorithm has been proposed [Opt. Express 22, 4960-4972 (2014)]. In this paper, we study how the performance of FPM and EPRY-FPM algorithms are affected by imperfections of the illumination system using both numerical simulations and experiments. The investigated imperfections include varying and non-uniform intensities, and wavefront aberrations. Our study shows that the aberrations of the illumination system significantly affect the performance of both FPM and EPRY-FPM algorithms. Hence, in practice, aberrations in the illumination system gain significant influence on the resulting image quality.

Registration of interferometric SAR images

NASA Technical Reports Server (NTRS)

Lin, Qian; Vesecky, John F.; Zebker, Howard A.

1992-01-01

Interferometric synthetic aperture radar (INSAR) is a new way of performing topography mapping. Among the factors critical to mapping accuracy is the registration of the complex SAR images from repeated orbits. A new algorithm for registering interferometric SAR images is presented. A new figure of merit, the average fluctuation function of the phase difference image, is proposed to evaluate the fringe pattern quality. The process of adjusting the registration parameters according to the fringe pattern quality is optimized through a downhill simplex minimization algorithm. The results of applying the proposed algorithm to register two pairs of Seasat SAR images with a short baseline (75 m) and a long baseline (500 m) are shown. It is found that the average fluctuation function is a very stable measure of fringe pattern quality allowing very accurate registration.

Integrated image presentation of transmission and fluorescent X-ray CT using synchrotron radiation

NASA Astrophysics Data System (ADS)

Zeniya, T.; Takeda, T.; Yu, Q.; Hasegawa, Y.; Hyodo, K.; Yuasa, T.; Hiranaka, Y.; Itai, Y.; Akatsuka, T.

2001-07-01

We have developed a computed tomography (CT) system with synchrotron radiation (SR) to detect fluorescent X-rays and transmitted X-rays simultaneously. Both SR transmission X-ray CT (SR-TXCT) and SR fluorescent X-ray CT (SR-FXCT) can describe cross-sectional images with high spatial and contrast resolutions as compared to conventional CT. TXCT gives morphological information and FXCT gives functional information of organs. So, superposed display system for SR-FXCT and SR-TXCT images has been developed for clinical diagnosis with higher reliability. Preliminary experiment with brain phantom was carried out and the superposition of both images was performed. The superposed SR-CT image gave us both functional and morphological information easily with high reliability, thus demonstrating the usefulness of this system.

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.

Effect of Using 2 mm Voxels on Observer Performance for PET Lesion Detection

NASA Astrophysics Data System (ADS)

Morey, A. M.; Noo, Frédéric; Kadrmas, Dan J.

2016-06-01

Positron emission tomography (PET) images are typically reconstructed with an in-plane pixel size of approximately 4 mm for cancer imaging. The objective of this work was to evaluate the effect of using smaller pixels on general oncologic lesion-detection. A series of observer studies was performed using experimental phantom data from the Utah PET Lesion Detection Database, which modeled whole-body FDG PET cancer imaging of a 92 kg patient. The data comprised 24 scans over 4 days on a Biograph mCT time-of-flight (TOF) PET/CT scanner, with up to 23 lesions (diam. 6-16 mm) distributed throughout the phantom each day. Images were reconstructed with 2.036 mm and 4.073 mm pixels using ordered-subsets expectation-maximization (OSEM) both with and without point spread function (PSF) modeling and TOF. Detection performance was assessed using the channelized non-prewhitened numerical observer with localization receiver operating characteristic (LROC) analysis. Tumor localization performance and the area under the LROC curve were then analyzed as functions of the pixel size. In all cases, the images with 2 mm pixels provided higher detection performance than those with 4 mm pixels. The degree of improvement from the smaller pixels was larger than that offered by PSF modeling for these data, and provided roughly half the benefit of using TOF. Key results were confirmed by two human observers, who read subsets of the test data. This study suggests that a significant improvement in tumor detection performance for PET can be attained by using smaller voxel sizes than commonly used at many centers. The primary drawback is a 4-fold increase in reconstruction time and data storage requirements.

Novel view synthesis by interpolation over sparse examples

NASA Astrophysics Data System (ADS)

Liang, Bodong; Chung, Ronald C.

2006-01-01

Novel view synthesis (NVS) is an important problem in image rendering. It involves synthesizing an image of a scene at any specified (novel) viewpoint, given some images of the scene at a few sample viewpoints. The general understanding is that the solution should bypass explicit 3-D reconstruction of the scene. As it is, the problem has a natural tie to interpolation, despite that mainstream efforts on the problem have been adopting formulations otherwise. Interpolation is about finding the output of a function f(x) for any specified input x, given a few input-output pairs {(xi,fi):i=1,2,3,...,n} of the function. If the input x is the viewpoint, and f(x) is the image, the interpolation problem becomes exactly NVS. We treat the NVS problem using the interpolation formulation. In particular, we adopt the example-based everything or interpolation (EBI) mechanism-an established mechanism for interpolating or learning functions from examples. EBI has all the desirable properties of a good interpolation: all given input-output examples are satisfied exactly, and the interpolation is smooth with minimum oscillations between the examples. We point out that EBI, however, has difficulty in interpolating certain classes of functions, including the image function in the NVS problem. We propose an extension of the mechanism for overcoming the limitation. We also present how the extended interpolation mechanism could be used to synthesize images at novel viewpoints. Real image results show that the mechanism has promising performance, even with very few example images.

Functional magnetic resonance imaging reflects changes in brain functioning with sedation.

PubMed

Starbuck, Victoria N; Kay, Gary G; Platenberg, R. Craig; Lin, Chin-Shoou; Zielinski, Brandon A

2000-12-01

Functional magnetic resonance imaging (fMRI) studies have demonstrated localized brain activation during cognitive tasks. Brain activation increases with task complexity and decreases with familiarity. This study investigates how sleepiness alters the relationship between brain activation and task familiarity. We hypothesize that sleepiness prevents the reduction in activation associated with practice. Twenty-nine individuals rated their sleepiness using the Stanford Sleepiness Scale before fMRI. During imaging, subjects performed the Paced Auditory Serial Addition Test, a continuous mental arithmetic task. A positive correlation was observed between self-rated sleepiness and frontal brain activation. Fourteen subjects participated in phase 2. Sleepiness was induced by evening dosing with chlorpheniramine (CP) (8 mg or 12 mg) and terfenadine (60 mg) in the morning for 3 days before the second fMRI scan. The Multiple Sleep Latency Test (MSLT) was also performed. Results revealed a significant increase in fMRI activation in proportion to the dose of CP. In contrast, for all subjects receiving placebo there was a reduction in brain activation. MSLT revealed significant daytime sleepiness for subjects receiving CP. These findings suggest that sleepiness interferes with efficiency of brain functioning. The sleepy or sedated brain shows increased oxygen utilization during performance of a familiar cognitive task. Thus, the beneficial effect of prior task exposure is lost under conditions of sedation. Copyright 2000 John Wiley & Sons, Ltd.

Early evaluation of MDIS workstations at Madigan Army Medical Center

NASA Astrophysics Data System (ADS)

Leckie, Robert G.; Goeringer, Fred; Smith, Donald V.; Bender, Gregory N.; Choi, Hyung-Sik; Haynor, David R.; Kim, Yongmin

1993-06-01

The image viewing workstation is an all-important link in the PACS (Picture Archiving and Communications System) chain since it represents the interface between the system and the user. For PACS to function, the working environment and transfer of information to the user must be the same or better than the traditional film-based system. The important characteristics of a workstation from a clinical standpoint are acceptable image quality, rapid response time, a friendly user interface, and a well-integrated, highly-reliable, fault-tolerant system which provides the user ample functions to complete his tasks successfully. Since early 1992, the MDIS (Medical Diagnostic Imaging Support) system's diagnostic and clinical workstations have been installed at Madigan Army Medical Center. Various functionalities and performance characteristics of the MDIS workstations such as image display, response time, database, and ergonomics will be presented. User comments and early experience with the workstations as well as new functionality recommended for the future will be discussed.

Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology

NASA Astrophysics Data System (ADS)

Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Development and Performance Evaluation of Image-Based Robotic Waxing System for Detailing Automobiles

PubMed Central

Hsu, Bing-Cheng

2018-01-01

Waxing is an important aspect of automobile detailing, aimed at protecting the finish of the car and preventing rust. At present, this delicate work is conducted manually due to the need for iterative adjustments to achieve acceptable quality. This paper presents a robotic waxing system in which surface images are used to evaluate the quality of the finish. An RGB-D camera is used to build a point cloud that details the sheet metal components to enable path planning for a robot manipulator. The robot is equipped with a multi-axis force sensor to measure and control the forces involved in the application and buffing of wax. Images of sheet metal components that were waxed by experienced car detailers were analyzed using image processing algorithms. A Gaussian distribution function and its parameterized values were obtained from the images for use as a performance criterion in evaluating the quality of surfaces prepared by the robotic waxing system. Waxing force and dwell time were optimized using a mathematical model based on the image-based criterion used to measure waxing performance. Experimental results demonstrate the feasibility of the proposed robotic waxing system and image-based performance evaluation scheme. PMID:29757940

Development and Performance Evaluation of Image-Based Robotic Waxing System for Detailing Automobiles.

PubMed

Lin, Chi-Ying; Hsu, Bing-Cheng

2018-05-14

Waxing is an important aspect of automobile detailing, aimed at protecting the finish of the car and preventing rust. At present, this delicate work is conducted manually due to the need for iterative adjustments to achieve acceptable quality. This paper presents a robotic waxing system in which surface images are used to evaluate the quality of the finish. An RGB-D camera is used to build a point cloud that details the sheet metal components to enable path planning for a robot manipulator. The robot is equipped with a multi-axis force sensor to measure and control the forces involved in the application and buffing of wax. Images of sheet metal components that were waxed by experienced car detailers were analyzed using image processing algorithms. A Gaussian distribution function and its parameterized values were obtained from the images for use as a performance criterion in evaluating the quality of surfaces prepared by the robotic waxing system. Waxing force and dwell time were optimized using a mathematical model based on the image-based criterion used to measure waxing performance. Experimental results demonstrate the feasibility of the proposed robotic waxing system and image-based performance evaluation scheme.

Hard X-ray imaging spectroscopy of FOXSI microflares

NASA Astrophysics Data System (ADS)

Glesener, Lindsay; Krucker, Sam; Christe, Steven; Buitrago-Casas, Juan Camilo; Ishikawa, Shin-nosuke; Foster, Natalie

2015-04-01

The ability to investigate particle acceleration and hot thermal plasma in solar flares relies on hard X-ray imaging spectroscopy using bremsstrahlung emission from high-energy electrons. Direct focusing of hard X-rays (HXRs) offers the ability to perform cleaner imaging spectroscopy of this emission than has previously been possible. Using direct focusing, spectra for different sources within the same field of view can be obtained easily since each detector segment (pixel or strip) measures the energy of each photon interacting within that segment. The Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket payload has successfully completed two flights, observing microflares each time. Flare images demonstrate an instrument imaging dynamic range far superior to the indirect methods of previous instruments like the RHESSI spacecraft.In this work, we present imaging spectroscopy of microflares observed by FOXSI in its two flights. Imaging spectroscopy performed on raw FOXSI images reveals the temperature structure of flaring loops, while more advanced techniques such as deconvolution of the point spread function produce even more detailed images.

Comparison of analytic and iterative digital tomosynthesis reconstructions for thin slab objects

NASA Astrophysics Data System (ADS)

Yun, J.; Kim, D. W.; Ha, S.; Kim, H. K.

2017-11-01

For digital x-ray tomosynthesis of thin slab objects, we compare the tomographic imaging performances obtained from the filtered backprojection (FBP) and simultaneous algebraic reconstruction (SART) algorithms. The imaging performance includes the in-plane molulation-transfer function (MTF), the signal difference-to-noise ratio (SDNR), and the out-of-plane blur artifact or artifact-spread function (ASF). The MTF is measured using a thin tungsten-wire phantom, and the SDNR and the ASF are measured using a thin aluminum-disc phantom embedded in a plastic cylinder. The FBP shows a better MTF performance than the SART. On the contrary, the SART outperforms the FBP with regard to the SDNR and ASF performances. Detailed experimental results and their analysis results are described in this paper. For a more proper use of digital tomosynthesis technique, this study suggests to use a reconstuction algorithm suitable for application-specific purposes.

Dorsolateral prefrontal cortex activation during emotional anticipation and neuropsychological performance in posttraumatic stress disorder.

PubMed

Aupperle, Robin L; Allard, Carolyn B; Grimes, Erin M; Simmons, Alan N; Flagan, Taru; Behrooznia, Michelle; Cissell, Shadha H; Twamley, Elizabeth W; Thorp, Steven R; Norman, Sonya B; Paulus, Martin P; Stein, Murray B

2012-04-01

Posttraumatic stress disorder (PTSD) has been associated with executive or attentional dysfunction and problems in emotion processing. However, it is unclear whether these two domains of dysfunction are related to common or distinct neurophysiological substrates. To examine the hypothesis that greater neuropsychological impairment in PTSD relates to greater disruption in prefrontal-subcortical networks during emotional anticipation. Case-control, cross-sectional study. General community and hospital and community psychiatric clinics. Volunteer sample of 37 women with PTSD related to intimate partner violence and 34 age-comparable healthy control women. We used functional magnetic resonance imaging (fMRI) to examine neural responses during anticipation of negative and positive emotional images. The Clinician-Administered PTSD Scale was used to characterize PTSD symptom severity. The Wechsler Adult Intelligence Scale, Third Edition, Digit Symbol Test, Delis-Kaplan Executive Function System Color-Word Interference Test, and Wisconsin Card Sorting Test were used to characterize neuropsychological performance. Women with PTSD performed worse on complex visuomotor processing speed (Digit Symbol Test) and executive function (Color-Word Interference Inhibition/Switching subtest) measures compared with control subjects. Posttraumatic stress disorder was associated with greater anterior insula and attenuated lateral prefrontal cortex (PFC) activation during emotional anticipation. Greater dorsolateral PFC activation (anticipation of negative images minus anticipation of positive images) was associated with lower PTSD symptom severity and better visuomotor processing speed and executive functioning. Greater medial PFC and amygdala activation related to slower visuomotor processing speed. During emotional anticipation, women with PTSD show exaggerated activation in the anterior insula, a region important for monitoring internal bodily state. Greater dorsolateral PFC response in PTSD patients during emotional anticipation may reflect engagement of cognitive control networks that are beneficial for emotional and cognitive functioning. Novel treatments could be aimed at strengthening the balance between cognitive control (dorsolateral PFC) and affective processing (medial PFC and amygdala) networks to improve overall functioning for PTSD patients.

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

PubMed

Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

2017-03-21

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

Rehabilitation-triggered cortical plasticity after stroke: in vivo imaging at multiple scales (Conference Presentation)

NASA Astrophysics Data System (ADS)

Allegra Mascaro, Anna Letizia; Conti, Emilia; Lai, Stefano; Spalletti, Cristina; Di Giovanna, Antonino Paolo; Alia, Claudia; Panarese, Alessandro; Sacconi, Leonardo; Micera, Silvestro; Caleo, Matteo; Pavone, Francesco S.

2017-02-01

Neurorehabilitation protocols based on the use of robotic devices provide a highly repeatable therapy and have recently shown promising clinical results. Little is known about how rehabilitation molds the brain to promote motor recovery of the affected limb. We used a custom-made robotic platform that provides quantitative assessment of forelimb function in a retraction test. Complementary imaging techniques allowed us to access to the multiple facets of robotic rehabilitation-induced cortical plasticity after unilateral photothrombotic stroke in mice Primary Motor Cortex (Caudal Forelimb Area - CFA). First, we analyzed structural features of vasculature and dendritic reshaping in the peri-infarct area with two-photon fluorescence microscopy. Longitudinal analysis of dendritic branches and spines of pyramidal neurons suggests that robotic rehabilitation promotes the stabilization of peri-infarct cortical excitatory circuits, which is not accompanied by consistent vascular reorganization towards pre-stroke conditions. To investigate if this structural stabilization was linked to functional remapping, we performed mesoscale wide-field imaging on GCaMP6 mice while performing the motor task on the robotic platform. We revealed temporal and spatial features of the motor-triggered cortical activation, shining new light on rehabilitation-induced functional remapping of the ipsilesional cortex. Finally, by using an all-optical approach that combines optogenetic activation of the contralesional hemisphere and wide-field functional imaging of peri-infarct area, we dissected the effect of robotic rehabilitation on inter-hemispheric cortico-cortical connectivity.

An automated multi-scale network-based scheme for detection and location of seismic sources

NASA Astrophysics Data System (ADS)

Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

2017-12-01

We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

Priming Hand Motor Training with Repetitive Stimulation of the Fingertips; Performance Gain and Functional Imaging of Training Effects.

PubMed

Lotze, Martin; Ladda, Aija Marie; Roschka, Sybille; Platz, Thomas; Dinse, Hubert R

Application of repetitive electrical stimulation (rES) of the fingers has been shown to improve tactile perception and sensorimotor performance in healthy individuals. To increase motor performance by priming the effects of active motor training (arm ability training; AAT) using rES. We compared the performance gain for the training increase of the averaged AAT tasks of both hands in two groups of strongly right-handed healthy volunteers. Functional Magnetic Resonance Imaging (fMRI) before and after AAT was assessed using three tasks for each hand separately: finger sequence tapping, visually guided grip force modulation, and writing. Performance during fMRI was controlled for preciseness and frequency. A total of 30 participants underwent a two-week unilateral left hand AAT, 15 participants with 20 minutes of rES priming of all fingertips of the trained hand, and 15 participants without rES priming. rES-primed AAT improved the trained left-hand performance across all training tasks on average by 32.9%, non-primed AAT improved by 29.5%. This gain in AAT performance with rES priming was predominantly driven by an increased finger tapping velocity. Functional imaging showed comparable changes for both training groups over time. Across all participants, improved AAT performance was associated with a higher contralateral primary somatosensory cortex (S1) fMRI activation magnitude during the grip force modulation task. This study highlights the importance of S1 for hand motor training gain. In addition, it suggests the usage of rES of the fingertips for priming active hand motor training. Copyright © 2016 Elsevier Inc. All rights reserved.

Importance of balanced architectures in the design of high-performance imaging systems

NASA Astrophysics Data System (ADS)

Sgro, Joseph A.; Stanton, Paul C.

1999-03-01

Imaging systems employed in demanding military and industrial applications, such as automatic target recognition and computer vision, typically require real-time high-performance computing resources. While high- performances computing systems have traditionally relied on proprietary architectures and custom components, recent advances in high performance general-purpose microprocessor technology have produced an abundance of low cost components suitable for use in high-performance computing systems. A common pitfall in the design of high performance imaging system, particularly systems employing scalable multiprocessor architectures, is the failure to balance computational and memory bandwidth. The performance of standard cluster designs, for example, in which several processors share a common memory bus, is typically constrained by memory bandwidth. The symptom characteristic of this problem is failure to the performance of the system to scale as more processors are added. The problem becomes exacerbated if I/O and memory functions share the same bus. The recent introduction of microprocessors with large internal caches and high performance external memory interfaces makes it practical to design high performance imaging system with balanced computational and memory bandwidth. Real word examples of such designs will be presented, along with a discussion of adapting algorithm design to best utilize available memory bandwidth.

Don’t be Too Strict with Yourself! Rigid Negative Self-Representation in Healthy Subjects Mimics the Neurocognitive Profile of Depression for Autobiographical Memory

PubMed Central

Sperduti, Marco; Martinelli, Pénélope; Kalenzaga, Sandrine; Devauchelle, Anne-Dominique; Lion, Stéphanie; Malherbe, Caroline; Gallarda, Thierry; Amado, Isabelle; Krebs, Marie-Odile; Oppenheim, Catherine; Piolino, Pascale

2013-01-01

Autobiographical memory (AM) comprises representation of both specific (episodic) and generic (semantic) personal information. Depression is characterized by a shift from episodic to semantic AM retrieval. According to theoretical models, this process (“overgeneralization”), would be linked to reduced executive resources. Moreover, “overgeneral” memories, accompanied by a negativity bias in depression, lead to a pervasive negative self-representation. As executive functions and AM specificity are also closely intricate among “non-clinical” populations, “overgeneral” memories could result in depressive emotional responses. Consequently, our hypothesis was that the neurocognitive profile of healthy subjects showing a rigid negative self-image would mimic that of patients. Executive functions and self-image were measured and brain activity was recorded, by means of fMRI, during episodic AMs retrieval in young healthy subjects. The results show an inverse correlation, that is, a more rigid and negative self-image produces lower performances in both executive and specific memories. Moreover, higher negative self-image is associated with decreased activity in the left ventro-lateral prefrontal and in the anterior cingulate cortex, repeatedly shown to exhibit altered functioning in depression. Activity in these regions, on the contrary, positively correlates with executive and memory performances, in line with their role in executive functions and AM retrieval. These findings suggest that rigid negative self-image could represent a marker or a vulnerability trait of depression by being linked to reduced executive function efficiency and episodic AM decline. These results are encouraging for psychotherapeutic approaches aimed at cognitive flexibility in depression and other psychiatric disorders. PMID:23734107

Integration of radiographic images with an electronic medical record.

PubMed Central

Overhage, J. M.; Aisen, A.; Barnes, M.; Tucker, M.; McDonald, C. J.

2001-01-01

Radiographic images are important and expensive diagnostic tests. However, the provider caring for the patient often does not review the images directly due to time constraints. Institutions can use picture archiving and communications systems to make images more available to the provider, but this may not be the best solution. We integrated radiographic image review into the Regenstrief Medical Record System in order to address this problem. To achieve adequate performance, we store JPEG compressed images directly in the RMRS. Currently, physicians review about 5% of all radiographic studies using the RMRS image review function. PMID:11825241

Arterial input function derived from pairwise correlations between PET-image voxels.

PubMed

Schain, Martin; Benjaminsson, Simon; Varnäs, Katarina; Forsberg, Anton; Halldin, Christer; Lansner, Anders; Farde, Lars; Varrone, Andrea

2013-07-01

A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [(11)C]flumazenil and [(11)C]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (VT) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in VT was good (∼3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.

Functional Imaging of the Lungs with Gas Agents

PubMed Central

Kruger, Stanley J.; Nagle, Scott K.; Couch, Marcus J.; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B.

2015-01-01

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI) – hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas – and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multi-detector computed tomography (CT). However, MRI also offers capabilities for fast multi-spectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultra-short echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. Relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF) in both adults and children. PMID:26218920

Evaluation of modulation transfer function of optical lens system by support vector regression methodologies - A comparative study

NASA Astrophysics Data System (ADS)

Petković, Dalibor; Shamshirband, Shahaboddin; Saboohi, Hadi; Ang, Tan Fong; Anuar, Nor Badrul; Rahman, Zulkanain Abdul; Pavlović, Nenad T.

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict estimate MTF value of the actual optical system according to experimental tests. Instead of minimizing the observed training error, SVR_poly and SVR_rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR_rbf approach in compare to SVR_poly soft computing methodology.

3D elemental sensitive imaging using transmission X-ray microscopy.

PubMed

Liu, Yijin; Meirer, Florian; Wang, Junyue; Requena, Guillermo; Williams, Phillip; Nelson, Johanna; Mehta, Apurva; Andrews, Joy C; Pianetta, Piero

2012-09-01

Determination of the heterogeneous distribution of metals in alloy/battery/catalyst and biological materials is critical to fully characterize and/or evaluate the functionality of the materials. Using synchrotron-based transmission x-ray microscopy (TXM), it is now feasible to perform nanoscale-resolution imaging over a wide X-ray energy range covering the absorption edges of many elements; combining elemental sensitive imaging with determination of sample morphology. We present an efficient and reliable methodology to perform 3D elemental sensitive imaging with excellent sample penetration (tens of microns) using hard X-ray TXM. A sample of an Al-Si piston alloy is used to demonstrate the capability of the proposed method.

A wireless handheld probe with spectrally constrained evolution strategies for diffuse optical imaging of tissue

NASA Astrophysics Data System (ADS)

Flexman, M. L.; Kim, H. K.; Stoll, R.; Khalil, M. A.; Fong, C. J.; Hielscher, A. H.

2012-03-01

We present a low-cost, portable, wireless diffuse optical imaging device. The handheld device is fast, portable, and can be applied to a wide range of both static and dynamic imaging applications including breast cancer, functional brain imaging, and peripheral artery disease. The continuous-wave probe has four near-infrared wavelengths and uses digital detection techniques to perform measurements at 2.3 Hz. Using a multispectral evolution algorithm for chromophore reconstruction, we can measure absolute oxygenated and deoxygenated hemoglobin concentration as well as scattering in tissue. Performance of the device is demonstrated using a series of liquid phantoms comprised of Intralipid®, ink, and dye.

Evaluation of the image quality of telescopes using the star test

NASA Astrophysics Data System (ADS)

Vazquez y Monteil, Sergio; Salazar Romero, Marcos A.; Gale, David M.

2004-10-01

The Point Spread Function (PSF) or star test is one of the main criteria to be considered in the quality of the image formed by a telescope. In a real system the distribution of irradiance in the image of a point source is given by the PSF, a function which is highly sensitive to aberrations. The PSF of a telescope may be determined by measuring the intensity distribution in the image of a star. Alternatively, if we already know the aberrations present in the optical system, then we may use diffraction theory to calculate the function. In this paper we propose a method for determining the wavefront aberrations from the PSF, using Genetic Algorithms to perform an optimization process starting from the PSF instead of the more traditional method of adjusting an aberration polynomial. We show that this method of phase recuperation is immune to noise-induced errors arising during image aquisition and registration. Some practical results are shown.

SPED light sheet microscopy: fast mapping of biological system structure and function

PubMed Central

Tomer, Raju; Lovett-Barron, Matthew; Kauvar, Isaac; Andalman, Aaron; Burns, Vanessa M.; Sankaran, Sethuraman; Grosenick, Logan; Broxton, Michael; Yang, Samuel; Deisseroth, Karl

2016-01-01

The goal of understanding living nervous systems has driven interest in high-speed and large field-of-view volumetric imaging at cellular resolution. Light-sheet microscopy approaches have emerged for cellular-resolution functional brain imaging in small organisms such as larval zebrafish, but remain fundamentally limited in speed. Here we have developed SPED light sheet microscopy, which combines large volumetric field-of-view via an extended depth of field with the optical sectioning of light sheet microscopy, thereby eliminating the need to physically scan detection objectives for volumetric imaging. SPED enables scanning of thousands of volumes-per-second, limited only by camera acquisition rate, through the harnessing of optical mechanisms that normally result in unwanted spherical aberrations. We demonstrate capabilities of SPED microscopy by performing fast sub-cellular resolution imaging of CLARITY mouse brains and cellular-resolution volumetric Ca2+ imaging of entire zebrafish nervous systems. Together, SPED light sheet methods enable high-speed cellular-resolution volumetric mapping of biological system structure and function. PMID:26687363

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Targeting Neuronal-like Metabolism of Metastatic Tumor Cells as a Novel Therapy for Breast Cancer Brain Metastasis

DTIC Science & Technology

2017-03-01

Contribution to Project: Ian primarily focuses on developing tissue imaging pipeline and perform imaging data analysis . Funding Support: Partially...3D ReconsTruction), a multi-faceted image analysis pipeline , permitting quantitative interrogation of functional implications of heterogeneous... analysis pipeline , to observe and quantify phenotypic metastatic landscape heterogeneity in situ with spatial and molecular resolution. Our implementation

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

Potter, T.; McClain, C.J.; Shafer, R.B.

Ten patients were prospectively studied using 99mTc-PIPIDA imaging to evaluate the effects of fasting and parenteral alimentation on gallbladder function. Three of ten patients had initial nonvisualization of the gallbladder for up to 2 hr, yet had normal visualization on repeat imaging performed after resumption of oral intake or after parenteral alimentation was discontinued. 99mTc-PIPIDA imaging should be interpreted with caution in patients fitting into either of these groups.

Magnetic Resonance Imaging of Gel-cast Ceramic Composites

DOE R&D Accomplishments Database

Dieckman, S. L.; Balss, K. M.; Waterfield, L. G.; Jendrzejczyk, J. A.; Raptis, A. C.

1997-01-16

Magnetic resonance imaging (MRI) techniques are being employed to aid in the development of advanced near-net-shape gel-cast ceramic composites. MRI is a unique nondestructive evaluation tool that provides information on both the chemical and physical properties of materials. In this effort, MRI imaging was performed to monitor the drying of porous green-state alumina - methacrylamide-N.N`-methylene bisacrylamide (MAM-MBAM) polymerized composite specimens. Studies were performed on several specimens as a function of humidity and time. The mass and shrinkage of the specimens were also monitored and correlated with the water content.

Functional imaging to monitor vascular and metabolic response in canine head and neck tumors during fractionated radiotherapy.

PubMed

Rødal, Jan; Rusten, Espen; Søvik, Åste; Skogmo, Hege Kippenes; Malinen, Eirik

2013-10-01

Radiotherapy causes alterations in tumor biology, and non-invasive early assessment of such alterations may become useful for identifying treatment resistant disease. The purpose of the current work is to assess changes in vascular and metabolic features derived from functional imaging of canine head and neck tumors during fractionated radiotherapy. Material and methods. Three dogs with spontaneous head and neck tumors received intensity-modulated radiotherapy (IMRT). Contrast-enhanced cone beam computed tomography (CE-CBCT) at the treatment unit was performed at five treatment fractions. Dynamic (18)FDG-PET (D-PET) was performed prior to the start of radiotherapy, at mid-treatment and at 3-12 weeks after the completion of treatment. Tumor contrast enhancement in the CE-CBCT images was used as a surrogate for tumor vasculature. Vascular and metabolic tumor parameters were further obtained from the D-PET images. Changes in these tumor parameters were assessed, with emphasis on intra-tumoral distributions. Results. For all three patients, metabolic imaging parameters obtained from D-PET decreased from the pre- to the inter-therapy session. Correspondingly, for two of three patients, vascular imaging parameters obtained from both CE-CBCT and D-PET increased. Only one of the tumors showed a clear metabolic response after therapy. No systematic changes in the intra-tumor heterogeneity in the imaging parameters were found. Conclusion. Changes in vascular and metabolic parameters could be detected by the current functional imaging methods. Vascular tumor features from CE-CBCT and D-PET corresponded well. CE-CBCT is a potential method for easy response assessment when the patient is at the treatment unit.

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

PubMed

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

Characteristic of x-ray tomography performance using CdTe timepix detector

NASA Astrophysics Data System (ADS)

Zain, R. M.; O'Shea, V.; Maneuski, D.

2017-01-01

X-ray Computed Tomography (CT) is a non-destructive technique for visualizing interior features within solid objects, and for obtaining digital information on their 3-D geometries and properties. The selection of CdTe Timepix detector has a sufficient performance of imaging detector is based on quality of detector performance and energy resolution. The study of Modulation Transfer Function (MTF) shows a 70% contrast at 4 lp/mm was achieved for the 55 µm pixel pitch detector with the 60 kVp X-ray tube and 5 keV noise level. No significant degradation in performance was observed for X-ray tube energies of 20 - 60 keV. The paper discusses the application of the CdTe Timepix detector to produce a good quality image of X-ray tomography imaging.

The role of long-term physical exercise on performance and brain activation during the Stroop colour word task in fibromyalgia patients.

PubMed

Martinsen, S; Flodin, P; Berrebi, J; Löfgren, M; Bileviciute-Ljungar, I; Mannerkorpi, K; Ingvar, M; Fransson, P; Kosek, E

2018-05-01

The Stroop colour word test (SCWT) has been widely used to assess changes in cognitive performance such as processing speed, selective attention and the degree of automaticity. Moreover, the SCWT has proven to be a valuable tool to assess neuronal plasticity that is coupled to improvement in performance in clinical populations. In a previous study, we showed impaired cognitive processing during SCWT along with reduced task-related activations in patients with fibromyalgia. In this study, we used SCWT and functional magnetic resonance imagingFMRI to investigate the effects of a 15-week physical exercise intervention on cognitive performance, task-related cortical activation and distraction-induced analgesia (DIA) in patients with fibromyalgia and healthy controls. The exercise intervention yielded reduced fibromyalgia symptoms, improved cognitive processing and increased task-related activation of amygdala, but no effect on DIA. Our results suggest beneficial effects of physical exercise on cognitive functioning in FM. © 2017 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine.

Radioaerosol lung imaging in chronic obstructive pulmonary disease. Comparison with pulmonary function tests and roentgenography. [/sup 113m/In, /sup 99m/Tc, /sup 133/Xe tracer techniques

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

Ramanna, L.; Tashkin, D.P.; Taplin, G.V.

1975-11-01

Seventy subjects with either no, mild, or definite evidence of pulmonary abnormality on screening studies volunteered to have detailed pulmonary function tests (PFTs), respiratory questionnaires, physical examinations, and /sup 113m/indium aerosol-inhalation lung imaging performed. Also, 22 and 52 of these subjects underwent /sup 133/xenon ventilation and lung perfusion imaging with /sup 99m/technetium-labelled macroaggregated albumin, and 56 had chest x-ray examinations performed. Results of the radionuclide lung-imaging procedures were compared with those of conventional PFTs and other clinical diagnostic procedures used to identify chronic obstructive pulmonary disease (COPD). Abnormal radioaerosol patterns were found in 32 of 33 subjects with abnormal findingsmore » on PFTs, whereas results of PFTs were abnormal in only 32 of 46 subjects with abnormal aerosol deposition. Aerosol lung images were abnormal more frequently than respiratory questionnaire responses, findings on physical examination, chest x-ray films, and perfusion lung images and with approximately the same frequency as /sup 133/xenon ventilation scintiscans. These results suggest that radioaerosol lung imaging may be a more sensitive indicator of early COPD than other diagnostic procedures, including maximal midexpiratory flow rates, single-breath nitrogen washout, and closing volume. Further studies are required to determine the physiologic and pathologic significance of isolated aerosol lung-imaging abnormalities.« less

Rare-earth doped nanocomposites enable multiscale targeted short-wave infrared imaging of metastatic breast cancer

NASA Astrophysics Data System (ADS)

Pierce, Mark C.; Higgins, Laura M.; Ganapathy, Vidya; Kantamneni, Harini; Riman, Richard E.; Roth, Charles M.; Moghe, Prabhas V.

2017-02-01

We are investigating the ability of targeted rare earth (RE) doped nanocomposites to detect and track micrometastatic breast cancer lesions to distant sites in pre-clinical in vivo models. Functionalizing RE nanocomposites with AMD3100 promotes targeting to CXCR4, a recognized marker for highly metastatic disease. Mice were inoculated with SCP-28 (CXCR4 positive) and 4175 (CXCR4 negative) cell lines. Whole animal in vivo SWIR fluorescence imaging was performed after bioluminescence imaging confirmed tumor burden in the lungs. Line-scanning confocal fluorescence microscopy provided high-resolution imaging of RE nanocomposite uptake and native tissue autofluorescence in ex vivo lung specimens. Co-registered optical coherence tomography imaging allowed assessment of tissue microarchitecture. In conclusion, multiscale optical molecular imaging can be performed in pre-clinical models of metastatic breast cancer, using targeted RE-doped nanocomposites.

On use of image quality metrics for perceptual blur modeling: image/video compression case

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

2018-02-01

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

Objective measurement of the optical image quality in the human eye

NASA Astrophysics Data System (ADS)

Navarro, Rafael M.

2001-05-01

This communication reviews some recent studies on the optical performance of the human eye. Although the retinal image cannot be recorded directly, different objective methods have been developed, which permit to determine optical quality parameters, such as the Point Spread Function (PSF), the Modulation Transfer Function (MTF), the geometrical ray aberrations or the wavefront distortions, in the living human eye. These methods have been applied in both basic and applied research. This includes the measurement of the optical performance of the eye across visual field, the optical quality of eyes with intraocular lens implants, the aberrations induced by LASIK refractive surgery, or the manufacture of customized phase plates to compensate the wavefront aberration in the eye.

PET imaging in the assessment of normal and impaired cognitive function.

PubMed

Silverman, Daniel H S; Alavi, Abass

2005-01-01

PET has been used to directly quantify several processes relevant to the status of cerebral health and function, including cerebral blood flow, cerebral blood volume, cerebral rate of oxygen metabolism, and cerebral glucose use. Clinically, the most commonly performed PET studies of the brain are performed with fluorine-18-fluorodeoxyglucose as the imaged radiopharmaceutical. Such scans have demonstrated diagnostic and prognostic use in evaluating patients who have cognitive impairment, and in distinguishing among primary neurodegenerative dementias and other causes of cognitive decline. In certain pathologic circumstances, the normal coupling between blood flow and metabolic needs may be disturbed, and changes in oxygen extraction fraction can have significant prognostic value.

NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Howle, W. M.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Clustered functional MRI of overt speech production.

PubMed

Sörös, Peter; Sokoloff, Lisa Guttman; Bose, Arpita; McIntosh, Anthony R; Graham, Simon J; Stuss, Donald T

2006-08-01

To investigate the neural network of overt speech production, event-related fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speech-related movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the cortical and subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum, reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.

Electroencephalographic imaging of higher brain function

NASA Technical Reports Server (NTRS)

Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.

1999-01-01

High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

A method to determine the impact of reduced visual function on nodule detection performance.

PubMed

Thompson, J D; Lança, C; Lança, L; Hogg, P

2017-02-01

In this study we aim to validate a method to assess the impact of reduced visual function and observer performance concurrently with a nodule detection task. Three consultant radiologists completed a nodule detection task under three conditions: without visual defocus (0.00 Dioptres; D), and with two different magnitudes of visual defocus (-1.00 D and -2.00 D). Defocus was applied with lenses and visual function was assessed prior to each image evaluation. Observers evaluated the same cases on each occasion; this comprised of 50 abnormal cases containing 1-4 simulated nodules (5, 8, 10 and 12 mm spherical diameter, 100 HU) placed within a phantom, and 25 normal cases (images containing no nodules). Data was collected under the free-response paradigm and analysed using Rjafroc. A difference in nodule detection performance would be considered significant at p < 0.05. All observers had acceptable visual function prior to beginning the nodule detection task. Visual acuity was reduced to an unacceptable level for two observers when defocussed to -1.00 D and for one observer when defocussed to -2.00 D. Stereoacuity was unacceptable for one observer when defocussed to -2.00 D. Despite unsatisfactory visual function in the presence of defocus we were unable to find a statistically significant difference in nodule detection performance (F(2,4) = 3.55, p = 0.130). A method to assess visual function and observer performance is proposed. In this pilot evaluation we were unable to detect any difference in nodule detection performance when using lenses to reduce visual function. Copyright © 2016 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

The relationship between bilingualism and selective attention in young adults: Evidence from an ambiguous figures task.

PubMed

Chung-Fat-Yim, Ashley; Sorge, Geoff B; Bialystok, Ellen

2017-03-01

Previous research has shown that bilinguals outperform monolinguals on a variety of tasks that have been described as involving executive functioning, but the precise mechanism for those effects or a clear definition for "executive function" is unknown. This uncertainty has led to a number of studies for which no performance difference between monolingual and bilingual adults has been detected. One approach to clarifying these issues comes from research with children showing that bilinguals were more able than their monolingual peers to perceive both interpretations of an ambiguous figure, an ability that is more tied to a conception of selective attention than to specific components of executive function. The present study extends this notion to adults by assessing their ability to see the alternative image in an ambiguous figure. Bilinguals performed this task more efficiently than monolinguals by requiring fewer cues to identify the second image. This finding has implications for the role of selective attention in performance differences between monolinguals and bilinguals.

Generalized Scalar-on-Image Regression Models via Total Variation.

PubMed

Wang, Xiao; Zhu, Hongtu

2017-01-01

The use of imaging markers to predict clinical outcomes can have a great impact in public health. The aim of this paper is to develop a class of generalized scalar-on-image regression models via total variation (GSIRM-TV), in the sense of generalized linear models, for scalar response and imaging predictor with the presence of scalar covariates. A key novelty of GSIRM-TV is that it is assumed that the slope function (or image) of GSIRM-TV belongs to the space of bounded total variation in order to explicitly account for the piecewise smooth nature of most imaging data. We develop an efficient penalized total variation optimization to estimate the unknown slope function and other parameters. We also establish nonasymptotic error bounds on the excess risk. These bounds are explicitly specified in terms of sample size, image size, and image smoothness. Our simulations demonstrate a superior performance of GSIRM-TV against many existing approaches. We apply GSIRM-TV to the analysis of hippocampus data obtained from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset.

Contour-Driven Atlas-Based Segmentation

PubMed Central

Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

2016-01-01

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

Calibration and Image Reconstruction for the Hurricane Imaging Radiometer (HIRAD)

NASA Technical Reports Server (NTRS)

Ruf, Christopher; Roberts, J. Brent; Biswas, Sayak; James, Mark W.; Miller, Timothy

2012-01-01

The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a aprox 70 km swath width with approx 3 km spatial resolution. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.

Confocal multispot microscope for fast and deep imaging in semicleared tissues

NASA Astrophysics Data System (ADS)

Adam, Marie-Pierre; Müllenbroich, Marie Caroline; Di Giovanna, Antonino Paolo; Alfieri, Domenico; Silvestri, Ludovico; Sacconi, Leonardo; Pavone, Francesco Saverio

2018-02-01

Although perfectly transparent specimens are imaged faster with light-sheet microscopy, less transparent samples are often imaged with two-photon microscopy leveraging its robustness to scattering; however, at the price of increased acquisition times. Clearing methods that are capable of rendering strongly scattering samples such as brain tissue perfectly transparent specimens are often complex, costly, and time intensive, even though for many applications a slightly lower level of tissue transparency is sufficient and easily achieved with simpler and faster methods. Here, we present a microscope type that has been geared toward the imaging of semicleared tissue by combining multispot two-photon excitation with rolling shutter wide-field detection to image deep and fast inside semicleared mouse brain. We present a theoretical and experimental evaluation of the point spread function and contrast as a function of shutter size. Finally, we demonstrate microscope performance in fixed brain slices by imaging dendritic spines up to 400-μm deep.

Optimal classification for the diagnosis of duchenne muscular dystrophy images using support vector machines.

PubMed

Zhang, Ming-Huan; Ma, Jun-Shan; Shen, Ying; Chen, Ying

2016-09-01

This study aimed to investigate the optimal support vector machines (SVM)-based classifier of duchenne muscular dystrophy (DMD) magnetic resonance imaging (MRI) images. T1-weighted (T1W) and T2-weighted (T2W) images of the 15 boys with DMD and 15 normal controls were obtained. Textural features of the images were extracted and wavelet decomposed, and then, principal features were selected. Scale transform was then performed for MRI images. Afterward, SVM-based classifiers of MRI images were analyzed based on the radical basis function and decomposition levels. The cost (C) parameter and kernel parameter [Formula: see text] were used for classification. Then, the optimal SVM-based classifier, expressed as [Formula: see text]), was identified by performance evaluation (sensitivity, specificity and accuracy). Eight of 12 textural features were selected as principal features (eigenvalues [Formula: see text]). The 16 SVM-based classifiers were obtained using combination of (C, [Formula: see text]), and those with lower C and [Formula: see text] values showed higher performances, especially classifier of [Formula: see text]). The SVM-based classifiers of T1W images showed higher performance than T1W images at the same decomposition level. The T1W images in classifier of [Formula: see text]) at level 2 decomposition showed the highest performance of all, and its overall correct sensitivity, specificity, and accuracy reached 96.9, 97.3, and 97.1 %, respectively. The T1W images in SVM-based classifier [Formula: see text] at level 2 decomposition showed the highest performance of all, demonstrating that it was the optimal classification for the diagnosis of DMD.

A novel configurable VLSI architecture design of window-based image processing method

NASA Astrophysics Data System (ADS)

Zhao, Hui; Sang, Hongshi; Shen, Xubang

2018-03-01

Most window-based image processing architecture can only achieve a certain kind of specific algorithms, such as 2D convolution, and therefore lack the flexibility and breadth of application. In addition, improper handling of the image boundary can cause loss of accuracy, or consume more logic resources. For the above problems, this paper proposes a new VLSI architecture of window-based image processing operations, which is configurable and based on consideration of the image boundary. An efficient technique is explored to manage the image borders by overlapping and flushing phases at the end of row and the end of frame, which does not produce new delay and reduce the overhead in real-time applications. Maximize the reuse of the on-chip memory data, in order to reduce the hardware complexity and external bandwidth requirements. To perform different scalar function and reduction function operations in pipeline, this can support a variety of applications of window-based image processing. Compared with the performance of other reported structures, the performance of the new structure has some similarities to some of the structures, but also superior to some other structures. Especially when compared with a systolic array processor CWP, this structure at the same frequency of approximately 12.9% of the speed increases. The proposed parallel VLSI architecture was implemented with SIMC 0.18-μm CMOS technology, and the maximum clock frequency, power consumption, and area are 125Mhz, 57mW, 104.8K Gates, respectively, furthermore the processing time is independent of the different window-based algorithms mapped to the structure

Wigner analysis of three dimensional pupil with finite lateral aperture

PubMed Central

Chen, Hsi-Hsun; Oh, Se Baek; Zhai, Xiaomin; Tsai, Jui-Chang; Cao, Liang-Cai; Barbastathis, George; Luo, Yuan

2015-01-01

A three dimensional (3D) pupil is an optical element, most commonly implemented on a volume hologram, that processes the incident optical field on a 3D fashion. Here we analyze the diffraction properties of a 3D pupil with finite lateral aperture in the 4-f imaging system configuration, using the Wigner Distribution Function (WDF) formulation. Since 3D imaging pupil is finite in both lateral and longitudinal directions, the WDF of the volume holographic 4-f imager theoretically predicts distinct Bragg diffraction patterns in phase space. These result in asymmetric profiles of diffracted coherent point spread function between degenerate diffraction and Bragg diffraction, elucidating the fundamental performance of volume holographic imaging. Experimental measurements are also presented, confirming the theoretical predictions. PMID:25836443

Objective assessment of image quality. IV. Application to adaptive optics

PubMed Central

Barrett, Harrison H.; Myers, Kyle J.; Devaney, Nicholas; Dainty, Christopher

2008-01-01

The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed. PMID:17106464

The use of vision-based image quality metrics to predict low-light performance of camera phones

NASA Astrophysics Data System (ADS)

Hultgren, B.; Hertel, D.

2010-01-01

Small digital camera modules such as those in mobile phones have become ubiquitous. Their low-light performance is of utmost importance since a high percentage of images are made under low lighting conditions where image quality failure may occur due to blur, noise, and/or underexposure. These modes of image degradation are not mutually exclusive: they share common roots in the physics of the imager, the constraints of image processing, and the general trade-off situations in camera design. A comprehensive analysis of failure modes is needed in order to understand how their interactions affect overall image quality. Low-light performance is reported for DSLR, point-and-shoot, and mobile phone cameras. The measurements target blur, noise, and exposure error. Image sharpness is evaluated from three different physical measurements: static spatial frequency response, handheld motion blur, and statistical information loss due to image processing. Visual metrics for sharpness, graininess, and brightness are calculated from the physical measurements, and displayed as orthogonal image quality metrics to illustrate the relative magnitude of image quality degradation as a function of subject illumination. The impact of each of the three sharpness measurements on overall sharpness quality is displayed for different light levels. The power spectrum of the statistical information target is a good representation of natural scenes, thus providing a defined input signal for the measurement of power-spectrum based signal-to-noise ratio to characterize overall imaging performance.

Maximizing fluorescence collection efficiency in multiphoton microscopy

PubMed Central

Zinter, Joseph P.; Levene, Michael J.

2011-01-01

Understanding fluorescence propagation through a multiphoton microscope is of critical importance in designing high performance systems capable of deep tissue imaging. Optical models of a scattering tissue sample and the Olympus 20X 0.95NA microscope objective were used to simulate fluorescence propagation as a function of imaging depth for physiologically relevant scattering parameters. The spatio-angular distribution of fluorescence at the objective back aperture derived from these simulations was used to design a simple, maximally efficient post-objective fluorescence collection system. Monte Carlo simulations corroborated by data from experimental tissue phantoms demonstrate collection efficiency improvements of 50% – 90% over conventional, non-optimized fluorescence collection geometries at large imaging depths. Imaging performance was verified by imaging layer V neurons in mouse cortex to a depth of 850 μm. PMID:21934897

Evaluation of spiral acquisition variants for functional imaging of human superior colliculus at 3T field strength.

PubMed

Singh, Vimal; Pfeuffer, Josef; Zhao, Tiejun; Ress, David

2018-04-01

High-resolution functional magnetic resonance imaging of human subcortical brain structures is challenging because of their deep location in the cranium, and their comparatively weak blood oxygen level dependent responses to strong stimuli. Magnetic resonance imaging data for subcortical brain regions exhibit both low signal-to-noise ratio and low functional contrast-to-noise ratio. To overcome these challenges, this work evaluates the use of dual-echo spiral variants that combine outward and inward trajectories. Specifically, in-in, in-out, and out-out combinations are evaluated. For completeness, single-echo spiral-in and parallel-receive-accelerated echo-planar-imaging sequences are also evaluated. Sequence evaluation was based on comparison of functional contrast-to-noise ratio within retinotopically predefined regions of interest. Superior colliculus was chosen as sample subcortical brain region because it exhibits a strong visual response. All sequences were compared relative to a single-echo spiral-out trajectory to establish a within-session reference. In superior colliculus, the dual-echo out-out outperformed the reference trajectory by 55% in contrast-to-noise ratio, while all other trajectories had performance similar to the reference. The sequences were also compared in early visual cortex. Here, both dual-echo spiral out-out and in-out outperformed the reference by ∼25%. Dual-echo spiral variants offer improved contrast-to-noise ratio performance for high-resolution imaging for both superior colliculus and cortex. Magn Reson Med 79:1931-1940, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Effect of the image resolution on the statistical descriptors of heterogeneous media.

PubMed

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Effect of the image resolution on the statistical descriptors of heterogeneous media

NASA Astrophysics Data System (ADS)

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Flexible electronic control system based on FPGA for liquid-crystal microlens

NASA Astrophysics Data System (ADS)

Zhang, Bo; Xin, Zhaowei; Li, Dapeng; Wei, Dong; Zhang, Xinyu; Wang, Haiwei; Xie, Changsheng

2018-02-01

Traditional imaging based on common optical lens can only be used to collect intensity information of incident beams, but actually lightwave also carries other mode information about targets and environment, including: spectrum, wavefront, and depth of target, and so on. It is very important to acquire those information mentioned for efficiently detecting and identifying targets in complex background. There is a urgent need to develop new high-performance optical imaging components. The liquid-crystal microlens (LCMs) only by applying spatial electrical field to change optical performance, have demonstrated remarkable advantages comparing conventional lenses, and therefore show a widely application prospect. Because the physical properties of the spatial electric fields between electrode plates in LCMs are directly related to the light-field performances of LCMs, the quality of voltage signal applied to LCMs needs high requirements. In this paper, we design and achieve a new type of digital voltage equipment with a wide adjustable voltage range and high precise voltage to effectively drive and adjust LCMs. More importantly, the device primarily based on field-programmable gate array(FPGA) can generate flexible and stable voltage signals to cooperate with the various functions of LCMs. Our experiments show that through the electronic control system, the LCMs already realize several significant functions including: electrically swing focus, wavefront imaging, electrically tunable spectral imaging and light-field imaging.

Assessment of a New High-Performance Small-Animal X-Ray Tomograph

NASA Astrophysics Data System (ADS)

Vaquero, J. J.; Redondo, S.; Lage, E.; Abella, M.; Sisniega, A.; Tapias, G.; Montenegro, M. L. Soto; Desco, M.

2008-06-01

We have developed a new X-ray cone-beam tomograph for in vivo small-animal imaging using a flat panel detector (CMOS technology with a microcolumnar CsI scintillator plate) and a microfocus X-ray source. The geometrical configuration was designed to achieve a spatial resolution of about 12 lpmm with a field of view appropriate for laboratory rodents. In order to achieve high performance with regard to per-animal screening time and cost, the acquisition software takes advantage of the highest frame rate of the detector and performs on-the-fly corrections on the detector raw data. These corrections include geometrical misalignments, sensor non-uniformities, and defective elements. The resulting image is then converted to attenuation values. We measured detector modulation transfer function (MTF), detector stability, system resolution, quality of the reconstructed tomographic images and radiated dose. The system resolution was measured following the standard test method ASTM E 1695 -95. For image quality evaluation, we assessed signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as a function of the radiated dose. Dose studies for different imaging protocols were performed by introducing TLD dosimeters in representative organs of euthanized laboratory rats. Noise figure, measured as standard deviation, was 50 HU for a dose of 10 cGy. Effective dose with standard research protocols is below 200 mGy, confirming that the system is appropriate for in vivo imaging. Maximum spatial resolution achieved was better than 50 micron. Our experimental results obtained with image quality phantoms as well as with in-vivo studies show that the proposed configuration based on a CMOS flat panel detector and a small micro-focus X-ray tube leads to a compact design that provides good image quality and low radiated dose, and it could be used as an add-on for existing PET or SPECT scanners.

The analysis on the relation between the compression method and the performance enhancement of MSC (Multi-Spectral Camera) image data

NASA Astrophysics Data System (ADS)

Yong, Sang-Soon; Ra, Sung-Woong

2007-10-01

Multi-Spectral Camera(MSC) is a main payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The MSC instrument has one(1) channel for panchromatic imaging and four(4) channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI CCD Focal Plane Array (FPA). The instrument images the earth using a push-broom motion with a swath width of 15 km and a ground sample distance (GSD) of 1 m over the entire field of view (FOV) at altitude 685 Km. The instrument is designed to have an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/ offset and on-board image data compression/ storage. The compression method on KOMPSAT-2 MSC was selected and used to match EOS input rate and PDTS output data rate on MSC image data chain. At once the MSC performance was carefully handled to minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP and Cal./Val.(Calibration and Validation) phase. In this paper, on-orbit image data chain in MSC and image data processing on KGS including general MSC description is briefly described. The influences on image performance between on-board compression algorithms and between performance restoration methods in ground station are analyzed, and the relation between both methods is to be analyzed and discussed.

Retinal Image Quality During Accommodation

PubMed Central

López-Gil, N.; Martin, J.; Liu, T.; Bradley, A.; Díaz-Muñoz, D.; Thibos, L.

2013-01-01

Purpose We asked if retinal image quality is maximum during accommodation, or sub-optimal due to accommodative error, when subjects perform an acuity task. Methods Subjects viewed a monochromatic (552nm), high-contrast letter target placed at various viewing distances. Wavefront aberrations of the accommodating eye were measured near the endpoint of an acuity staircase paradigm. Refractive state, defined as the optimum target vergence for maximising retinal image quality, was computed by through-focus wavefront analysis to find the power of the virtual correcting lens that maximizes visual Strehl ratio. Results Despite changes in ocular aberrations and pupil size during binocular viewing, retinal image quality and visual acuity typically remain high for all target vergences. When accommodative errors lead to sub-optimal retinal image quality, acuity and measured image quality both decline. However, the effect of accommodation errors of on visual acuity are mitigated by pupillary constriction associated with accommodation and binocular convergence and also to binocular summation of dissimilar retinal image blur. Under monocular viewing conditions some subjects displayed significant accommodative lag that reduced visual performance, an effect that was exacerbated by pharmacological dilation of the pupil. Conclusions Spurious measurement of accommodative error can be avoided when the image quality metric used to determine refractive state is compatible with the focusing criteria used by the visual system to control accommodation. Real focusing errors of the accommodating eye do not necessarily produce a reliably measurable loss of image quality or clinically significant loss of visual performance, probably because of increased depth-of-focus due to pupil constriction. When retinal image quality is close to maximum achievable (given the eye’s higher-order aberrations), acuity is also near maximum. A combination of accommodative lag, reduced image quality, and reduced visual function may be a useful sign for diagnosing functionally-significant accommodative errors indicating the need for therapeutic intervention. PMID:23786386

Retinal image quality during accommodation.

PubMed

López-Gil, Norberto; Martin, Jesson; Liu, Tao; Bradley, Arthur; Díaz-Muñoz, David; Thibos, Larry N

2013-07-01

We asked if retinal image quality is maximum during accommodation, or sub-optimal due to accommodative error, when subjects perform an acuity task. Subjects viewed a monochromatic (552 nm), high-contrast letter target placed at various viewing distances. Wavefront aberrations of the accommodating eye were measured near the endpoint of an acuity staircase paradigm. Refractive state, defined as the optimum target vergence for maximising retinal image quality, was computed by through-focus wavefront analysis to find the power of the virtual correcting lens that maximizes visual Strehl ratio. Despite changes in ocular aberrations and pupil size during binocular viewing, retinal image quality and visual acuity typically remain high for all target vergences. When accommodative errors lead to sub-optimal retinal image quality, acuity and measured image quality both decline. However, the effect of accommodation errors of on visual acuity are mitigated by pupillary constriction associated with accommodation and binocular convergence and also to binocular summation of dissimilar retinal image blur. Under monocular viewing conditions some subjects displayed significant accommodative lag that reduced visual performance, an effect that was exacerbated by pharmacological dilation of the pupil. Spurious measurement of accommodative error can be avoided when the image quality metric used to determine refractive state is compatible with the focusing criteria used by the visual system to control accommodation. Real focusing errors of the accommodating eye do not necessarily produce a reliably measurable loss of image quality or clinically significant loss of visual performance, probably because of increased depth-of-focus due to pupil constriction. When retinal image quality is close to maximum achievable (given the eye's higher-order aberrations), acuity is also near maximum. A combination of accommodative lag, reduced image quality, and reduced visual function may be a useful sign for diagnosing functionally-significant accommodative errors indicating the need for therapeutic intervention. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

Motion-Blurred Particle Image Restoration for On-Line Wear Monitoring

PubMed Central

Peng, Yeping; Wu, Tonghai; Wang, Shuo; Kwok, Ngaiming; Peng, Zhongxiao

2015-01-01

On-line images of wear debris contain important information for real-time condition monitoring, and a dynamic imaging technique can eliminate particle overlaps commonly found in static images, for instance, acquired using ferrography. However, dynamic wear debris images captured in a running machine are unavoidably blurred because the particles in lubricant are in motion. Hence, it is difficult to acquire reliable images of wear debris with an adequate resolution for particle feature extraction. In order to obtain sharp wear particle images, an image processing approach is proposed. Blurred particles were firstly separated from the static background by utilizing a background subtraction method. Second, the point spread function was estimated using power cepstrum to determine the blur direction and length. Then, the Wiener filter algorithm was adopted to perform image restoration to improve the image quality. Finally, experiments were conducted with a large number of dynamic particle images to validate the effectiveness of the proposed method and the performance of the approach was also evaluated. This study provides a new practical approach to acquire clear images for on-line wear monitoring. PMID:25856328

Photothermal quantitative phase imaging of living cells with nanoparticles utilizing a cost-efficient setup

NASA Astrophysics Data System (ADS)

Turko, Nir A.; Isbach, Michael; Ketelhut, Steffi; Greve, Burkhard; Schnekenburger, Jürgen; Shaked, Natan T.; Kemper, Björn

2017-02-01

We explored photothermal quantitative phase imaging (PTQPI) of living cells with functionalized nanoparticles (NPs) utilizing a cost-efficient setup based on a cell culture microscope. The excitation light was modulated by a mechanical chopper wheel with low frequencies. Quantitative phase imaging (QPI) was performed with Michelson interferometer-based off-axis digital holographic microscopy and a standard industrial camera. We present results from PTQPI observations on breast cancer cells that were incubated with functionalized gold NPs binding to the epidermal growth factor receptor. Moreover, QPI was used to quantify the impact of the NPs and the low frequency light excitation on cell morphology and viability.

Characterisation of a resolution enhancing image inversion interferometer.

PubMed

Wicker, Kai; Sindbert, Simon; Heintzmann, Rainer

2009-08-31

Image inversion interferometers have the potential to significantly enhance the lateral resolution and light efficiency of scanning fluorescence microscopes. Self-interference of a point source's coherent point spread function with its inverted copy leads to a reduction in the integrated signal for off-axis sources compared to sources on the inversion axis. This can be used to enhance the resolution in a confocal laser scanning microscope. We present a simple image inversion interferometer relying solely on reflections off planar surfaces. Measurements of the detection point spread function for several types of light sources confirm the predicted performance and suggest its usability for scanning confocal fluorescence microscopy.

Compressive Sensing via Nonlocal Smoothed Rank Function

PubMed Central

Fan, Ya-Ru; Liu, Jun; Zhao, Xi-Le

2016-01-01

Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction. PMID:27583683

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

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

Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivativesmore » of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.« less

Spatial-scanning hyperspectral imaging probe for bio-imaging applications

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2016-03-01

The three common methods to perform hyperspectral imaging are the spatial-scanning, spectral-scanning, and snapshot methods. However, only the spectral-scanning and snapshot methods have been configured to a hyperspectral imaging probe as of today. This paper presents a spatial-scanning (pushbroom) hyperspectral imaging probe, which is realized by integrating a pushbroom hyperspectral imager with an imaging probe. The proposed hyperspectral imaging probe can also function as an endoscopic probe by integrating a custom fabricated image fiber bundle unit. The imaging probe is configured by incorporating a gradient-index lens at the end face of an image fiber bundle that consists of about 50 000 individual fiberlets. The necessary simulations, methodology, and detailed instrumentation aspects that are carried out are explained followed by assessing the developed probe's performance. Resolution test targets such as United States Air Force chart as well as bio-samples such as chicken breast tissue with blood clot are used as test samples for resolution analysis and for performance validation. This system is built on a pushbroom hyperspectral imaging system with a video camera and has the advantage of acquiring information from a large number of spectral bands with selectable region of interest. The advantages of this spatial-scanning hyperspectral imaging probe can be extended to test samples or tissues residing in regions that are difficult to access with potential diagnostic bio-imaging applications.

Advanced Mail Systems Scanner Technology. Executive Summary and Appendixes A-E.

DTIC Science & Technology

1980-10-01

data base. 6. Perform color acquisition studies. 7. Investigate address and bar code reading. MASS MEMORY TECHNOLOGY 1. Collect performance data on...area of the 1728-by-2200 ICAS image memory and to transmit the data to any of the three color memories of the Comtal. Function table information can...for printing color images. The software allows the transmission of data from the ICAS frame-store memory via the MCU to the Dicomed. Software test

Towards A Complete Model Of Photopic Visual Threshold Performance

NASA Astrophysics Data System (ADS)

Overington, I.

1982-02-01

Based on a wide variety of fragmentary evidence taken from psycho-physics, neurophysiology and electron microscopy, it has been possible to put together a very widely applicable conceptual model of photopic visual threshold performance. Such a model is so complex that a single comprehensive mathematical version is excessively cumbersome. It is, however, possible to set up a suite of related mathematical models, each of limited application but strictly known envelope of usage. Such models may be used for assessment of a variety of facets of visual performance when using display imagery, including effects and interactions of image quality, random and discrete display noise, viewing distance, image motion, etc., both for foveal interrogation tasks and for visual search tasks. The specific model may be selected from the suite according to the assessment task in hand. The paper discusses in some depth the major facets of preperceptual visual processing and their interaction with instrumental image quality and noise. It then highlights the statistical nature of visual performance before going on to consider a number of specific mathematical models of partial visual function. Where appropriate, these are compared with widely popular empirical models of visual function.

Grating scattering BRDF and imaging performances: A test survey performed in the frame of the flex mission

NASA Astrophysics Data System (ADS)

Harnisch, Bernd; Deep, Atul; Vink, Ramon; Coatantiec, Claude

2017-11-01

Key components in optical spectrometers are the gratings. Their influence on the overall infield straylight of the spectrometer depends not only on the technology used for grating fabrication but also on the potential existence of ghost images caused by irregularities of the grating constant. For the straylight analysis of spectrometer no general Bidirectional Reflectance Distribution Function (BRDF) model of gratings exist, as it does for optically smooth surfaces. These models are needed for the determination of spectrometer straylight background and for the calculation of spectrometer out of band rejection performances. Within the frame of the Fluorescence Earth Explorer mission (FLEX), gratings manufactured using different technologies have been investigated in terms of straylight background and imaging performance in the used diffraction order. The gratings which have been investigated cover a lithographically written grating, a volume Bragg grating, two holographic gratings and an off-the-shelf ruled grating. In this paper we present a survey of the measured bidirectional reflectance/transmittance distribution function and the determination of an equivalent surface micro-roughness of the gratings, describing the scattering of the grating around the diffraction order. This is specifically needed for the straylight modeling of the spectrometer.

Attention bias in older women with remitted depression is associated with enhanced amygdala activity and functional connectivity.

PubMed

Albert, Kimberly; Gau, Violet; Taylor, Warren D; Newhouse, Paul A

2017-03-01

Cognitive bias is a common characteristic of major depressive disorder (MDD) and is posited to remain during remission and contribute to recurrence risk. Attention bias may be related to enhanced amygdala activity or altered amygdala functional connectivity in depression. The current study examined attention bias, brain activity for emotional images, and functional connectivity in post-menopausal women with and without a history of major depression. Attention bias for emotionally valenced images was examined in 33 postmenopausal women with (n=12) and without (n=21) a history of major depression using an emotion dot probe task during fMRI. Group differences in amygdala activity and functional connectivity were assessed using fMRI and examined for correlations to attention performance. Women with a history of MDD showed greater attentional bias for negative images and greater activity in brain areas including the amygdala for both positive and negative images (pcorr <0.001) than women without a history of MDD. In all participants, amygdala activity for negative images was correlated with attention facilitation for emotional images. Women with a history of MDD had significantly greater functional connectivity between the amygdala and hippocampal complex. In all participants amygdala-hippocampal connectivity was positively correlated with attention facilitation for negative images. Small sample with unbalanced groups. These findings provide evidence for negative attentional bias in euthymic, remitted depressed individuals. Activity and functional connectivity in limbic and attention networks may provide a neurobiological basis for continued cognitive bias in remitted depression. Copyright © 2016 Elsevier B.V. All rights reserved.

CMOS image sensor with organic photoconductive layer having narrow absorption band and proposal of stack type solid-state image sensors

NASA Astrophysics Data System (ADS)

Takada, Shunji; Ihama, Mikio; Inuiya, Masafumi

2006-02-01

Digital still cameras overtook film cameras in Japanese market in 2000 in terms of sales volume owing to their versatile functions. However, the image-capturing capabilities such as sensitivity and latitude of color films are still superior to those of digital image sensors. In this paper, we attribute the cause for the high performance of color films to their multi-layered structure, and propose the solid-state image sensors with stacked organic photoconductive layers having narrow absorption bands on CMOS read-out circuits.

MEMS scanning micromirror for optical coherence tomography.

PubMed

Strathman, Matthew; Liu, Yunbo; Keeler, Ethan G; Song, Mingli; Baran, Utku; Xi, Jiefeng; Sun, Ming-Ting; Wang, Ruikang; Li, Xingde; Lin, Lih Y

2015-01-01

This paper describes an endoscopic-inspired imaging system employing a micro-electromechanical system (MEMS) micromirror scanner to achieve beam scanning for optical coherence tomography (OCT) imaging. Miniaturization of a scanning mirror using MEMS technology can allow a fully functional imaging probe to be contained in a package sufficiently small for utilization in a working channel of a standard gastroesophageal endoscope. This work employs advanced image processing techniques to enhance the images acquired using the MEMS scanner to correct non-idealities in mirror performance. The experimental results demonstrate the effectiveness of the proposed technique.

MEMS scanning micromirror for optical coherence tomography

PubMed Central

Strathman, Matthew; Liu, Yunbo; Keeler, Ethan G.; Song, Mingli; Baran, Utku; Xi, Jiefeng; Sun, Ming-Ting; Wang, Ruikang; Li, Xingde; Lin, Lih Y.

2014-01-01

This paper describes an endoscopic-inspired imaging system employing a micro-electromechanical system (MEMS) micromirror scanner to achieve beam scanning for optical coherence tomography (OCT) imaging. Miniaturization of a scanning mirror using MEMS technology can allow a fully functional imaging probe to be contained in a package sufficiently small for utilization in a working channel of a standard gastroesophageal endoscope. This work employs advanced image processing techniques to enhance the images acquired using the MEMS scanner to correct non-idealities in mirror performance. The experimental results demonstrate the effectiveness of the proposed technique. PMID:25657887

Navigation for the new millennium: Autonomous navigation for Deep Space 1

NASA Technical Reports Server (NTRS)

Reidel, J. E.; Bhaskaran, S.; Synnott, S. P.; Desai, S. D.; Bollman, W. E.; Dumont, P. J.; Halsell, C. A.; Han, D.; Kennedy, B. M.; Null, G. W.;

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Investigating the performance of reconstruction methods used in structured illumination microscopy as a function of the illumination pattern's modulation frequency

NASA Astrophysics Data System (ADS)

Shabani, H.; Sánchez-Ortiga, E.; Preza, C.

2016-03-01

Surpassing the resolution of optical microscopy defined by the Abbe diffraction limit, while simultaneously achieving optical sectioning, is a challenging problem particularly for live cell imaging of thick samples. Among a few developing techniques, structured illumination microscopy (SIM) addresses this challenge by imposing higher frequency information into the observable frequency band confined by the optical transfer function (OTF) of a conventional microscope either doubling the spatial resolution or filling the missing cone based on the spatial frequency of the pattern when the patterned illumination is two-dimensional. Standard reconstruction methods for SIM decompose the low and high frequency components from the recorded low-resolution images and then combine them to reach a high-resolution image. In contrast, model-based approaches rely on iterative optimization approaches to minimize the error between estimated and forward images. In this paper, we study the performance of both groups of methods by simulating fluorescence microscopy images from different type of objects (ranging from simulated two-point sources to extended objects). These simulations are used to investigate the methods' effectiveness on restoring objects with various types of power spectrum when modulation frequency of the patterned illumination is changing from zero to the incoherent cut-off frequency of the imaging system. Our results show that increasing the amount of imposed information by using a higher modulation frequency of the illumination pattern does not always yield a better restoration performance, which was found to be depended on the underlying object. Results from model-based restoration show performance improvement, quantified by an up to 62% drop in the mean square error compared to standard reconstruction, with increasing modulation frequency. However, we found cases for which results obtained with standard reconstruction methods do not always follow the same trend.

Enhanced spectral domain optical coherence tomography for pathological and functional studies

NASA Astrophysics Data System (ADS)

Yuan, Zhijia

Optical coherence tomography (OCT) is a novel technique that enables noninvasive or minimally invasive, cross-sectional imaging of biological tissue at sub-10mum spatial resolution and up to 2-3mm imaging depth. Numerous technological advances have emerged in recent years that have shown great potential to develop OCT into a powerful imaging and diagnostic tools. In particular, the implementation of Fourier-domain OCT (FDOCT) is a major step forward that leads to greatly improved imaging rate and image fidelity of OCT. This dissertation summarizes the work that focuses on enhancing the performances and functionalities of spectral radar based FDOCT (SDOCT) for pathological and functional applications. More specifically, chapters 1-4 emphasize on the development of SDOCT and its utility in pathological studies, including cancer diagnosis. The principle of SDOCT is first briefly outlined, followed by the design of our bench-top SDOCT systems with emphasis on spectral linear interpolation, calibration and system dispersion compensation. For ultrahigh-resolution SDOCT, time-lapse image registration and frame averaging is introduced to effectively reduce speckle noise and uncover subcellular details, showing great promise for enhancing the diagnosis of carcinoma in situ. To overcome the image depth limitation of OCT, a dual-modal imaging method combing SDOCT with high-frequency ultrasound is proposed and examined in animal cancer models to enhance the sensitivity and staging capabilities for bladder cancer diagnosis. Chapters 5-7 summarize the work on developing Doppler SDOCT for functional studies. Digital-frequency-ramping OCT (DFR-OCT) is developed in the study, which has demonstrated the ability to significantly improve the signal-to-noise ratio and thus sensitivity for retrieving subsurface blood flow imaging. New DFR algorithms and imaging processing methods are discussed to further enhance cortical CBF imaging. Applications of DFR-OCT for brain functional studies are presented and laser speckle imaging is combined to enable quantitative cerebral blood flow (CBF) imaging at high spatiotemporal resolutions. An angiography-enhanced Doppler optical coherence tomography (aDFR-OCT) was also demonstrated to enable quantitative imaging of capillary changes for brain functional studies. Lastly, future work on technological development and potential biomedical applications is briefly outlined.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Development and Characterization of a High-Energy Neutron Time-of-Flight Imaging System

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

Madden, Amanda Christine; Schirato, Richard C.; Swift, Alicia L.

We present that Los Alamos National Laboratory has developed a prototype of a high-energy neutron time-of-flight imaging system for the non-destructive evaluation of dense, massive, and/or high atomic number objects. High-energy neutrons provide the penetrating power, and thus the high dynamic range necessary to image internal features and defects of such objects. The addition of the time gating capability allows for scatter rejection when paired with a pulsed monoenergetic beam, or neutron energy selection when paired with a pulsed broad-spectrum neutron source. The Time Gating to Reject Scatter and Select Energy (TiGReSSE) system was tested at the Los Alamos Neutronmore » Science Center’s (LANSCE) Weapons Nuclear Research (WNR) facility, a spallation neutron source, to provide proof of concept measurements and to characterize the instrument response. This paper will show results of several objects imaged during this run cycle. In addition, results from system performance metrics such as the Modulation Transfer Function and the Detective Quantum Efficiency measured as a function of neutron energy, characterize the current system performance and inform the next generation of neutron imaging instrument.« less

Development and Characterization of a High-Energy Neutron Time-of-Flight Imaging System

DOE PAGES

Madden, Amanda Christine; Schirato, Richard C.; Swift, Alicia L.; ...

2017-02-09

We present that Los Alamos National Laboratory has developed a prototype of a high-energy neutron time-of-flight imaging system for the non-destructive evaluation of dense, massive, and/or high atomic number objects. High-energy neutrons provide the penetrating power, and thus the high dynamic range necessary to image internal features and defects of such objects. The addition of the time gating capability allows for scatter rejection when paired with a pulsed monoenergetic beam, or neutron energy selection when paired with a pulsed broad-spectrum neutron source. The Time Gating to Reject Scatter and Select Energy (TiGReSSE) system was tested at the Los Alamos Neutronmore » Science Center’s (LANSCE) Weapons Nuclear Research (WNR) facility, a spallation neutron source, to provide proof of concept measurements and to characterize the instrument response. This paper will show results of several objects imaged during this run cycle. In addition, results from system performance metrics such as the Modulation Transfer Function and the Detective Quantum Efficiency measured as a function of neutron energy, characterize the current system performance and inform the next generation of neutron imaging instrument.« less

An integrative approach for analyzing hundreds of neurons in task performing mice using wide-field calcium imaging.

PubMed

Mohammed, Ali I; Gritton, Howard J; Tseng, Hua-an; Bucklin, Mark E; Yao, Zhaojie; Han, Xue

2016-02-08

Advances in neurotechnology have been integral to the investigation of neural circuit function in systems neuroscience. Recent improvements in high performance fluorescent sensors and scientific CMOS cameras enables optical imaging of neural networks at a much larger scale. While exciting technical advances demonstrate the potential of this technique, further improvement in data acquisition and analysis, especially those that allow effective processing of increasingly larger datasets, would greatly promote the application of optical imaging in systems neuroscience. Here we demonstrate the ability of wide-field imaging to capture the concurrent dynamic activity from hundreds to thousands of neurons over millimeters of brain tissue in behaving mice. This system allows the visualization of morphological details at a higher spatial resolution than has been previously achieved using similar functional imaging modalities. To analyze the expansive data sets, we developed software to facilitate rapid downstream data processing. Using this system, we show that a large fraction of anatomically distinct hippocampal neurons respond to discrete environmental stimuli associated with classical conditioning, and that the observed temporal dynamics of transient calcium signals are sufficient for exploring certain spatiotemporal features of large neural networks.

Image correlation based method for the analysis of collagen fibers patterns

NASA Astrophysics Data System (ADS)

Rosa, Ramon G. T.; Pratavieira, Sebastião.; Kurachi, Cristina

2015-06-01

The collagen fibers are one of the most important structural proteins in skin, being responsible for its strength and flexibility. It is known that their properties, like fibers density, ordination and mean diameter can be affected by several skin conditions, what makes these properties a good parameter to be used on the diagnosis and evaluation of skin aging, cancer, healing, among other conditions. There is, however, a need for methods capable of analyzing quantitatively the organization patterns of these fibers. To address this need, we developed a method based on the autocorrelation function of the images that allows the construction of vector field plots of the fibers directions and does not require any kind of curve fitting or optimization. The analyzed images were obtained through Second Harmonic Generation Imaging Microscopy. This paper presents a concise review on the autocorrelation function and some of its applications to image processing, details the developed method and the results obtained through the analysis of hystopathological slides of landrace porcine skin. The method has high accuracy on the determination of the fibers direction and presents high performance. We look forward to perform further studies keeping track of different skin conditions over time.

Microenvironments and Signaling Pathways Regulating Early Dissemination, Dormancy, and Metastasis

DTIC Science & Technology

2016-09-01

all these cell types in all tissues and we have used intravital imaging to document intravasation in early cancer lesions (see also partnering PI...report we showed how we optimized a mammary gland imaging window to perform intravital imaging and detect P-TMEM function during early stages of...MECs) assemble primary Tumor Microenvironment of Metastasis structures (P-TMEM) during early dissemination. SA1.1. Objective: Use intravital

Adaptive optical fluorescence microscopy.

PubMed

Ji, Na

2017-03-31

The past quarter century has witnessed rapid developments of fluorescence microscopy techniques that enable structural and functional imaging of biological specimens at unprecedented depth and resolution. The performance of these methods in multicellular organisms, however, is degraded by sample-induced optical aberrations. Here I review recent work on incorporating adaptive optics, a technology originally applied in astronomical telescopes to combat atmospheric aberrations, to improve image quality of fluorescence microscopy for biological imaging.

Multispectral, Fluorescent and Photoplethysmographic Imaging for Remote Skin Assessment

PubMed Central

Spigulis, Janis

2017-01-01

Optical tissue imaging has several advantages over the routine clinical imaging methods, including non-invasiveness (it does not change the structure of tissues), remote operation (it avoids infections) and the ability to quantify the tissue condition by means of specific image parameters. Dermatologists and other skin experts need compact (preferably pocket-size), self-sustaining and easy-to-use imaging devices. The operational principles and designs of ten portable in-vivo skin imaging prototypes developed at the Biophotonics Laboratory of Institute of Atomic Physics and Spectroscopy, University of Latvia during the recent five years are presented in this paper. Four groups of imaging devices are considered. Multi-spectral imagers offer possibilities for distant mapping of specific skin parameters, thus facilitating better diagnostics of skin malformations. Autofluorescence intensity and photobleaching rate imagers show a promising potential for skin tumor identification and margin delineation. Photoplethysmography video-imagers ensure remote detection of cutaneous blood pulsations and can provide real-time information on cardiovascular parameters and anesthesia efficiency. Multimodal skin imagers perform several of the abovementioned functions by taking a number of spectral and video images with the same image sensor. Design details of the developed prototypes and results of clinical tests illustrating their functionality are presented and discussed. PMID:28534815

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Integrated software environment based on COMKAT for analyzing tracer pharmacokinetics with molecular imaging.

PubMed

Fang, Yu-Hua Dean; Asthana, Pravesh; Salinas, Cristian; Huang, Hsuan-Ming; Muzic, Raymond F

2010-01-01

An integrated software package, Compartment Model Kinetic Analysis Tool (COMKAT), is presented in this report. COMKAT is an open-source software package with many functions for incorporating pharmacokinetic analysis in molecular imaging research and has both command-line and graphical user interfaces. With COMKAT, users may load and display images, draw regions of interest, load input functions, select kinetic models from a predefined list, or create a novel model and perform parameter estimation, all without having to write any computer code. For image analysis, COMKAT image tool supports multiple image file formats, including the Digital Imaging and Communications in Medicine (DICOM) standard. Image contrast, zoom, reslicing, display color table, and frame summation can be adjusted in COMKAT image tool. It also displays and automatically registers images from 2 modalities. Parametric imaging capability is provided and can be combined with the distributed computing support to enhance computation speeds. For users without MATLAB licenses, a compiled, executable version of COMKAT is available, although it currently has only a subset of the full COMKAT capability. Both the compiled and the noncompiled versions of COMKAT are free for academic research use. Extensive documentation, examples, and COMKAT itself are available on its wiki-based Web site, http://comkat.case.edu. Users are encouraged to contribute, sharing their experience, examples, and extensions of COMKAT. With integrated functionality specifically designed for imaging and kinetic modeling analysis, COMKAT can be used as a software environment for molecular imaging and pharmacokinetic analysis.

Cardiovascular imaging environment: will the future be cloud-based?

PubMed

Kawel-Boehm, Nadine; Bluemke, David A

2017-07-01

In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

A methodology for image quality evaluation of advanced CT systems.

PubMed

Wilson, Joshua M; Christianson, Olav I; Richard, Samuel; Samei, Ehsan

2013-03-01

This work involved the development of a phantom-based method to quantify the performance of tube current modulation and iterative reconstruction in modern computed tomography (CT) systems. The quantification included resolution, HU accuracy, noise, and noise texture accounting for the impact of contrast, prescribed dose, reconstruction algorithm, and body size. A 42-cm-long, 22.5-kg polyethylene phantom was designed to model four body sizes. Each size was represented by a uniform section, for the measurement of the noise-power spectrum (NPS), and a feature section containing various rods, for the measurement of HU and the task-based modulation transfer function (TTF). The phantom was scanned on a clinical CT system (GE, 750HD) using a range of tube current modulation settings (NI levels) and reconstruction methods (FBP and ASIR30). An image quality analysis program was developed to process the phantom data to calculate the targeted image quality metrics as a function of contrast, prescribed dose, and body size. The phantom fabrication closely followed the design specifications. In terms of tube current modulation, the tube current and resulting image noise varied as a function of phantom size as expected based on the manufacturer specification: From the 16- to 37-cm section, the HU contrast for each rod was inversely related to phantom size, and noise was relatively constant (<5% change). With iterative reconstruction, the TTF exhibited a contrast dependency with better performance for higher contrast objects. At low noise levels, TTFs of iterative reconstruction were better than those of FBP, but at higher noise, that superiority was not maintained at all contrast levels. Relative to FBP, the NPS of iterative reconstruction exhibited an ~30% decrease in magnitude and a 0.1 mm(-1) shift in the peak frequency. Phantom and image quality analysis software were created for assessing CT image quality over a range of contrasts, doses, and body sizes. The testing platform enabled robust NPS, TTF, HU, and pixel noise measurements as a function of body size capable of characterizing the performance of reconstruction algorithms and tube current modulation techniques.

A Class of Manifold Regularized Multiplicative Update Algorithms for Image Clustering.

PubMed

Yang, Shangming; Yi, Zhang; He, Xiaofei; Li, Xuelong

2015-12-01

Multiplicative update algorithms are important tools for information retrieval, image processing, and pattern recognition. However, when the graph regularization is added to the cost function, different classes of sample data may be mapped to the same subspace, which leads to the increase of data clustering error rate. In this paper, an improved nonnegative matrix factorization (NMF) cost function is introduced. Based on the cost function, a class of novel graph regularized NMF algorithms is developed, which results in a class of extended multiplicative update algorithms with manifold structure regularization. Analysis shows that in the learning, the proposed algorithms can efficiently minimize the rank of the data representation matrix. Theoretical results presented in this paper are confirmed by simulations. For different initializations and data sets, variation curves of cost functions and decomposition data are presented to show the convergence features of the proposed update rules. Basis images, reconstructed images, and clustering results are utilized to present the efficiency of the new algorithms. Last, the clustering accuracies of different algorithms are also investigated, which shows that the proposed algorithms can achieve state-of-the-art performance in applications of image clustering.

Lower bound for LCD image quality

NASA Astrophysics Data System (ADS)

Olson, William P.; Balram, Nikhil

1996-03-01

The paper presents an objective lower bound for the discrimination of patterns and fine detail in images on a monochrome LCD. In applications such as medical imaging and military avionics the information of interest is often at the highest frequencies in the image. Since LCDs are sampled data systems, their output modulation is dependent on the phase between the input signal and the sampling points. This phase dependence becomes particularly significant at high spatial frequencies. In order to use an LCD for applications such as those mentioned above it is essential to have a lower (worst case) bound on the performance of the display. We address this problem by providing a mathematical model for the worst case output modulation of an LCD in response to a sine wave input. This function can be interpreted as a worst case modulation transfer function (MTF). The intersection of the worst case MTF with the contrast threshold function (CTF) of the human visual system defines the highest spatial frequency that will always be detectable. In addition to providing the worst case limiting resolution, this MTF is combined with the CTF to produce objective worst case image quality values using the modulation transfer function area (MTFA) metric.

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Implementation of total focusing method for phased array ultrasonic imaging on FPGA

NASA Astrophysics Data System (ADS)

Guo, JianQiang; Li, Xi; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

2015-02-01

This paper describes a multi-FPGA imaging system dedicated for the real-time imaging using the Total Focusing Method (TFM) and Full Matrix Capture (FMC). The system was entirely described using Verilog HDL language and implemented on Altera Stratix IV GX FPGA development board. The whole algorithm process is to: establish a coordinate system of image and divide it into grids; calculate the complete acoustic distance of array element between transmitting array element and receiving array element, and transform it into index value; then index the sound pressure values from ROM and superimpose sound pressure values to get pixel value of one focus point; and calculate the pixel values of all focus points to get the final imaging. The imaging result shows that this algorithm has high SNR of defect imaging. And FPGA with parallel processing capability can provide high speed performance, so this system can provide the imaging interface, with complete function and good performance.

Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury.

PubMed

Caeyenberghs, Karen; Leemans, Alexander; Heitger, Marcus H; Leunissen, Inge; Dhollander, Thijs; Sunaert, Stefan; Dupont, Patrick; Swinnen, Stephan P

2012-04-01

Patients with traumatic brain injury show clear impairments in behavioural flexibility and inhibition that often persist beyond the time of injury, affecting independent living and psychosocial functioning. Functional magnetic resonance imaging studies have shown that patients with traumatic brain injury typically show increased and more broadly dispersed frontal and parietal activity during performance of cognitive control tasks. We constructed binary and weighted functional networks and calculated their topological properties using a graph theoretical approach. Twenty-three adults with traumatic brain injury and 26 age-matched controls were instructed to switch between coordination modes while making spatially and temporally coupled circular motions with joysticks during event-related functional magnetic resonance imaging. Results demonstrated that switching performance was significantly lower in patients with traumatic brain injury compared with control subjects. Furthermore, although brain networks of both groups exhibited economical small-world topology, altered functional connectivity was demonstrated in patients with traumatic brain injury. In particular, compared with controls, patients with traumatic brain injury showed increased connectivity degree and strength, and higher values of local efficiency, suggesting adaptive mechanisms in this group. Finally, the degree of increased connectivity was significantly correlated with poorer switching task performance and more severe brain injury. We conclude that analysing the functional brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Two-photon imaging in living brain slices.

PubMed

Mainen, Z F; Maletic-Savatic, M; Shi, S H; Hayashi, Y; Malinow, R; Svoboda, K

1999-06-01

Two-photon excitation laser scanning microscopy (TPLSM) has become the tool of choice for high-resolution fluorescence imaging in intact neural tissues. Compared with other optical techniques, TPLSM allows high-resolution imaging and efficient detection of fluorescence signal with minimal photobleaching and phototoxicity. The advantages of TPLSM are especially pronounced in highly scattering environments such as the brain slice. Here we describe our approaches to imaging various aspects of synaptic function in living brain slices. To combine several imaging modes together with patch-clamp electrophysiological recordings we found it advantageous to custom-build an upright microscope. Our design goals were primarily experimental convenience and efficient collection of fluorescence. We describe our TPLSM imaging system and its performance in detail. We present dynamic measurements of neuronal morphology of neurons expressing green fluorescent protein (GFP) and GFP fusion proteins as well as functional imaging of calcium dynamics in individual dendritic spines. Although our microscope is a custom instrument, its key advantages can be easily implemented as a modification of commercial laser scanning microscopes. Copyright 1999 Academic Press.

Effects of ionizing radiation on charge-coupled imagers

NASA Technical Reports Server (NTRS)

Killiany, J. M.; Baker, W. D.; Saks, N. S.; Barbe, D. F.

1975-01-01

The effects of ionizing radiation on three different charge coupled imagers have been investigated. Device performance was evaluated as a function of total gamma ray dose. The principal failure mechanisms have been identified for each particular device structure. The clock and bias voltages required for high total dose operation of the devices are presented.

Infrared scanning laser ophthalmoscope imaging of the macula and its correlation with functional loss and structural changes in patients with stargardt disease.

PubMed

Anastasakis, Anastasios; Fishman, Gerald A; Lindeman, Martin; Genead, Mohamed A; Zhou, Wensheng

2011-05-01

To correlate the degree of functional loss with structural changes in patients with Stargardt disease. Eighteen eyes of 10 patients with Stargardt disease were studied. Scanning laser ophthalmoscope infrared images were compared with corresponding spectral-domain optical coherence tomography scans. Additionally, scanning laser ophthalmoscope microperimetry was performed, and results were superimposed on scanning laser ophthalmoscope infrared images and in selected cases on fundus autofluorescence images. Seventeen of 18 eyes showed a distinct hyporeflective foveal and/or perifoveal area with distinct borders on scanning laser ophthalmoscope infrared images, which was less evident on funduscopy and incompletely depicted in fundus autofluorescence images. This hyporeflective zone corresponded to areas of significantly elevated psychophysical thresholds on microperimetry testing, in addition to thinning of the retinal pigment epithelium and disorganization or loss of the photoreceptor cell inner segment-outer segment junction and external-limiting membrane on spectral-domain optical coherence tomography. Scanning laser ophthalmoscope infrared fundus images are useful for depicting retinal structural changes in patients with Stargardt disease. A spectral-domain optical coherence tomography/scanning laser ophthalmoscope microperimetry device allows for a direct correlation of structural abnormalities with functional defects that will likely be applicable for the determination of retinal areas for potential improvement of retinal function in these patients during future clinical trials and for the monitoring of the diseases' natural history.

SLO-infrared imaging of the macula and its correlation with functional loss and structural changes in patients with Stargardt disease

PubMed Central

Anastasakis, Anastasios; Fishman, Gerald A; Lindeman, Martin; Genead, Mohamed A; Zhou, Wensheng

2010-01-01

Purpose To correlate the degree of functional loss with structural changes in patients with Stargardt disease. Methods Eighteen eyes of 10 Stargardt patients were studied. Scanning laser ophthalmoscope (SLO) infrared images were compared to corresponding spectral domain optical coherence tomography (SD-OCT) scans. Additionally, SLO microperimetry was performed and results were superimposed on SLO infrared images and in selected cases on fundus autofluorescence (FAF) images. Results Seventeen of 18 eyes showed a distinct hypo-reflective foveal and/or perifoveal area with distinct borders on SLO-infrared images which was less evident on funduscopy and incompletely depicted in FAF images. This hypo-reflective zone corresponded to areas of significantly elevated psychophysical thresholds on microperimetry testing, in addition to thinning of the retinal pigment epithelium (RPE), disorganization or loss of the photoreceptor cell inner-outer segment (IS-OS) junction and external limiting membrane (ELM) on SD-OCT. Conclusion SLO-infrared fundus images are useful for depicting retinal structural changes in Stargardt patients. An SD-OCT/SLO microperimetry device allows for a direct correlation of structural abnormalities with functional defects that will likely be applicable for the determination of retinal areas for potential improvement of retinal function in these patients during future clinical trials and for the monitoring of the diseases' natural history. PMID:21293320

Control Software for Advanced Video Guidance Sensor

NASA Technical Reports Server (NTRS)

Howard, Richard T.; Book, Michael L.; Bryan, Thomas C.

2006-01-01

Embedded software has been developed specifically for controlling an Advanced Video Guidance Sensor (AVGS). A Video Guidance Sensor is an optoelectronic system that provides guidance for automated docking of two vehicles. Such a system includes pulsed laser diodes and a video camera, the output of which is digitized. From the positions of digitized target images and known geometric relationships, the relative position and orientation of the vehicles are computed. The present software consists of two subprograms running in two processors that are parts of the AVGS. The subprogram in the first processor receives commands from an external source, checks the commands for correctness, performs commanded non-image-data-processing control functions, and sends image data processing parts of commands to the second processor. The subprogram in the second processor processes image data as commanded. Upon power-up, the software performs basic tests of functionality, then effects a transition to a standby mode. When a command is received, the software goes into one of several operational modes (e.g. acquisition or tracking). The software then returns, to the external source, the data appropriate to the command.

Characterization of adaptive statistical iterative reconstruction (ASIR) in low contrast helical abdominal imaging via a transfer function based method

NASA Astrophysics Data System (ADS)

Zhang, Da; Li, Xinhua; Liu, Bob

2012-03-01

Since the introduction of ASiR, its potential in noise reduction has been reported in various clinical applications. However, the influence of different scan and reconstruction parameters on the trade off between ASiR's blurring effect and noise reduction in low contrast imaging has not been fully studied. Simple measurements on low contrast images, such as CNR or phantom scores could not explore the nuance nature of this problem. We tackled this topic using a method which compares the performance of ASiR in low contrast helical imaging based on an assumed filter layer on top of the FBP reconstruction. Transfer functions of this filter layer were obtained from the noise power spectra (NPS) of corresponding FBP and ASiR images that share the same scan and reconstruction parameters. 2D transfer functions were calculated as sqrt[NPSASiR(u, v)/NPSFBP(u, v)]. Synthesized ACR phantom images were generated by filtering the FBP images with the transfer functions of specific (FBP, ASiR) pairs, and were compared with the ASiR images. It is shown that the transfer functions could predict the deterministic blurring effect of ASiR on low contrast objects, as well as the degree of noise reductions. Using this method, the influence of dose, scan field of view (SFOV), display field of view (DFOV), ASiR level, and Recon Mode on the behavior of ASiR in low contrast imaging was studied. It was found that ASiR level, dose level, and DFOV play more important roles in determining the behavior of ASiR than the other two parameters.

FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography.

PubMed

Ale, Angelique; Ermolayev, Vladimir; Herzog, Eva; Cohrs, Christian; de Angelis, Martin Hrabé; Ntziachristos, Vasilis

2012-06-01

The development of hybrid optical tomography methods to improve imaging performance has been suggested over a decade ago and has been experimentally demonstrated in animals and humans. Here we examined in vivo performance of a camera-based hybrid fluorescence molecular tomography (FMT) system for 360° imaging combined with X-ray computed tomography (XCT). Offering an accurately co-registered, information-rich hybrid data set, FMT-XCT has new imaging possibilities compared to stand-alone FMT and XCT. We applied FMT-XCT to a subcutaneous 4T1 tumor mouse model, an Aga2 osteogenesis imperfecta model and a Kras lung cancer mouse model, using XCT information during FMT inversion. We validated in vivo imaging results against post-mortem planar fluorescence images of cryoslices and histology data. Besides offering concurrent anatomical and functional information, FMT-XCT resulted in the most accurate FMT performance to date. These findings indicate that addition of FMT optics into the XCT gantry may be a potent upgrade for small-animal XCT systems.

Composite multi-lobe descriptor for cross spectral face recognition: matching active IR to visible light images

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.

2015-05-01

Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.

Matching rendered and real world images by digital image processing

NASA Astrophysics Data System (ADS)

Mitjà, Carles; Bover, Toni; Bigas, Miquel; Escofet, Jaume

2010-05-01

Recent advances in computer-generated images (CGI) have been used in commercial and industrial photography providing a broad scope in product advertising. Mixing real world images with those rendered from virtual space software shows a more or less visible mismatching between corresponding image quality performance. Rendered images are produced by software which quality performance is only limited by the resolution output. Real world images are taken with cameras with some amount of image degradation factors as lens residual aberrations, diffraction, sensor low pass anti aliasing filters, color pattern demosaicing, etc. The effect of all those image quality degradation factors can be characterized by the system Point Spread Function (PSF). Because the image is the convolution of the object by the system PSF, its characterization shows the amount of image degradation added to any taken picture. This work explores the use of image processing to degrade the rendered images following the parameters indicated by the real system PSF, attempting to match both virtual and real world image qualities. The system MTF is determined by the slanted edge method both in laboratory conditions and in the real picture environment in order to compare the influence of the working conditions on the device performance; an approximation to the system PSF is derived from the two measurements. The rendered images are filtered through a Gaussian filter obtained from the taking system PSF. Results with and without filtering are shown and compared measuring the contrast achieved in different final image regions.

Functional magnetic resonance imaging exploration of combined hand and speech movements in Parkinson's disease.

PubMed

Pinto, Serge; Mancini, Laura; Jahanshahi, Marjan; Thornton, John S; Tripoliti, Elina; Yousry, Tarek A; Limousin, Patricia

2011-10-01

Among the repertoire of motor functions, although hand movement and speech production tasks have been investigated widely by functional neuroimaging, paradigms combining both movements have been studied less so. Such paradigms are of particular interest in Parkinson's disease, in which patients have specific difficulties performing two movements simultaneously. In 9 unmedicated patients with Parkinson's disease and 15 healthy control subjects, externally cued tasks (i.e., hand movement, speech production, and combined hand movement and speech production) were performed twice in a random order and functional magnetic resonance imaging detected cerebral activations, compared to the rest. F-statistics tested within-group (significant activations at P values < 0.05, familywise error corrected), between-group, and between-task comparisons (regional activations significant at P values < 0.001, uncorrected, with cluster size > 10 voxels). For control subjects, the combined task activations comprised the sum of those obtained during hand movement and speech production performed separately, reflecting the neural correlates of performing movements sharing similar programming modalities. In patients with Parkinson's disease, only activations underlying hand movement were observed during the combined task. We interpreted this phenomenon as patients' potential inability to recruit facilitatory activations while performing two movements simultaneously. This lost capacity could be related to a functional prioritization of one movement (i.e., hand movement), in comparison with the other (i.e., speech production). Our observation could also reflect the inability of patients with Parkinson's disease to intrinsically engage the motor coordination necessary to perform a combined task. Copyright © 2011 Movement Disorder Society.

UWGSP4: an imaging and graphics superworkstation and its medical applications

NASA Astrophysics Data System (ADS)

Jong, Jing-Ming; Park, Hyun Wook; Eo, Kilsu; Kim, Min-Hwan; Zhang, Peng; Kim, Yongmin

1992-05-01

UWGSP4 is configured with a parallel architecture for image processing and a pipelined architecture for computer graphics. The system's peak performance is 1,280 MFLOPS for image processing and over 200,000 Gouraud shaded 3-D polygons per second for graphics. The simulated sustained performance is about 50% of the peak performance in general image processing. Most of the 2-D image processing functions are efficiently vectorized and parallelized in UWGSP4. A performance of 770 MFLOPS in convolution and 440 MFLOPS in FFT is achieved. The real-time cine display, up to 32 frames of 1280 X 1024 pixels per second, is supported. In 3-D imaging, the update rate for the surface rendering is 10 frames of 20,000 polygons per second; the update rate for the volume rendering is 6 frames of 128 X 128 X 128 voxels per second. The system provides 1280 X 1024 X 32-bit double frame buffers and one 1280 X 1024 X 8-bit overlay buffer for supporting realistic animation, 24-bit true color, and text annotation. A 1280 X 1024- pixel, 66-Hz noninterlaced display screen with 1:1 aspect ratio can be windowed into the frame buffer for the display of any portion of the processed image or graphics.

MTF evaluation of in-line phase contrast imaging system

NASA Astrophysics Data System (ADS)

Sun, Xiaoran; Gao, Feng; Zhao, Huijuan; Zhang, Limin; Li, Jiao; Zhou, Zhongxing

2017-02-01

X-ray phase contrast imaging (XPCI) is a novel method that exploits the phase shift for the incident X-ray to form an image. Various XPCI methods have been proposed, among which, in-line phase contrast imaging (IL-PCI) is regarded as one of the most promising clinical methods. The contrast of the interface is enhanced due to the introduction of the boundary fringes in XPCI, thus it is generally used to evaluate the image quality of XPCI. But the contrast is a comprehensive index and it does not reflect the information of image quality in the frequency range. The modulation transfer function (MTF), which is the Fourier transform of the system point spread function, is recognized as the metric to characterize the spatial response of conventional X-ray imaging system. In this work, MTF is introduced into the image quality evaluation of the IL-PCI system. Numerous simulations based on Fresnel - Kirchhoff diffraction theory are performed with varying system settings and the corresponding MTFs were calculated for comparison. The results show that MTF can provide more comprehensive information of image quality comparing to contrast in IL-PCI.

Cascaded systems analysis of photon counting detectors

PubMed Central

Xu, J.; Zbijewski, W.; Gang, G.; Stayman, J. W.; Taguchi, K.; Lundqvist, M.; Fredenberg, E.; Carrino, J. A.; Siewerdsen, J. H.

2014-01-01

Purpose: Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). Methods: A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1–7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored. Results: The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f50 (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons. Conclusions: The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems. PMID:25281959

Cascaded systems analysis of photon counting detectors.

PubMed

Xu, J; Zbijewski, W; Gang, G; Stayman, J W; Taguchi, K; Lundqvist, M; Fredenberg, E; Carrino, J A; Siewerdsen, J H

2014-10-01

Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1-7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored. The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f50 (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons. The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems.

Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice

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

Fei Baowei; Wang Hesheng; Muzic, Raymond F. Jr.

2006-03-15

We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET {sup 18}F-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration,more » we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5{+-}0.4 mm which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.« less

Research-grade CMOS image sensors for remote sensing applications

NASA Astrophysics Data System (ADS)

Saint-Pe, Olivier; Tulet, Michel; Davancens, Robert; Larnaudie, Franck; Magnan, Pierre; Martin-Gonthier, Philippe; Corbiere, Franck; Belliot, Pierre; Estribeau, Magali

2004-11-01

Imaging detectors are key elements for optical instruments and sensors on board space missions dedicated to Earth observation (high resolution imaging, atmosphere spectroscopy...), Solar System exploration (micro cameras, guidance for autonomous vehicle...) and Universe observation (space telescope focal planes, guiding sensors...). This market has been dominated by CCD technology for long. Since the mid-90s, CMOS Image Sensors (CIS) have been competing with CCDs for consumer domains (webcams, cell phones, digital cameras...). Featuring significant advantages over CCD sensors for space applications (lower power consumption, smaller system size, better radiations behaviour...), CMOS technology is also expanding in this field, justifying specific R&D and development programs funded by national and European space agencies (mainly CNES, DGA and ESA). All along the 90s and thanks to their increasingly improving performances, CIS have started to be successfully used for more and more demanding space applications, from vision and control functions requiring low-level performances to guidance applications requiring medium-level performances. Recent technology improvements have made possible the manufacturing of research-grade CIS that are able to compete with CCDs in the high-performances arena. After an introduction outlining the growing interest of optical instruments designers for CMOS image sensors, this paper will present the existing and foreseen ways to reach high-level electro-optics performances for CIS. The developments and performances of CIS prototypes built using an imaging CMOS process will be presented in the corresponding section.

Two Unipolar Terminal-Attractor-Based Associative Memories

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Wu, Chwan-Hwa

1995-01-01

Two unipolar mathematical models of electronic neural network functioning as terminal-attractor-based associative memory (TABAM) developed. Models comprise sets of equations describing interactions between time-varying inputs and outputs of neural-network memory, regarded as dynamical system. Simplifies design and operation of optoelectronic processor to implement TABAM performing associative recall of images. TABAM concept described in "Optoelectronic Terminal-Attractor-Based Associative Memory" (NPO-18790). Experimental optoelectronic apparatus that performed associative recall of binary images described in "Optoelectronic Inner-Product Neural Associative Memory" (NPO-18491).

Central Executive Dysfunction and Deferred Prefrontal Processing in Veterans with Gulf War Illness.

PubMed

Hubbard, Nicholas A; Hutchison, Joanna L; Motes, Michael A; Shokri-Kojori, Ehsan; Bennett, Ilana J; Brigante, Ryan M; Haley, Robert W; Rypma, Bart

2014-05-01

Gulf War Illness is associated with toxic exposure to cholinergic disruptive chemicals. The cholinergic system has been shown to mediate the central executive of working memory (WM). The current work proposes that impairment of the cholinergic system in Gulf War Illness patients (GWIPs) leads to behavioral and neural deficits of the central executive of WM. A large sample of GWIPs and matched controls (MCs) underwent functional magnetic resonance imaging during a varied-load working memory task. Compared to MCs, GWIPs showed a greater decline in performance as WM-demand increased. Functional imaging suggested that GWIPs evinced separate processing strategies, deferring prefrontal cortex activity from encoding to retrieval for high demand conditions. Greater activity during high-demand encoding predicted greater WM performance. Behavioral data suggest that WM executive strategies are impaired in GWIPs. Functional data further support this hypothesis and suggest that GWIPs utilize less effective strategies during high-demand WM.

Central Executive Dysfunction and Deferred Prefrontal Processing in Veterans with Gulf War Illness

PubMed Central

Hubbard, Nicholas A.; Hutchison, Joanna L.; Motes, Michael A.; Shokri-Kojori, Ehsan; Bennett, Ilana J.; Brigante, Ryan M.; Haley, Robert W.; Rypma, Bart

2015-01-01

Gulf War Illness is associated with toxic exposure to cholinergic disruptive chemicals. The cholinergic system has been shown to mediate the central executive of working memory (WM). The current work proposes that impairment of the cholinergic system in Gulf War Illness patients (GWIPs) leads to behavioral and neural deficits of the central executive of WM. A large sample of GWIPs and matched controls (MCs) underwent functional magnetic resonance imaging during a varied-load working memory task. Compared to MCs, GWIPs showed a greater decline in performance as WM-demand increased. Functional imaging suggested that GWIPs evinced separate processing strategies, deferring prefrontal cortex activity from encoding to retrieval for high demand conditions. Greater activity during high-demand encoding predicted greater WM performance. Behavioral data suggest that WM executive strategies are impaired in GWIPs. Functional data further support this hypothesis and suggest that GWIPs utilize less effective strategies during high-demand WM. PMID:25767746

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Extracting Intrinsic Functional Networks with Feature-Based Group Independent Component Analysis

ERIC Educational Resources Information Center

Calhoun, Vince D.; Allen, Elena

2013-01-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in…

RANKING TEM CAMERAS BY THEIR RESPONSE TO ELECTRON SHOT NOISE

PubMed Central

Grob, Patricia; Bean, Derek; Typke, Dieter; Li, Xueming; Nogales, Eva; Glaeser, Robert M.

2013-01-01

We demonstrate two ways in which the Fourier transforms of images that consist solely of randomly distributed electrons (shot noise) can be used to compare the relative performance of different electronic cameras. The principle is to determine how closely the Fourier transform of a given image does, or does not, approach that of an image produced by an ideal camera, i.e. one for which single-electron events are modeled as Kronecker delta functions located at the same pixels where the electrons were incident on the camera. Experimentally, the average width of the single-electron response is characterized by fitting a single Lorentzian function to the azimuthally averaged amplitude of the Fourier transform. The reciprocal of the spatial frequency at which the Lorentzian function falls to a value of 0.5 provides an estimate of the number of pixels at which the corresponding line-spread function falls to a value of 1/e. In addition, the excess noise due to stochastic variations in the magnitude of the response of the camera (for single-electron events) is characterized by the amount to which the appropriately normalized power spectrum does, or does not, exceed the total number of electrons in the image. These simple measurements provide an easy way to evaluate the relative performance of different cameras. To illustrate this point we present data for three different types of scintillator-coupled camera plus a silicon-pixel (direct detection) camera. PMID:23747527

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy.

PubMed

Tang, Jing; Kuwabara, Hiroto; Wong, Dean F; Rahmim, Arman

2010-08-07

We developed an anatomy-guided 4D closed-form algorithm to directly reconstruct parametric images from projection data for (nearly) irreversible tracers. Conventional methods consist of individually reconstructing 2D/3D PET data, followed by graphical analysis on the sequence of reconstructed image frames. The proposed direct reconstruction approach maintains the simplicity and accuracy of the expectation-maximization (EM) algorithm by extending the system matrix to include the relation between the parametric images and the measured data. A closed-form solution was achieved using a different hidden complete-data formulation within the EM framework. Furthermore, the proposed method was extended to maximum a posterior reconstruction via incorporation of MR image information, taking the joint entropy between MR and parametric PET features as the prior. Using realistic simulated noisy [(11)C]-naltrindole PET and MR brain images/data, the quantitative performance of the proposed methods was investigated. Significant improvements in terms of noise versus bias performance were demonstrated when performing direct parametric reconstruction, and additionally upon extending the algorithm to its Bayesian counterpart using the MR-PET joint entropy measure.

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention.

PubMed

Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L

2013-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. We have hypothesized that the changes in neural activity observed during increased cholinergic function reflect an increase in neural efficiency that leads to improved task performance. The current study tested this hypothesis by assessing neural efficiency based on cholinergically-mediated effects on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover fMRI study. Following an infusion of physostigmine (1 mg/h) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Physostigmine administration also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus processing regions support the hypothesis that cholinergic augmentation results in enhanced neural efficiency. This article is part of a Special Issue entitled 'Cognitive Enhancers'. Copyright © 2012 Elsevier Ltd. All rights reserved.

Physical evaluation of color and monochrome medical displays using an imaging colorimeter

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

2013-03-01

This paper presents an approach to physical evaluation of color and monochrome medical grade displays using an imaging colorimeter. The purpose of this study was to examine the influence of medical display types, monochrome or color at the same maximum luminance settings, on diagnostic performance. The focus was on the measurements of physical characteristics including spatial resolution and noise performance, which we believed could affect the clinical performance. Specifically, Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS) were evaluated and compared at different digital driving levels (DDL) between two EIZO displays.

Clinical experience with a high-performance ATM-connected DICOM archive for cardiology

NASA Astrophysics Data System (ADS)

Solomon, Harry P.

1997-05-01

A system to archive large image sets, such as cardiac cine runs, with near realtime response must address several functional and performance issues, including efficient use of a high performance network connection with standard protocols, an architecture which effectively integrates both short- and long-term mass storage devices, and a flexible data management policy which allows optimization of image distribution and retrieval strategies based on modality and site-specific operational use. Clinical experience with such as archive has allowed evaluation of these systems issues and refinement of a traffic model for cardiac angiography.

Prediction of Viking lander camera image quality

NASA Technical Reports Server (NTRS)

Huck, F. O.; Burcher, E. E.; Jobson, D. J.; Wall, S. D.

1976-01-01

Formulations are presented that permit prediction of image quality as a function of camera performance, surface radiance properties, and lighting and viewing geometry. Predictions made for a wide range of surface radiance properties reveal that image quality depends strongly on proper camera dynamic range command and on favorable lighting and viewing geometry. Proper camera dynamic range commands depend mostly on the surface albedo that will be encountered. Favorable lighting and viewing geometries depend mostly on lander orientation with respect to the diurnal sun path over the landing site, and tend to be independent of surface albedo and illumination scattering function. Side lighting with low sun elevation angles (10 to 30 deg) is generally favorable for imaging spatial details and slopes, whereas high sun elevation angles are favorable for measuring spectral reflectances.

Optical-to-optical interface device

NASA Technical Reports Server (NTRS)

Jacobson, A. D.; Bleha, W. P.; Miller, L.; Grinberg, J.; Fraas, L.; Margerum, D.

1975-01-01

An investigation was conducted to develop an optical-to-optical interface device capable of performing real-time incoherent-to-incoherent optical image conversion. The photoactivated liquid crystal light valve developed earlier represented a prototype liquid crystal light valve device capable of performing these functions. A device was developed which had high performance and extended lifetime.

High resolution multiplexed functional imaging in live embryos (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Fourier multiplexed fluorescence lifetime imaging (FmFLIM) scanning laser optical tomography (FmFLIM-SLOT) combines FmFLIM and Scanning laser optical tomography (SLOT) to perform multiplexed 3D FLIM imaging of live embryos. The system had demonstrate multiplexed functional imaging of zebrafish embryos genetically express Foster Resonant Energy Transfer (FRET) sensors. However, previous system has a 20 micron resolution because the focused Gaussian beam diverges quickly from the focused plane, makes it difficult to achieve high resolution imaging over a long projection depth. Here, we present a high-resolution FmFLIM-SLOT system with achromatic Bessel beam, which achieves 3 micron resolution in 3D deep tissue imaging. In Bessel-FmFLIM-SLOT, multiple laser excitation lines are firstly intensity modulated by a Michelson interferometer with a spinning polygon mirror optical delay line, which enables Fourier multiplexed multi-channel lifetime measurements. Then, a spatial light modulator and a prism are used to transform the modulated Gaussian laser beam to an achromatic Bessel beam. The achromatic Bessel beam scans across the whole specimen with equal angular intervals as sample rotated. After tomography reconstruction and the frequency domain lifetime analysis method, both the 3D intensity and lifetime image of multiple excitation-emission can be obtained. Using Bessel-FmFLIM-SLOT system, we performed cellular-resolution FLIM tomography imaging of live zebrafish embryo. Genetically expressed FRET sensors in these embryo will allow non-invasive observation of multiple biochemical processes in vivo.

Simulation approach for the evaluation of tracking accuracy in radiotherapy: a preliminary study.

PubMed

Tanaka, Rie; Ichikawa, Katsuhiro; Mori, Shinichiro; Sanada, Sigeru

2013-01-01

Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). It is important to keep the patient dose as low as possible while maintaining tracking accuracy. A simulation approach would be helpful to optimize the imaging conditions. This study was performed to develop a computer simulation platform based on a noise property of the imaging system for the evaluation of tracking accuracy at any noise level. Flat-field images were obtained using a direct-type dynamic FPD, and noise power spectrum (NPS) analysis was performed. The relationship between incident quantum number and pixel value was addressed, and a conversion function was created. The pixel values were converted into a map of quantum number using the conversion function, and the map was then input into the random number generator to simulate image noise. Simulation images were provided at different noise levels by changing the incident quantum numbers. Subsequently, an implanted marker was tracked automatically and the maximum tracking errors were calculated at different noise levels. The results indicated that the maximum tracking error increased with decreasing incident quantum number in flat-field images with an implanted marker. In addition, the range of errors increased with decreasing incident quantum number. The present method could be used to determine the relationship between image noise and tracking accuracy. The results indicated that the simulation approach would aid in determining exposure dose conditions according to the necessary tracking accuracy.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

Large-field-of-view imaging by multi-pupil adaptive optics.

PubMed

Park, Jung-Hoon; Kong, Lingjie; Zhou, Yifeng; Cui, Meng

2017-06-01

Adaptive optics can correct for optical aberrations. We developed multi-pupil adaptive optics (MPAO), which enables simultaneous wavefront correction over a field of view of 450 × 450 μm 2 and expands the correction area to nine times that of conventional methods. MPAO's ability to perform spatially independent wavefront control further enables 3D nonplanar imaging. We applied MPAO to in vivo structural and functional imaging in the mouse brain.

Display management subsystem, version 1: A user's eye view

NASA Technical Reports Server (NTRS)

Parker, Dolores

1986-01-01

The structure and application functions of the Display Management Subsystem (DMS) are described. The DMS, a subsystem of the Transportable Applications Executive (TAE), was designed to provide a device-independent interface for an image processing and display environment. The system is callable by C and FORTRAN applications, portable to accommodate different image analysis terminals, and easily expandable to meet local needs. Generic applications are also available for performing many image processing tasks.

[Future perspectives for diagnostic imaging in urology: from anatomic and functional to molecular imaging].

PubMed

Macis, Giuseppe; Di Giovanni, Silvia; Di Franco, Davide; Bonomo, Lorenzo

2013-01-01

The future approach of diagnostic imaging in urology follows the technological progress, which made the visualization of in vivo molecular processes possible. From anatomo-morphological diagnostic imaging and through functional imaging molecular radiology is reached. Based on molecular probes, imaging is aimed at assessing the in vivo molecular processes, their physiology and function at cellular level. The future imaging will investigate the complex tumor functioning as metabolism, aerobic glycolysis in particular, angiogenesis, cell proliferation, metastatic potential, hypoxia, apoptosis and receptors expressed by neoplastic cells. Methods for performing molecular radiology are CT, MRI, PET-CT, PET-MRI, SPECT and optical imaging. Molecular ultrasound combines technological advancement with targeted contrast media based on microbubbles, this allowing the selective registration of microbubble signal while that of stationary tissues is suppressed. An experimental study was carried out where the ultrasound molecular probe BR55 strictly bound to prostate tumor results in strong enhancement in the early phase after contrast, this contrast being maintained in the late phase. This late enhancement is markedly significant for the detection of prostatic cancer foci and to guide the biopsy sampling. The 124I-cG250 molecular antibody which is strictly linked to cellular carbonic anhydrase IX of clear cell renal carcinoma, allows the acquisition of diagnostic PET images of clear cell renal carcinoma without biopsy. This WG-250 (RENCAREX) antibody was used as a therapy in metastatic clear cell renal carcinoma. Future advancements and applications will result in early cancer diagnosis, personalized therapy that will be specific according to the molecular features of cancer and leading to the development of catheter-based multichannel molecular imaging devices for cystoscopy-based molecular imaging diagnosis and intervention.

Nicotine effects on brain function and functional connectivity in schizophrenia.

PubMed

Jacobsen, Leslie K; D'Souza, D Cyril; Mencl, W Einar; Pugh, Kenneth R; Skudlarski, Pawel; Krystal, John H

2004-04-15

Nicotine in tobacco smoke can improve functioning in multiple cognitive domains. High rates of smoking among schizophrenic patients may reflect an effort to remediate cognitive dysfunction. Our primary aim was to determine whether nicotine improves cognitive function by facilitating activation of brain regions mediating task performance or by facilitating functional connectivity. Thirteen smokers with schizophrenia and 13 smokers with no mental illness were withdrawn from tobacco and underwent functional magnetic resonance imaging (fMRI) scanning twice, once after placement of a placebo patch and once after placement of a nicotine patch. During scanning, subjects performed an n-back task with two levels of working memory load and of selective attention load. During the most difficult (dichotic 2-back) task condition, nicotine improved performance of schizophrenic subjects and worsened performance of control subjects. Nicotine also enhanced activation of a network of regions, including anterior cingulate cortex and bilateral thalamus, and modulated thalamocortical functional connectivity to a greater degree in schizophrenic than in control subjects during dichotic 2-back task performance. In tasks that tax working memory and selective attention, nicotine may improve performance in schizophrenia patients by enhancing activation of and functional connectivity between brain regions that mediate task performance.

Characterization and evaluation of a flexible MRI receive coil array for radiation therapy MR treatment planning using highly decoupled RF circuits.

PubMed

McGee, Kiaran P; Stormont, Robert S; Lindsay, Scott A; Taracila, Victor; Savitskij, Dennis; Robb, Fraser; Witte, Robert J; Kaufmann, Timothy J; Huston, John; Riederer, Stephen J; Borisch, Eric A; Rossman, Phillip J

2018-04-13

The growth in the use of magnetic resonance imaging (MRI) data for radiation therapy (RT) treatment planning has been facilitated by scanner hardware and software advances that have enabled RT patients to be imaged in treatment position while providing morphologic and functional assessment of tumor volumes and surrounding normal tissues. Despite these advances, manufacturers have been slow to develop radiofrequency (RF) coils that closely follow the contour of a RT patient undergoing MR imaging. Instead, relatively large form surface coil arrays have been adapted from diagnostic imaging. These arrays can be challenging to place on, and in general do not conform to the patient's body habitus, resulting in sub optimal image quality. The purpose of this study is to report on the characterization of a new flexible and highly decoupled RF coil for use in MR imaging of RT patients. Coil performance was evaluated by performing signal-to-noise ratio (SNR) and noise correlation measurements using two coil (SNR) and four coil (noise correlation) element combinations as a function of coil overlap distance and comparing these values to those obtained using conventional coil elements. In vivo testing was performed in both normal volunteers and patients using a four and 16 element RF coil. Phantom experiments demonstrate the highly decoupled nature of the new coil elements when compared to conventional RF coils, while in vivo testing demonstrate that these coils can be integrated into extremely flexible and form fitting substrates that follow the exact contour of the patient. The new coil design addresses limitations imposed by traditional surface coil arrays and have the potential to significantly impact MR imaging for both diagnostic and RT applications.

Sci-Thur AM: YIS – 08: Automated Imaging Quality Assurance for Image-Guided Small Animal Irradiators

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

Johnstone, Chris; Bazalova-Carter, Magdalena

Purpose: To develop quality assurance (QA) standards and tolerance levels for image quality of small animal irradiators. Methods: A fully automated in-house QA software for image analysis of a commercial microCT phantom was created. Quantitative analyses of CT linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, modulation transfer function (MTF), and CT number evaluation was performed. Phantom microCT scans from seven institutions acquired with varying parameters (kVp, mA, time, voxel size, and frame rate) and five irradiator units (Xstrahl SARRP, PXI X-RAD 225Cx, PXI X-RAD SmART, GE explore CT/RT 140, and GE Explore CT 120) were analyzed. Multi-institutional datamore » sets were compared using our in-house software to establish pass/fail criteria for each QA test. Results: CT linearity (R2>0.996) was excellent at all but Institution 2. Acceptable SNR (>35) and noise levels (<55HU) were obtained at four of the seven institutions, where failing scans were acquired with less than 120mAs. Acceptable MTF (>1.5 lp/mm for MTF=0.2) was obtained at all but Institution 6 due to the largest scan voxel size (0.35mm). The geometric accuracy passed (<1.5%) at five of the seven institutions. Conclusion: Our QA software can be used to rapidly perform quantitative imaging QA for small animal irradiators, accumulate results over time, and display possible changes in imaging functionality from its original performance and/or from the recommended tolerance levels. This tool will aid researchers in maintaining high image quality, enabling precise conformal dose delivery to small animals.« less

A discrepancy within primate spatial vision and its bearing on the definition of edge detection processes in machine vision

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1990-01-01

The visual perception of form information is considered to be based on the functioning of simple and complex neurons in the primate striate cortex. However, a review of the physiological data on these brain cells cannot be harmonized with either the perceptual spatial frequency performance of primates or the performance which is necessary for form perception in humans. This discrepancy together with recent interest in cortical-like and perceptual-like processing in image coding and machine vision prompted a series of image processing experiments intended to provide some definition of the selection of image operators. The experiments were aimed at determining operators which could be used to detect edges in a computational manner consistent with the visual perception of structure in images. Fundamental issues were the selection of size (peak spatial frequency) and circular versus oriented operators (or some combination). In a previous study, circular difference-of-Gaussian (DOG) operators, with peak spatial frequency responses at about 11 and 33 cyc/deg were found to capture the primary structural information in images. Here larger scale circular DOG operators were explored and led to severe loss of image structure and introduced spatial dislocations (due to blur) in structure which is not consistent with visual perception. Orientation sensitive operators (akin to one class of simple cortical neurons) introduced ambiguities of edge extent regardless of the scale of the operator. For machine vision schemes which are functionally similar to natural vision form perception, two circularly symmetric very high spatial frequency channels appear to be necessary and sufficient for a wide range of natural images. Such a machine vision scheme is most similar to the physiological performance of the primate lateral geniculate nucleus rather than the striate cortex.

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

Loughran, B; Singh, V; Jain, A

Purpose: Although generalized linear system analytic metrics such as GMTF and GDQE can evaluate performance of the whole imaging system including detector, scatter and focal-spot, a simplified task-specific measured metric may help to better compare detector systems. Methods: Low quantum-noise images of a neuro-vascular stent with a modified ANSI head phantom were obtained from the average of many exposures taken with the high-resolution Micro-Angiographic Fluoroscope (MAF) and with a Flat Panel Detector (FPD). The square of the Fourier Transform of each averaged image, equivalent to the measured product of the system GMTF and the object function in spatial-frequency space, wasmore » then divided by the normalized noise power spectra (NNPS) for each respective system to obtain a task-specific generalized signal-to-noise ratio. A generalized measured relative object detectability (GM-ROD) was obtained by taking the ratio of the integral of the resulting expressions for each detector system to give an overall metric that enables a realistic systems comparison for the given detection task. Results: The GM-ROD provides comparison of relative performance of detector systems from actual measurements of the object function as imaged by those detector systems. This metric includes noise correlations and spatial frequencies relevant to the specific object. Additionally, the integration bounds for the GM-ROD can be selected to emphasis the higher frequency band of each detector if high-resolution image details are to be evaluated. Examples of this new metric are discussed with a comparison of the MAF to the FPD for neuro-vascular interventional imaging. Conclusion: The GM-ROD is a new direct-measured task-specific metric that can provide clinically relevant comparison of the relative performance of imaging systems. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

Characterization and evaluation of a flexible MRI receive coil array for radiation therapy MR treatment planning using highly decoupled RF circuits

NASA Astrophysics Data System (ADS)

McGee, Kiaran P.; Stormont, Robert S.; Lindsay, Scott A.; Taracila, Victor; Savitskij, Dennis; Robb, Fraser; Witte, Robert J.; Kaufmann, Timothy J.; Huston, John, III; Riederer, Stephen J.; Borisch, Eric A.; Rossman, Phillip J.

2018-04-01

The growth in the use of magnetic resonance imaging (MRI) data for radiation therapy (RT) treatment planning has been facilitated by scanner hardware and software advances that have enabled RT patients to be imaged in treatment position while providing morphologic and functional assessment of tumor volumes and surrounding normal tissues. Despite these advances, manufacturers have been slow to develop radiofrequency (RF) coils that closely follow the contour of a RT patient undergoing MR imaging. Instead, relatively large form surface coil arrays have been adapted from diagnostic imaging. These arrays can be challenging to place on, and in general do not conform to the patient’s body habitus, resulting in sub optimal image quality. The purpose of this study is to report on the characterization of a new flexible and highly decoupled RF coil for use in MR imaging of RT patients. Coil performance was evaluated by performing signal-to-noise ratio (SNR) and noise correlation measurements using two coil (SNR) and four coil (noise correlation) element combinations as a function of coil overlap distance and comparing these values to those obtained using conventional coil elements. In vivo testing was performed in both normal volunteers and patients using a four and 16 element RF coil. Phantom experiments demonstrate the highly decoupled nature of the new coil elements when compared to conventional RF coils, while in vivo testing demonstrate that these coils can be integrated into extremely flexible and form fitting substrates that follow the exact contour of the patient. The new coil design addresses limitations imposed by traditional surface coil arrays and have the potential to significantly impact MR imaging for both diagnostic and RT applications.

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

Initial Investigation of preclinical integrated SPECT and MR imaging.

PubMed

Hamamura, Mark J; Ha, Seunghoon; Roeck, Werner W; Wagenaar, Douglas J; Meier, Dirk; Patt, Bradley E; Nalcioglu, Orhan

2010-02-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source.

Initial Investigation of Preclinical Integrated SPECT and MR Imaging

PubMed Central

Hamamura, Mark J.; Ha, Seunghoon; Roeck, Werner W.; Wagenaar, Douglas J.; Meier, Dirk; Patt, Bradley E.; Nalcioglu, Orhan

2014-01-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source. PMID:20082527

Three-dimensional surface imaging system for assessing human obesity

NASA Astrophysics Data System (ADS)

Xu, Bugao; Yu, Wurong; Yao, Ming; Pepper, M. Reese; Freeland-Graves, Jeanne H.

2009-10-01

The increasing prevalence of obesity suggests a need to develop a convenient, reliable, and economical tool for assessment of this condition. Three-dimensional (3-D) body surface imaging has emerged as an exciting technology for the estimation of body composition. We present a new 3-D body imaging system, which is designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology is used to satisfy the requirement for a simple hardware setup and fast image acquisition. The portability of the system is created via a two-stand configuration, and the accuracy of body volume measurements is improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3-D body imaging. Body measurement functions dedicated to body composition assessment also are developed. The overall performance of the system is evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

A 3D surface imaging system for assessing human obesity

NASA Astrophysics Data System (ADS)

Xu, B.; Yu, W.; Yao, M.; Yao, X.; Li, Q.; Pepper, M. R.; Freeland-Graves, J. H.

2009-08-01

The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body measurement functions dedicated to body composition assessment also were developed. The overall performance of the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

Capsule Endoscopy in Patients with Implantable Electromedical Devices is Safe

PubMed Central

Harris, Lucinda A.; Hansel, Stephanie L.; Rajan, Elizabeth; Srivathsan, Komandoor; Rea, Robert; Crowell, Michael D.; Fleischer, David E.; Pasha, Shabana F.; Gurudu, Suryakanth R.; Heigh, Russell I.; Shiff, Arthur D.; Post, Janice K.; Leighton, Jonathan A.

2013-01-01

Background and Study Aims. The presence of an implantable electromechanical cardiac device (IED) has long been considered a relative contraindication to the performance of video capsule endoscopy (CE). The primary aim of this study was to evaluate the safety of CE in patients with IEDs. A secondary purpose was to determine whether IEDs have any impact on images captured by CE. Patients and Methods. A retrospective chart review of all patients who had a capsule endoscopy at Mayo Clinic in Scottsdale, AZ, USA, or Rochester, MN, USA, (January 2002 to June 2010) was performed to identify CE studies done on patients with IEDs. One hundred and eighteen capsule studies performed in 108 patients with IEDs were identified and reviewed for demographic data, method of preparation, and study data. Results. The most common indications for CE were obscure gastrointestinal bleeding (77%), anemia (14%), abdominal pain (5%), celiac disease (2%), diarrhea (1%), and Crohn's disease (1%). Postprocedure assessments did not reveal any detectable alteration on the function of the IED. One patient with an ICD had a 25-minute loss of capsule imaging due to recorder defect. Two patients with LVADs had interference with capsule image acquisition. Conclusions. CE did not interfere with IED function, including PM, ICD, and/or LVAD and thus appears safe. Additionally, PM and ICD do not appear to interfere with image acquisition but LVAD may interfere with capsule images and require that capsule leads be positioned as far away as possible from the IED to assure reliable image acquisition. PMID:23710168

Scanning two-photon microscopy with upconverting lanthanide nanoparticles via Richardson-Lucy deconvolution.

PubMed

Gainer, Christian F; Utzinger, Urs; Romanowski, Marek

2012-07-01

The use of upconverting lanthanide nanoparticles in fast-scanning microscopy is hindered by a long luminescence decay time, which greatly blurs images acquired in a nondescanned mode. We demonstrate herein an image processing method based on Richardson-Lucy deconvolution that mitigates the detrimental effects of their luminescence lifetime. This technique generates images with lateral resolution on par with the system's performance, ∼1.2  μm, while maintaining an axial resolution of 5 μm or better at a scan rate comparable with traditional two-photon microscopy. Remarkably, this can be accomplished with near infrared excitation power densities of 850 W/cm(2), several orders of magnitude below those used in two-photon imaging with molecular fluorophores. By way of illustration, we introduce the use of lipids to coat and functionalize these nanoparticles, rendering them water dispersible and readily conjugated to biologically relevant ligands, in this case epidermal growth factor receptor antibody. This deconvolution technique combined with the functionalized nanoparticles will enable three-dimensional functional tissue imaging at exceptionally low excitation power densities.

Angular stable plates in proximal meta-epiphyseal tibial fractures: study of joint restoration and clinical and functional evaluation.

PubMed

Giannotti, S; Giovannelli, D; Dell'Osso, G; Bottai, V; Bugelli, G; Celli, F; Citarelli, C; Guido, G

2016-04-01

The tibial plateau fractures involve one of the main weight bearing joints of the human body. The goals of surgical treatment are anatomical reduction, articular surface reconstruction and high primary stability. The aim of this study was to evaluate the clinical and functional outcomes after internal plate fixation of this kind of fractures. From January 2009 to December 2012, we treated 75 cases of tibial plateau fracture with angular stable plates. We used Rasmussen Score and the Knee Society Score for the clinical and functional evaluation. Twenty-five cases that underwent hardware removal had arthroscopic and CT evaluation of the joint. No complications occurred. The clinical and functional evaluation, performed by the KSS and Rasmussen Score, highlighted the high percentage of good-to-excellent results (over 90 %). In every case, the range of motion was good with flexion >90°. Arthroscopy showed the presence of chondral damage in 100 % of patients. In all the cases, we found that X-ray images seem better than the CT images. Angular stable plates allow to obtain a good primary stability, permitting an early joint recovery with an excellent range of motion. Avoiding to perform a knee arthrotomy at the time of fracture reduction could prove to be an advantage in terms of functional recovery. The meniscus on the injured bone should be preserved in order to maintain good function of the joint. X-ray images remain the gold standard in checking the progression of post-traumatic osteoarthritis.

Characterization of scintillator-based detectors for few-ten-keV high-spatial-resolution x-ray imaging

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

Larsson, Jakob C., E-mail: jakob.larsson@biox.kth.se; Lundström, Ulf; Hertz, Hans M.

2016-06-15

Purpose: High-spatial-resolution x-ray imaging in the few-ten-keV range is becoming increasingly important in several applications, such as small-animal imaging and phase-contrast imaging. The detector properties critically influence the quality of such imaging. Here the authors present a quantitative comparison of scintillator-based detectors for this energy range and at high spatial frequencies. Methods: The authors determine the modulation transfer function, noise power spectrum (NPS), and detective quantum efficiency for Gadox, needle CsI, and structured CsI scintillators of different thicknesses and at different photon energies. An extended analysis of the NPS allows for direct measurements of the scintillator effective absorption efficiency andmore » effective light yield as well as providing an alternative method to assess the underlying factors behind the detector properties. Results: There is a substantial difference in performance between the scintillators depending on the imaging task but in general, the CsI based scintillators perform better than the Gadox scintillators. At low energies (16 keV), a thin needle CsI scintillator has the best performance at all frequencies. At higher energies (28–38 keV), the thicker needle CsI scintillators and the structured CsI scintillator all have very good performance. The needle CsI scintillators have higher absorption efficiencies but the structured CsI scintillator has higher resolution. Conclusions: The choice of scintillator is greatly dependent on the imaging task. The presented comparison and methodology will assist the imaging scientist in optimizing their high-resolution few-ten-keV imaging system for best performance.« less

Characterization of scintillator-based detectors for few-ten-keV high-spatial-resolution x-ray imaging.

PubMed

Larsson, Jakob C; Lundström, Ulf; Hertz, Hans M

2016-06-01

High-spatial-resolution x-ray imaging in the few-ten-keV range is becoming increasingly important in several applications, such as small-animal imaging and phase-contrast imaging. The detector properties critically influence the quality of such imaging. Here the authors present a quantitative comparison of scintillator-based detectors for this energy range and at high spatial frequencies. The authors determine the modulation transfer function, noise power spectrum (NPS), and detective quantum efficiency for Gadox, needle CsI, and structured CsI scintillators of different thicknesses and at different photon energies. An extended analysis of the NPS allows for direct measurements of the scintillator effective absorption efficiency and effective light yield as well as providing an alternative method to assess the underlying factors behind the detector properties. There is a substantial difference in performance between the scintillators depending on the imaging task but in general, the CsI based scintillators perform better than the Gadox scintillators. At low energies (16 keV), a thin needle CsI scintillator has the best performance at all frequencies. At higher energies (28-38 keV), the thicker needle CsI scintillators and the structured CsI scintillator all have very good performance. The needle CsI scintillators have higher absorption efficiencies but the structured CsI scintillator has higher resolution. The choice of scintillator is greatly dependent on the imaging task. The presented comparison and methodology will assist the imaging scientist in optimizing their high-resolution few-ten-keV imaging system for best performance.

Boosting instance prototypes to detect local dermoscopic features.

PubMed

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

NASA Technical Reports Server (NTRS)

Jayroe, R. R.

1994-01-01

Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available evaluation criteria basically compare the observed results with the expected results. For the image reconstruction processes of registration and compression, the expected results are usually the original data or some selected characteristics of the original data. For classification processes the expected result is the ground truth of the scene. Thus, the comparison process consists of determining what changes occur in processing, where the changes occur, how much change occurs, and the amplitude of the change. The package includes evaluation routines for performing such comparisons as average uncertainty, average information transfer, chi-square statistics, multidimensional histograms, and computation of contingency matrices. This collection of routines is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 662K of 8 bit bytes. This collection of image processing and evaluation routines was developed in 1979.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography.

PubMed

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-09-01

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multiresolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low-resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model, which may introduce artifacts in regions where no significant correlation exists between anatomical and functional details. A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present, the new model outperformed the 2D global approach, avoiding artifacts and significantly improving quality of the corrected images and their quantitative accuracy. A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multiresolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography

PubMed Central

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E.; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-01-01

Purpose Partial volume effects (PVE) are consequences of the limited spatial resolution in emission tomography leading to under-estimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multi-resolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model which may introduce artefacts in regions where no significant correlation exists between anatomical and functional details. Methods A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Results Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present the new model outperformed the 2D global approach, avoiding artefacts and significantly improving quality of the corrected images and their quantitative accuracy. Conclusions A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multi-resolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information. PMID:21978037

Functional Connectivity of the Precuneus in Female University Students with Long-Term Musical Training.

PubMed

Tanaka, Shoji; Kirino, Eiji

2016-01-01

Conceiving concrete mental imagery is critical for skillful musical expression and performance. The precuneus, a core component of the default mode network (DMN), is a hub of mental image processing that participates in functions such as episodic memory retrieval and imagining future events. The precuneus connects with many brain regions in the frontal, parietal, temporal, and occipital cortices. The aim of this study was to examine the effects of long-term musical training on the resting-state functional connectivity of the precuneus. Our hypothesis was that the functional connectivity of the precuneus is altered in musicians. We analyzed the functional connectivity of the precuneus using resting-state functional magnetic resonance imaging (fMRI) data recorded in female university students majoring in music and nonmusic disciplines. The results show that the music students had higher functional connectivity of the precuneus with opercular/insular regions, which are associated with interoceptive and emotional processing; Heschl's gyrus (HG) and the planum temporale (PT), which process complex tonal information; and the lateral occipital cortex (LOC), which processes visual information. Connectivity of the precuneus within the DMN did not differ between the two groups. Our finding suggests that functional connections between the precuneus and the regions outside of the DMN play an important role in musical performance. We propose that a neural network linking the precuneus with these regions contributes to translate mental imagery into information relevant to musical performance.

Functional Connectivity of the Precuneus in Female University Students with Long-Term Musical Training

PubMed Central

Tanaka, Shoji; Kirino, Eiji

2016-01-01

Conceiving concrete mental imagery is critical for skillful musical expression and performance. The precuneus, a core component of the default mode network (DMN), is a hub of mental image processing that participates in functions such as episodic memory retrieval and imagining future events. The precuneus connects with many brain regions in the frontal, parietal, temporal, and occipital cortices. The aim of this study was to examine the effects of long-term musical training on the resting-state functional connectivity of the precuneus. Our hypothesis was that the functional connectivity of the precuneus is altered in musicians. We analyzed the functional connectivity of the precuneus using resting-state functional magnetic resonance imaging (fMRI) data recorded in female university students majoring in music and nonmusic disciplines. The results show that the music students had higher functional connectivity of the precuneus with opercular/insular regions, which are associated with interoceptive and emotional processing; Heschl’s gyrus (HG) and the planum temporale (PT), which process complex tonal information; and the lateral occipital cortex (LOC), which processes visual information. Connectivity of the precuneus within the DMN did not differ between the two groups. Our finding suggests that functional connections between the precuneus and the regions outside of the DMN play an important role in musical performance. We propose that a neural network linking the precuneus with these regions contributes to translate mental imagery into information relevant to musical performance. PMID:27445765

Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images

NASA Technical Reports Server (NTRS)

Blonski, Slawomir

2006-01-01

Characterization was conducted under the Memorandum of Understanding among Orbital Sciences Corp., ORBIMAGE, Inc., and NASA Applied Sciences Directorate. Acquired five OrbView-3 panchromatic images of the permanent Stennis Space Center edge targets painted on a concrete surface. Each image is available at two processing levels: Georaw and Basic. Georaw is an intermediate image in which individual pixels are aligned by a nominal shift in the along-scan direction to adjust for the staggered layout of the panchromatic detectors along the focal plane array. Georaw images are engineering data and are not delivered to customers. The Basic product includes a cubic interpolation to align the pixels better along the focal plane and to correct for sensor artifacts, such as smile and attitude smoothing. This product retains satellite geometry - no rectification is performed. Processing of the characterized images did not include image sharpening, which is applied by default to OrbView-3 image products delivered by ORBIMAGE to customers. Edge responses were extracted from images of tilted edges in two directions: along-scan and cross-scan. Each edge response was approximated with a superposition of three sigmoidal functions through a nonlinear least-squares curve-fitting. Line Spread Functions (LSF) were derived by differentiation of the analytical approximation. Modulation Transfer Functions (MTF) were obtained after applying the discrete Fourier transform to the LSF.

Brain activity underlying tool-related and imitative skills after major left hemisphere stroke.

PubMed

Martin, Markus; Nitschke, Kai; Beume, Lena; Dressing, Andrea; Bühler, Laura E; Ludwig, Vera M; Mader, Irina; Rijntjes, Michel; Kaller, Christoph P; Weiller, Cornelius

2016-05-01

Apraxia is a debilitating cognitive motor disorder that frequently occurs after left hemisphere stroke and affects tool-associated and imitative skills. However, the severity of the apraxic deficits varies even across patients with similar lesions. This variability raises the question whether regions outside the left hemisphere network typically associated with cognitive motor tasks in healthy subjects are of additional functional relevance. To investigate this hypothesis, we explored regions where functional magnetic resonance imaging activity is associated with better cognitive motor performance in patients with left hemisphere ischaemic stroke. Thirty-six patients with chronic (>6 months) large left hemisphere infarcts (age ± standard deviation, 60 ± 12 years, 29 male) and 29 control subjects (age ± standard deviation, 72 ± 7, 15 male) were first assessed behaviourally outside the scanner with tests for actual tool use, pantomime and imitation of tool-use gestures, as well as for meaningless gesture imitation. Second, functional magnetic resonance imaging activity was registered during the passive observation of videos showing tool-associated actions. Voxel-wise linear regression analyses were used to identify areas where behavioural performance was correlated with functional magnetic resonance imaging activity. Furthermore, lesions were delineated on the magnetic resonance imaging scans for voxel-based lesion-symptom mapping. The analyses revealed two sets of regions where functional magnetic resonance imaging activity was associated with better performance in the clinical tasks. First, activity in left hemisphere areas thought to mediate cognitive motor functions in healthy individuals (i.e. activity within the putative 'healthy' network) was correlated with better scores. Within this network, tool-associated tasks were mainly related to activity in supramarginal gyrus and ventral premotor cortex, while meaningless gesture imitation depended more on the anterior intraparietal sulcus and superior parietal lobule. Second, repeating the regression analyses with total left hemisphere lesion volume as additional covariate demonstrated that tool-related skills were further supported by right premotor, right inferior frontal and left anterior temporal areas, while meaningless gesture imitation was also driven by the left dorso-lateral prefrontal cortex. In summary, tool-related and imitative skills in left hemisphere stroke patients depend on the activation of spared left hemisphere regions that support these abilities in healthy individuals. In addition, cognitive motor functions rely on the activation of ipsi- and contralesional areas that are situated outside this 'healthy' network. This activity may explain why some patients perform surprisingly well despite large left brain lesions, while others are severely impaired. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

3-D ultrafast Doppler imaging applied to the noninvasive mapping of blood vessels in vivo.

PubMed

Provost, Jean; Papadacci, Clement; Demene, Charlie; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

2015-08-01

Ultrafast Doppler imaging was introduced as a technique to quantify blood flow in an entire 2-D field of view, expanding the field of application of ultrasound imaging to the highly sensitive anatomical and functional mapping of blood vessels. We have recently developed 3-D ultrafast ultrasound imaging, a technique that can produce thousands of ultrasound volumes per second, based on a 3-D plane and diverging wave emissions, and demonstrated its clinical feasibility in human subjects in vivo. In this study, we show that noninvasive 3-D ultrafast power Doppler, pulsed Doppler, and color Doppler imaging can be used to perform imaging of blood vessels in humans when using coherent compounding of 3-D tilted plane waves. A customized, programmable, 1024-channel ultrasound system was designed to perform 3-D ultrafast imaging. Using a 32 × 32, 3-MHz matrix phased array (Vermon, Tours, France), volumes were beamformed by coherently compounding successive tilted plane wave emissions. Doppler processing was then applied in a voxel-wise fashion. The proof of principle of 3-D ultrafast power Doppler imaging was first performed by imaging Tygon tubes of various diameters, and in vivo feasibility was demonstrated by imaging small vessels in the human thyroid. Simultaneous 3-D color and pulsed Doppler imaging using compounded emissions were also applied in the carotid artery and the jugular vein in one healthy volunteer.

Brain Tumors: The Influence of Tumor Type and Routine MR Imaging Characteristics at BOLD Functional MR Imaging in the Primary Motor Gyrus

PubMed Central

Fraga de Abreu, Vitor Hugo; Peck, Kyung K.; Petrovich-Brennan, Nicole M.; Woo, Kaitlin M.

2016-01-01

Purpose To evaluate the effects of histologic features and anatomic magnetic resonance (MR) imaging characteristics of brain tumors on the functional MR imaging signal in the primary motor cortex (PMC), as false-negative blood oxygen level–dependent (BOLD) functional MR imaging activation can limit the accurate localization of eloquent cortices. Materials and Methods Institutional review board approval was obtained, and informed consent was waived for this HIPAA-compliant retrospective study. It comprised 63 patients referred between 2006 and 2014 for preoperative functional MR imaging localization of the Rolandic cortex. The patients had glioblastoma multiforme (GBM) (n = 20), metastasis (n = 21), or meningioma (n = 22). The volumes of functional MR imaging activation were measured during performance of a bilateral hand motor task. Ratios of functional MR imaging activation were normalized to PMC volume. Statistical analysis was performed for the following: (a) differences between hemispheres within each histologic tumor type (paired Wilcoxon test), (b) differences across tumor types (Kruskal-Wallis and Fisher tests), (c) pairwise tests between tumor types (Mann-Whitney U test), (d) relationships between fast fluid-attenuated inversion recovery (FLAIR) data and enhancement volume with activation (Spearman rank correlation coefficient), and (e) differences in activation volumes by tumor location (Mann-Whitney U test). Results A significant interhemispheric difference was found between the activation volumes in GBMs (mean, 511.43 voxels ± 307.73 [standard deviation] and 330.78 voxels ± 278.95; P < .01) but not in metastases (504.68 voxels ± 220.98 and 460.22 voxels ± 276.83; P = .15) or meningiomas (424.07 voxels ± 247.58 and 415.18 voxels ± 222.36; P = .85). GBMs showed significantly lower activation ratios (median, 0.49; range, 0.04–1.15) than metastases (median, 0.79; range, 0.28–1.66; P = .043) and meningiomas (median, 0.91; range, 0.52–2.05; P < .01). There was a moderate correlation with the volumes of FLAIR abnormality in metastases (ρ = −0.50) and meningiomas (ρ = −0.55). Enhancement volume (ρ = −0.11) and tumor distance from the PMC (median, 0.73 and range, 0.04–2.05 for near and median, 0.82 and range, 0.39–1.66 for far; P = .14) did not influence activation. Conclusion BOLD functional MR imaging activation in the ipsilateral PMC is influenced by tumor type and is significantly reduced in GBMs. FLAIR abnormality correlates moderately with the activation ratios in metastases and meningiomas. © RSNA, 2016 Online supplemental material is available for this article. PMID:27383533

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Analyser-based phase contrast image reconstruction using geometrical optics.

PubMed

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-07-21

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 microm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Modeling a color-rendering operator for high dynamic range images using a cone-response function

NASA Astrophysics Data System (ADS)

Choi, Ho-Hyoung; Kim, Gi-Seok; Yun, Byoung-Ju

2015-09-01

Tone-mapping operators are the typical algorithms designed to produce visibility and the overall impression of brightness, contrast, and color of high dynamic range (HDR) images on low dynamic range (LDR) display devices. Although several new tone-mapping operators have been proposed in recent years, the results of these operators have not matched those of the psychophysical experiments based on the human visual system. A color-rendering model that is a combination of tone-mapping and cone-response functions using an XYZ tristimulus color space is presented. In the proposed method, the tone-mapping operator produces visibility and the overall impression of brightness, contrast, and color in HDR images when mapped onto relatively LDR devices. The tone-mapping resultant image is obtained using chromatic and achromatic colors to avoid well-known color distortions shown in the conventional methods. The resulting image is then processed with a cone-response function wherein emphasis is placed on human visual perception (HVP). The proposed method covers the mismatch between the actual scene and the rendered image based on HVP. The experimental results show that the proposed method yields an improved color-rendering performance compared to conventional methods.

A large, switchable optical clearing skull window for cerebrovascular imaging

PubMed Central

Zhang, Chao; Feng, Wei; Zhao, Yanjie; Yu, Tingting; Li, Pengcheng; Xu, Tonghui; Luo, Qingming; Zhu, Dan

2018-01-01

Rationale: Intravital optical imaging is a significant method for investigating cerebrovascular structure and function. However, its imaging contrast and depth are limited by the turbid skull. Tissue optical clearing has a great potential for solving this problem. Our goal was to develop a transparent skull window, without performing a craniotomy, for use in assessing cerebrovascular structure and function. Methods: Skull optical clearing agents were topically applied to the skulls of mice to create a transparent window within 15 min. The clearing efficacy, repeatability, and safety of the skull window were then investigated. Results: Imaging through the optical clearing skull window enhanced both the contrast and the depth of intravital imaging. The skull window could be used on 2-8-month-old mice and could be expanded from regional to bi-hemispheric. In addition, the window could be repeatedly established without inducing observable inflammation and metabolic toxicity. Conclusion: We successfully developed an easy-to-handle, large, switchable, and safe optical clearing skull window. Combined with various optical imaging techniques, cerebrovascular structure and function can be observed through this optical clearing skull window. Thus, it has the potential for use in basic research on the physiopathologic processes of cortical vessels. PMID:29774069

An optimal algorithm for reconstructing images from binary measurements

NASA Astrophysics Data System (ADS)

Yang, Feng; Lu, Yue M.; Sbaiz, Luciano; Vetterli, Martin

2010-01-01

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera [1] or the gigapixel digital film camera [2, 3]. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor response curve, and reduced exposure time in low light conditions, due to its highly sensitive photon detection mechanism. We use maximum likelihood estimator (MLE) to reconstruct a high quality conventional image from the binary sensor measurements of the gigavision camera. We prove that when the threshold T is "1", the negative loglikelihood function is a convex function. Therefore, optimal solution can be achieved using convex optimization. Base on filter bank techniques, fast algorithms are given for computing the gradient and the multiplication of a vector and Hessian matrix of the negative log-likelihood function. We show that with a minor change, our algorithm also works for estimating conventional images from multiple binary images. Numerical experiments with synthetic 1-D signals and images verify the effectiveness and quality of the proposed algorithm. Experimental results also show that estimation performance can be improved by increasing the oversampling factor or the number of binary images.

Functional Imaging of Audio-Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed

Rinne, Teemu; Muers, Ross S; Salo, Emma; Slater, Heather; Petkov, Christopher I

2017-06-01

The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio-visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio-visual selective attention modulates the primate brain, identify sources for "lost" attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. © The Author 2017. Published by Oxford University Press.

Functional Imaging of Audio–Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed Central

Muers, Ross S.; Salo, Emma; Slater, Heather; Petkov, Christopher I.

2017-01-01

Abstract The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio–visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio–visual selective attention modulates the primate brain, identify sources for “lost” attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. PMID:28419201

Selected configuration tradeoffs of contour optical instruments

NASA Astrophysics Data System (ADS)

Warren, J.; Strohbehn, K.; Murchie, S.; Fort, D.; Reynolds, E.; Heyler, G.; Peacock, K.; Boldt, J.; Darlington, E.; Hayes, J.; Henshaw, R.; Izenberg, N.; Kardian, C.; Lees, J.; Lohr, D.; Mehoke, D.; Schaefer, E.; Sholar, T.; Spisz, T.; Willey, C.; Veverka, J.; Bell, J.; Cochran, A.

2003-01-01

The Comet Nucleus Tour (CONTOUR) is a low-cost NASA Discovery mission designed to conduct three close flybys of comet nuclei. Selected configuration tradeoffs conducted to balance science requirements with low mission cost are reviewed. The tradeoffs discussed focus on the optical instruments and related spacecraft considerations. Two instruments are under development. The CONTOUR Forward Imager (CFI) is designed to perform optical navigation, moderate resolution nucleus/jet imaging, and imaging of faint molecular emission bands in the coma. The CONTOUR Remote Imager and Spectrometer (CRISP) is designed to obtain high-resolution multispectral images of the nucleus, conduct spectral mapping of the nucleus surface, and provide a backup optical navigation capability. Tradeoffs discussed are: (1) the impact on the optical instruments of not using reaction wheels on the spacecraft, (2) the improved performance and simplification gained by implementing a dedicated star tracker instead of including this function in CFI, (3) the improved flexibility and robustness of switching to a low frame rate tracker for CRISP, (4) the improved performance and simplification of replacing a visible imaging spectrometer by enhanced multispectral imaging in CRISP, and (5) the impact on spacecraft resources of these and other tradeoffs.

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

On-orbit Performance and Calibration of the HMI Instrument

NASA Astrophysics Data System (ADS)

Hoeksema, J. Todd; Bush, Rock; HMI Calibration Team

2016-10-01

The Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) has observed the Sun almost continuously since the completion of commissioning in May 2010, returning more than 100,000,000 filtergrams from geosynchronous orbit. Diligent and exhaustive monitoring of the instrument's performance ensures that HMI functions properly and allows proper calibration of the full-disk images and processing of the HMI observables. We constantly monitor trends in temperature, pointing, mechanism behavior, and software errors. Cosmic ray contamination is detected and bad pixels are removed from each image. Routine calibration sequences and occasional special observing programs are used to measure the instrument focus, distortion, scattered light, filter profiles, throughput, and detector characteristics. That information is used to optimize instrument performance and adjust calibration of filtergrams and observables.

MEMS-based system and image processing strategy for epiretinal prosthesis.

PubMed

Xia, Peng; Hu, Jie; Qi, Jin; Gu, Chaochen; Peng, Yinghong

2015-01-01

Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.

Multifacet structure of observed reconstructed integral images.

PubMed

Martínez-Corral, Manuel; Javidi, Bahram; Martínez-Cuenca, Raúl; Saavedra, Genaro

2005-04-01

Three-dimensional images generated by an integral imaging system suffer from degradations in the form of grid of multiple facets. This multifacet structure breaks the continuity of the observed image and therefore reduces its visual quality. We perform an analysis of this effect and present the guidelines in the design of lenslet imaging parameters for optimization of viewing conditions with respect to the multifacet degradation. We consider the optimization of the system in terms of field of view, observer position and pupil function, lenslet parameters, and type of reconstruction. Numerical tests are presented to verify the theoretical analysis.

Restoration of non-uniform exposure motion blurred image

NASA Astrophysics Data System (ADS)

Luo, Yuanhong; Xu, Tingfa; Wang, Ningming; Liu, Feng

2014-11-01

Restoring motion-blurred image is the key technologies in the opto-electronic detection system. The imaging sensors such as CCD and infrared imaging sensor, which are mounted on the motion platforms, quickly move together with the platforms of high speed. As a result, the images become blur. The image degradation will cause great trouble for the succeeding jobs such as objects detection, target recognition and tracking. So the motion-blurred images must be restoration before detecting motion targets in the subsequent images. On the demand of the real weapon task, in order to deal with targets in the complex background, this dissertation uses the new theories in the field of image processing and computer vision to research the new technology of motion deblurring and motion detection. The principle content is as follows: 1) When the prior knowledge about degradation function is unknown, the uniform motion blurred images are restored. At first, the blur parameters, including the motion blur extent and direction of PSF(point spread function), are estimated individually in domain of logarithmic frequency. The direction of PSF is calculated by extracting the central light line of the spectrum, and the extent is computed by minimizing the correction between the fourier spectrum of the blurred image and a detecting function. Moreover, in order to remove the strip in the deblurred image, windows technique is employed in the algorithm, which makes the deblurred image clear. 2) According to the principle of infrared image non-uniform exposure, a new restoration model for infrared blurred images is developed. The fitting of infrared image non-uniform exposure curve is performed by experiment data. The blurred images are restored by the fitting curve.

ISLE (Image and Signal Processing LISP Environment) reference manual

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

Sherwood, R.J.; Searfus, R.M.

1990-01-01

ISLE is a rapid prototyping system for performing image and signal processing. It is designed to meet the needs of a person doing development of image and signal processing algorithms in a research environment. The image and signal processing modules in ISLE form a very capable package in themselves. They also provide a rich environment for quickly and easily integrating user-written software modules into the package. ISLE is well suited to applications in which there is a need to develop a processing algorithm in an interactive manner. It is straightforward to develop the algorithms, load it into ISLE, apply themore » algorithm to an image or signal, display the results, then modify the algorithm and repeat the develop-load-apply-display cycle. ISLE consists of a collection of image and signal processing modules integrated into a cohesive package through a standard command interpreter. ISLE developer elected to concentrate their effort on developing image and signal processing software rather than developing a command interpreter. A COMMON LISP interpreter was selected for the command interpreter because it already has the features desired in a command interpreter, it supports dynamic loading of modules for customization purposes, it supports run-time parameter and argument type checking, it is very well documented, and it is a commercially supported product. This manual is intended to be a reference manual for the ISLE functions The functions are grouped into a number of categories and briefly discussed in the Function Summary chapter. The full descriptions of the functions and all their arguments are given in the Function Descriptions chapter. 6 refs.« less

Design Criteria For Networked Image Analysis System

NASA Astrophysics Data System (ADS)

Reader, Cliff; Nitteberg, Alan

1982-01-01

Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

Neutron Radiography, Tomography, and Diffraction of Commercial Lithium-ion Polymer Batteries

NASA Astrophysics Data System (ADS)

Butler, Leslie G.; Lehmann, Eberhard H.; Schillinger, Burkhard

Imaging an intact, commercial battery as it cycles and wears is proved possible with neutron imaging. The wavelength range of imaging neutrons corresponds nicely with crystallographic dimensions of the electrochemically active species and the metal elec- trodes are relatively transparent. The time scale of charge/discharge cycling is well matched to dynamic tomography as performed with a golden ratio based projection angle ordering. The hydrogen content does create scatter which tends to blur internal struc- ture. In this report, three neutron experiments will be described: 3D images of charged and discharged batteries were obtained with monochromatic neutrons at the FRM II reactor. 2D images (PSI) of fresh and worn batteries as a function of charge state may show a new wear pattern. In situ neutron diffraction (SNS) of the intact battery provides more information about the concentrations of electrochemical species within the battery as a function of charge state and wear. The combination of 2D imaging, 3D imaging, and diffraction data show how neutron imaging can contribute to battery development and wear monitoring.

Polychromatic sparse image reconstruction and mass attenuation spectrum estimation via B-spline basis function expansion

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

Gu, Renliang, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu; Dogandžić, Aleksandar, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu

2015-03-31

We develop a sparse image reconstruction method for polychromatic computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. To obtain a parsimonious measurement model parameterization, we first rewrite the measurement equation using our mass-attenuation parameterization, which has the Laplace integral form. The unknown mass-attenuation spectrum is expanded into basis functions using a B-spline basis of order one. We develop a block coordinate-descent algorithm for constrained minimization of a penalized negative log-likelihood function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and sparsity of themore » density map image in the wavelet domain. This algorithm alternates between a Nesterov’s proximal-gradient step for estimating the density map image and an active-set step for estimating the incident spectrum parameters. Numerical simulations demonstrate the performance of the proposed scheme.« less

Advanced Ultrasound Technologies for Diagnosis and Therapy.

PubMed

Rix, Anne; Lederle, Wiltrud; Theek, Benjamin; Lammers, Twan; Moonen, Chrit; Schmitz, Georg; Kiessling, Fabian

2018-05-01

Ultrasound is among the most rapidly advancing imaging techniques. Functional methods such as elastography have been clinically introduced, and tissue characterization is improved by contrast-enhanced scans. Here, novel superresolution techniques provide unique morphologic and functional insights into tissue vascularization. Functional analyses are complemented by molecular ultrasound imaging, to visualize markers of inflammation and angiogenesis. The full potential of diagnostic ultrasound may become apparent by integrating these multiple imaging features in radiomics approaches. Emerging interest in ultrasound also results from its therapeutic potential. Various applications of tumor ablation with high-intensity focused ultrasound are being clinically evaluated, and its performance strongly benefits from the integration into MRI. Additionally, oscillating microbubbles mediate sonoporation to open biologic barriers, thus improving the delivery of drugs or nucleic acids that are coadministered or coformulated with microbubbles. This article provides an overview of recent developments in diagnostic and therapeutic ultrasound, highlighting multiple innovation tracks and their translational potential. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Table-driven image transformation engine algorithm

NASA Astrophysics Data System (ADS)

Shichman, Marc

1993-04-01

A high speed image transformation engine (ITE) was designed and a prototype built for use in a generic electronic light table and image perspective transformation application code. The ITE takes any linear transformation, breaks the transformation into two passes and resamples the image appropriately for each pass. The system performance is achieved by driving the engine with a set of look up tables computed at start up time for the calculation of pixel output contributions. Anti-aliasing is done automatically in the image resampling process. Operations such as multiplications and trigonometric functions are minimized. This algorithm can be used for texture mapping, image perspective transformation, electronic light table, and virtual reality.

An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework

NASA Astrophysics Data System (ADS)

Sarı, H.; Eken, S.; Sayar, A.

2017-11-01

In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.

Temporal Coding of Volumetric Imagery

NASA Astrophysics Data System (ADS)

Llull, Patrick Ryan

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption. This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications. Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level. Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions. Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z ) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke. Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

Penalized Weighted Least-Squares Approach to Sinogram Noise Reduction and Image Reconstruction for Low-Dose X-Ray Computed Tomography

PubMed Central

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-01-01

Reconstructing low-dose X-ray CT (computed tomography) images is a noise problem. This work investigated a penalized weighted least-squares (PWLS) approach to address this problem in two dimensions, where the WLS considers first- and second-order noise moments and the penalty models signal spatial correlations. Three different implementations were studied for the PWLS minimization. One utilizes a MRF (Markov random field) Gibbs functional to consider spatial correlations among nearby detector bins and projection views in sinogram space and minimizes the PWLS cost function by iterative Gauss-Seidel algorithm. Another employs Karhunen-Loève (KL) transform to de-correlate data signals among nearby views and minimizes the PWLS adaptively to each KL component by analytical calculation, where the spatial correlation among nearby bins is modeled by the same Gibbs functional. The third one models the spatial correlations among image pixels in image domain also by a MRF Gibbs functional and minimizes the PWLS by iterative successive over-relaxation algorithm. In these three implementations, a quadratic functional regularization was chosen for the MRF model. Phantom experiments showed a comparable performance of these three PWLS-based methods in terms of suppressing noise-induced streak artifacts and preserving resolution in the reconstructed images. Computer simulations concurred with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS implementation may have the advantage in terms of computation for high-resolution dynamic low-dose CT imaging. PMID:17024831

Bi-cubic interpolation for shift-free pan-sharpening

NASA Astrophysics Data System (ADS)

Aiazzi, Bruno; Baronti, Stefano; Selva, Massimo; Alparone, Luciano

2013-12-01

Most of pan-sharpening techniques require the re-sampling of the multi-spectral (MS) image for matching the size of the panchromatic (Pan) image, before the geometric details of Pan are injected into the MS image. This operation is usually performed in a separable fashion by means of symmetric digital low-pass filtering kernels with odd lengths that utilize piecewise local polynomials, typically implementing linear or cubic interpolation functions. Conversely, constant, i.e. nearest-neighbour, and quadratic kernels, implementing zero and two degree polynomials, respectively, introduce shifts in the magnified images, that are sub-pixel in the case of interpolation by an even factor, as it is the most usual case. However, in standard satellite systems, the point spread functions (PSF) of the MS and Pan instruments are centered in the middle of each pixel. Hence, commercial MS and Pan data products, whose scale ratio is an even number, are relatively shifted by an odd number of half pixels. Filters of even lengths may be exploited to compensate the half-pixel shifts between the MS and Pan sampling grids. In this paper, it is shown that separable polynomial interpolations of odd degrees are feasible with linear-phase kernels of even lengths. The major benefit is that bi-cubic interpolation, which is known to represent the best trade-off between performances and computational complexity, can be applied to commercial MS + Pan datasets, without the need of performing a further half-pixel registration after interpolation, to align the expanded MS with the Pan image.

Limited-angle tomography for analyzer-based phase-contrast X-ray imaging

PubMed Central

Majidi, Keivan; Wernick, Miles N; Li, Jun; Muehleman, Carol; Brankov, Jovan G

2014-01-01

Multiple-Image Radiography (MIR) is an analyzer-based phase-contrast X-ray imaging method (ABI), which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT-MIR only if one considers volumetric images near the central plane and not the whole volume. PMID:24898008

Limited-angle tomography for analyzer-based phase-contrast x-ray imaging

NASA Astrophysics Data System (ADS)

Majidi, Keivan; Wernick, Miles N.; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-07-01

Multiple-image radiography (MIR) is an analyzer-based phase-contrast x-ray imaging method, which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT-MIR only if one considers volumetric images near the central plane and not the whole volume.

Experiences with semiautomatic aerotriangulation on digital photogrammetric stations

NASA Astrophysics Data System (ADS)

Kersten, Thomas P.; Stallmann, Dirk

1995-12-01

With the development of higher-resolution scanners, faster image-handling capabilities, and higher-resolution screens, digital photogrammetric workstations promise to rival conventional analytical plotters in functionality, i.e. in the degree of automation in data capture and processing, and in accuracy. The availability of high quality digital image data and inexpensive high capacity fast mass storage offers the capability to perform accurate semi- automatic or automatic triangulation of digital aerial photo blocks on digital photogrammetric workstations instead of analytical plotters. In this paper, we present our investigations and results on two photogrammetric triangulation blocks, the OEEPE (European Organisation for Experimental Photogrammetric Research) test block (scale 1;4'000) and a Swiss test block (scale 1:12'000) using digitized images. Twenty-eight images of the OEEPE test block were scanned on the Zeiss/Intergraph PS1 and the digital images were delivered with a resolution of 15 micrometer and 30 micrometer, while 20 images of the Swiss test block were scanned on the Desktop Publishing Scanner Agfa Horizon with a resolution of 42 micrometer and on the PS1 with 15 micrometer. Measurements in the digital images were performed on the commercial Digital photogrammetric Station Leica/Helava DPW770 and with basic hard- and software components of the Digital Photogrammetric Station DIPS II, an experimental system of the Institute of Geodesy and Photogrammetry, ETH Zurich. As a reference, the analog images of both photogrammetric test blocks were measured at analytical plotters. On DIPS II measurements of fiducial marks, signalized and natural tie points were performed by least squares template and image matching, while on DPW770 all points were measured by the cross correlation technique. The observations were adjusted in a self-calibrating bundle adjustment. The comparisons between these results and the experiences with the functionality of the commercial and the experimental system are presented.

PDSS/IMC requirements and functional specifications

NASA Technical Reports Server (NTRS)

1983-01-01

The system (software and hardware) requirements for the Payload Development Support System (PDSS)/Image Motion Compensator (IMC) are provided. The PDSS/IMC system provides the capability for performing Image Motion Compensator Electronics (IMCE) flight software test, checkout, and verification and provides the capability for monitoring the IMC flight computer system during qualification testing for fault detection and fault isolation.

Dynamic mapping of brain and cognitive control of virtual gameplay (study by functional magnetic resonance imaging).

PubMed

Rezakova, M V; Mazhirina, K G; Pokrovskiy, M A; Savelov, A A; Savelova, O A; Shtark, M B

2013-04-01

Using functional magnetic resonance imaging technique, we performed online brain mapping of gamers, practiced to voluntary (cognitively) control their heart rate, the parameter that operated a competitive virtual gameplay in the adaptive feedback loop. With the default start picture, the regions of interest during the formation of optimal cognitive strategy were as follows: Brodmann areas 19, 37, 39 and 40, i.e. cerebellar structures (vermis, amygdala, pyramids, clivus). "Localization" concept of the contribution of the cerebellum to cognitive processes is discussed.

Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2015-08-01

Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.

Numerical Analysis of a Flexible Dual Loop Coil and its Experimental Validation for pre-Clinical Magnetic Resonance Imaging of Rodents at 7 T

NASA Astrophysics Data System (ADS)

Solis-Najera, S.; Vazquez, F.; Hernandez, R.; Marrufo, O.; Rodriguez, A. O.

2016-12-01

A surface radio frequency coil was developed for small animal image acquisition in a pre-clinical magnetic resonance imaging system at 7 T. A flexible coil composed of two circular loops was developed to closely cover the object to be imaged. Electromagnetic numerical simulations were performed to evaluate its performance before the coil construction. An analytical expression of the mutual inductance for the two circular loops as a function of the separation between them was derived and used to validate the simulations. The RF coil is composed of two circular loops with a 5 cm external diameter and was tuned to 300 MHz and 50 Ohms matched. The angle between the loops was varied and the Q factor was obtained from the S11 simulations for each angle. B1 homogeneity was also evaluated using the electromagnetic simulations. The coil prototype was designed and built considering the numerical simulation results. To show the feasibility of the coil and its performance, saline-solution phantom images were acquired. A correlation of the simulations and imaging experimental results was conducted showing a concordance of 0.88 for the B1 field. The best coil performance was obtained at the 90° aperture angle. A more realistic phantom was also built using a formaldehyde-fixed rat phantom for ex vivo imaging experiments. All images showed a good image quality revealing clearly defined anatomical details of an ex vivo rat.

Neuroticism related differences in the functional neuroanatomical correlates of multitasking. An fMRI study.

PubMed

Szameitat, Andre J; Saylik, Rahmi; Parton, Andrew

2016-12-02

It is known that neuroticism impairs cognitive performance mostly in difficult tasks, but not so much in easier tasks. One pervasive situation of this type is multitasking, in which the combination of two simple tasks creates a highly demanding dual-task, and consequently high neurotics show higher dual-task costs than low neurotics. However, the functional neuroanatomical correlates of these additional performance impairments in high neurotics are unknown. To test for this, we assessed brain activity by means of functional magnetic resonance imaging (fMRI) in 17 low and 15 high neurotics while they were performing a demanding dual-task and the less demanding component tasks as single-tasks. Behavioural results showed that performance (response times and error rates) was lower in the dual-task than in the single-tasks (dual-task costs), and that these dual-task costs were significantly higher in high neurotics. Imaging data showed that high neurotics showed less dual-task specific activation in lateral (mainly middle frontal gyrus) and medial prefrontal cortices. We conclude that high levels of neuroticism impair behavioural performance in demanding tasks, and that this impairment is accompanied by reduced activation of the task-associated brain areas. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

IMAGEP - A FORTRAN ALGORITHM FOR DIGITAL IMAGE PROCESSING

NASA Technical Reports Server (NTRS)

Roth, D. J.

1994-01-01

IMAGEP is a FORTRAN computer algorithm containing various image processing, analysis, and enhancement functions. It is a keyboard-driven program organized into nine subroutines. Within the subroutines are other routines, also, selected via keyboard. Some of the functions performed by IMAGEP include digitization, storage and retrieval of images; image enhancement by contrast expansion, addition and subtraction, magnification, inversion, and bit shifting; display and movement of cursor; display of grey level histogram of image; and display of the variation of grey level intensity as a function of image position. This algorithm has possible scientific, industrial, and biomedical applications in material flaw studies, steel and ore analysis, and pathology, respectively. IMAGEP is written in VAX FORTRAN for DEC VAX series computers running VMS. The program requires the use of a Grinnell 274 image processor which can be obtained from Mark McCloud Associates, Campbell, CA. An object library of the required GMR series software is included on the distribution media. IMAGEP requires 1Mb of RAM for execution. The standard distribution medium for this program is a 1600 BPI 9track magnetic tape in VAX FILES-11 format. It is also available on a TK50 tape cartridge in VAX FILES-11 format. This program was developed in 1991. DEC, VAX, VMS, and TK50 are trademarks of Digital Equipment Corporation.

A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map

NASA Astrophysics Data System (ADS)

Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad

2016-06-01

In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.

Transthoracic Ultrafast Doppler Imaging of Human Left Ventricular Hemodynamic Function

PubMed Central

Osmanski, Bruno-Félix; Maresca, David; Messas, Emmanuel; Tanter, Mickael; Pernot, Mathieu

2016-01-01

Heart diseases can affect intraventricular blood flow patterns. Real-time imaging of blood flow patterns is challenging because it requires both a high frame rate and a large field of view. To date, standard Doppler techniques can only perform blood flow estimation with high temporal resolution within small regions of interest. In this work, we used ultrafast imaging to map in 2D human left ventricular blood flow patterns during the whole cardiac cycle. Cylindrical waves were transmitted at 4800 Hz with a transthoracic phased array probe to achieve ultrafast Doppler imaging of the left ventricle. The high spatio-temporal sampling of ultrafast imaging permits to rely on a much more effective wall filtering and to increase sensitivity when mapping blood flow patterns during the pre-ejection, ejection, early diastole, diastasis and late diastole phases of the heart cycle. The superior sensitivity and temporal resolution of ultrafast Doppler imaging makes it a promising tool for the noninvasive study of intraventricular hemodynamic function. PMID:25073134

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

Three-Dimensional Unstained Live-Cell Imaging Using Stimulated Parametric Emission Microscopy

NASA Astrophysics Data System (ADS)

Dang, Hieu M.; Kawasumi, Takehito; Omura, Gen; Umano, Toshiyuki; Kajiyama, Shin'ichiro; Ozeki, Yasuyuki; Itoh, Kazuyoshi; Fukui, Kiichi

2009-09-01

The ability to perform high-resolution unstained live imaging is very important to in vivo study of cell structures and functions. Stimulated parametric emission (SPE) microscopy is a nonlinear-optical microscopy based on ultra-fast electronic nonlinear-optical responses. For the first time, we have successfully applied this technique to archive three-dimensional (3D) images of unstained sub-cellular structures, such as, microtubules, nuclei, nucleoli, etc. in live cells. Observation of a complete cell division confirms the ability of SPE microscopy for long time-scale imaging.

Elevated Amygdala Response to Faces following Early Deprivation

ERIC Educational Resources Information Center

Tottenham, N.; Hare, T. A.; Millner, A.; Gilhooly, T.; Zevin, J. D.; Casey, B. J.

2011-01-01

A functional neuroimaging study examined the long-term neural correlates of early adverse rearing conditions in humans as they relate to socio-emotional development. Previously institutionalized (PI) children and a same-aged comparison group were scanned using functional magnetic resonance imaging (fMRI) while performing an Emotional Face Go/Nogo…

Nanoparticle-facilitated functional and molecular imaging for the early detection of cancer

PubMed Central

Sivasubramanian, Maharajan; Hsia, Yu; Lo, Leu-Wei

2014-01-01

Cancer detection in its early stages is imperative for effective cancer treatment and patient survival. In recent years, biomedical imaging techniques, such as magnetic resonance imaging, computed tomography and ultrasound have been greatly developed and have served pivotal roles in clinical cancer management. Molecular imaging (MI) is a non-invasive imaging technique that monitors biological processes at the cellular and sub-cellular levels. To achieve these goals, MI uses targeted imaging agents that can bind targets of interest with high specificity and report on associated abnormalities, a task that cannot be performed by conventional imaging techniques. In this respect, MI holds great promise as a potential therapeutic tool for the early diagnosis of cancer. Nevertheless, the clinical applications of targeted imaging agents are limited due to their inability to overcome biological barriers inside the body. The use of nanoparticles has made it possible to overcome these limitations. Hence, nanoparticles have been the subject of a great deal of recent studies. Therefore, developing nanoparticle-based imaging agents that can target tumors via active or passive targeting mechanisms is desirable. This review focuses on the applications of various functionalized nanoparticle-based imaging agents used in MI for the early detection of cancer. PMID:25988156

MRI compatibility of robot actuation techniques--a comparative study.

PubMed

Fischer, Gregory S; Krieger, Axel; Iordachita, Iulian; Csoma, Csaba; Whitcomb, Louis L; Gabor, Fichtinger

2008-01-01

This paper reports an experimental evaluation of the following three different MRI-compatible actuators: a Shinsei ultrasonic motor a Nanomotion ultrasonic motor and a pneumatic cylinder actuator. We report the results of a study comparing the effect of these actuators on the signal to noise ratio (SNR) of MRJ images under a variety of experimental conditions. Evaluation was performed with the controller inside and outside the scanner room and with both 1.5T and 3T MRI scanners. Pneumatic cylinders function with no loss of SNR with controller both inside and outside of the scanner room. The Nanomotion motor performs with moderate loss of SNR when moving during imaging. The Shinsei is unsuitable for motion during imaging. All may be used when motion is appropriately interleaved with imaging cycles.

The MVM imaging system and its spacecraft interactions. [Mariner Venus/Mercury TV system performance

NASA Technical Reports Server (NTRS)

Vescelus, F. E.

1975-01-01

The present work describes the main considerations and steps taken in determining the functional design of the imaging system of the Mariner Venus/Mercury (MVM) spacecraft and gives examples of some of the interactions between the spacecraft and the imaging instrument during the design and testing phases. Stringent cost and scheduling constraints dictated the use of the previous Mariner 9 dual-camera TV system. The TV parameters laid the groundwork for the imaging definition. Based on the flyby distances from Venus and Mercury and the goal of surface resolution better than 500 meters per sample pair, calculation was performed on focal length, format size, planetary coverage, and data rates. Some problems encountered in initial mechanical operation and as a result of spacecraft drift during the mission are also discussed.

Acousto-optic time- and space-integrating spotlight-mode SAR processor

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.

1993-09-01

The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.

WE-DE-BRA-06: Evaluation of the Imaging Performance of a Novel Water-Equivalent EPID

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

Blake, SJ; The Ingham Institute, Liverpool, NSW; Cheng, J

Purpose: To evaluate the megavoltage imaging performance of a novel, water-equivalent electronic portal imaging device (EPID) developed for simultaneous imaging and dosimetry applications in radiotherapy. Methods: A novel EPID prototype based on active matrix flat panel imager technology has been developed by our group and previously reported to exhibit a water-equivalent dose response. It was constructed by replacing all components above the photodiode detector in a standard clinical EPID (including the copper plate and phosphor screen) with a 15 × 15 cm{sup 2} array of plastic scintillator fibers. Individual fibers measured 0.5 × 0.5 × 30 mm{sup 3}. Spatial resolutionmore » was evaluated experimentally relative to that of a standard EPID with the thin slit technique to measure the modulation transfer function (MTF) for 6 MV x-ray beams. Monte Carlo (MC) EPID models were used to benchmark simulated MTFs against the measurements. The zero spatial frequency detective quantum efficiency (DQE(0)) was simulated for both EPID configurations and a preliminary optimization of the prototype was performed by evaluating DQE(0) as a function of fiber length up to 50 mm. Results: The MC-simulated DQE(0) for the prototype EPID configuration was ∼7 times greater than that of the standard EPID. The prototype’s DQE(0) also increased approximately linearly with fiber length, from ∼1% at 5 mm length to ∼11% at 50 mm length. The standard EPID MTF was greater than the prototype EPID’s for all spatial frequencies, reflecting the trade off between x-ray detection efficiency and spatial resolution with thick scintillators. Conclusion: This study offers promising evidence that a water-equivalent EPID previously demonstrated for radiotherapy dosimetry may also be used for radiotherapy imaging applications. Future studies on optimising the detector design will be performed to develop a next-generation prototype that offers improved megavoltage imaging performance, with the aim to at least match that of current clinical EPIDs. Funding for this project was provided by an Australian Research Council Linkage Project grant (2015) between The University of Sydney, South Western Sydney Local Health District and Perkin-Elmer Pty Ltd.« less

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

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

Gang, G; Stayman, J; Ouadah, S

2015-06-15

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and amore » wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within a patient-specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches. 2R01-CA-112163; R01-EB-017226; U01-EB-018758; Siemens Healthcare (Forcheim, Germany)« less

A method for surface topography measurement using a new focus function based on dual-tree complex wavelet transform

NASA Astrophysics Data System (ADS)

Li, Shimiao; Guo, Tong; Yuan, Lin; Chen, Jinping

2018-01-01

Surface topography measurement is an important tool widely used in many fields to determine the characteristics and functionality of a part or material. Among existing methods for this purpose, the focus variation method has proved high performance particularly in large slope scenarios. However, its performance depends largely on the effectiveness of focus function. This paper presents a method for surface topography measurement using a new focus measurement function based on dual-tree complex wavelet transform. Experiments are conducted on simulated defocused images to prove its high performance in comparison with other traditional approaches. The results showed that the new algorithm has better unimodality and sharpness. The method was also verified by measuring a MEMS micro resonator structure.

Impaired atrioventricular transport in patients with transposition of the great arteries palliated by atrial switch and preserved systolic right ventricular function: A magnetic resonance imaging study.

PubMed

Ladouceur, Magalie; Kachenoura, Nadjia; Soulat, Gilles; Bollache, Emilie; Redheuil, Alban; Azizi, Michel; Delclaux, Christophe; Chatellier, Gilles; Boutouyrie, Pierre; Iserin, Laurence; Bonnet, Damien; Mousseaux, Elie

2017-07-01

We aimed (1) determine if systemic right ventricle filling parameters influence systemic right ventricle stroke volume in adult patients with D-transposition of the great arteries (D-TGA) palliated by atrial switch, using cardiac magnetic resonance imaging and echocardiography, and (2) to study relationship of these diastolic parameters with exercise performance and BNP, in patients with preserved systolic systemic right ventricle function. Single-center, cross-sectional, prospective study. In patients with D-TGA palliated by atrial switch, diastolic dysfunction of the systemic right ventricle may precede systolic dysfunction. Forty-five patients with D-TGA and atrial switch and 45 age and sex-matched healthy subjects underwent cardiac magnetic resonance imaging and echocardiography. Filling flow-rates measured by phase-contrast cardiac magnetic resonance imaging were analyzed using customized software to estimate diastolic parameters and compared with exercise performance. In D-TGA, early filling of systemic right ventricle was impaired with a lower peak filling rate normalized by filling volume (Ef/FV measured by cardiac magnetic resonance imaging) and a higher early filling peak velocity normalized by early peak myocardial velocity (E US /Ea measured by echocardiography) compared with controls (P ≤ .04). Stroke volume of systemic right ventricle showed a direct and significant association with pulmonary venous pathway size (respectively r = 0.50, P < .01). Systemic right atrial area and systemic right ventricle mass/volume index measured by cardiac magnetic resonance imaging, as well as Ef/FV were significantly correlated with exercise performances and BNP (P < .01). All correlations were independent of age, gender, body mass index and blood pressure. Systemic right ventricle pre-load and stroke volume depend mainly on intraatrial pathway function. Moreover, systemic right ventricle remodeling and right atrial dysfunction impair systemic right ventricle filling, leading to BNP increase and exercise limitation. Cardiac magnetic resonance imaging should assess systemic right ventricle filling abnormalities in D-TGA patients. © 2017 Wiley Periodicals, Inc.

[Seeking the aetiology of autistic spectrum disorder. Part 2: Functional neuroimaging].

PubMed

Bryńska, Anita

2012-01-01

Multiple functional imaging techniques help to a better understanding of the neurobiological basis of autism-spectrum disorders (ASD). The early functional imaging studies on ASD focused on task-specific methods related to core symptom domains and explored patterns of activation in response to face processing, theory of mind tasks, language processing and executive function tasks. On the other hand, fMRI research in ASD focused on the development of functional connectivity methods and has provided evidence of alterations in cortical connectivity in ASD and establish autism as a disorder of under-connectivity among the brain regions participating in cortical networks. This atypical functional connectivity in ASD results in inefficiency and poor integration of processing in network connections to achieve task performance. The goal of this review is to summarise the actual neuroimaging functional data and examine their implication for understanding of the neurobiology of ASD.

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.

PubMed

Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

2017-04-06

An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

PubMed Central

Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

2017-01-01

An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods. PMID:28383503

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas.

PubMed

Nguyen, T B; Cron, G O; Perdrizet, K; Bezzina, K; Torres, C H; Chakraborty, S; Woulfe, J; Jansen, G H; Sinclair, J; Thornhill, R E; Foottit, C; Zanette, B; Cameron, I G

2015-11-01

Dynamic contrast-enhanced MR imaging parameters can be biased by poor measurement of the vascular input function. We have compared the diagnostic accuracy of dynamic contrast-enhanced MR imaging by using a phase-derived vascular input function and "bookend" T1 measurements with DSC MR imaging for preoperative grading of astrocytomas. This prospective study included 48 patients with a new pathologic diagnosis of an astrocytoma. Preoperative MR imaging was performed at 3T, which included 2 injections of 5-mL gadobutrol for dynamic contrast-enhanced and DSC MR imaging. During dynamic contrast-enhanced MR imaging, both magnitude and phase images were acquired to estimate plasma volume obtained from phase-derived vascular input function (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function (K(trans)_Φ) as well as plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (K(trans)_SI). From DSC MR imaging, corrected relative CBV was computed. Four ROIs were placed over the solid part of the tumor, and the highest value among the ROIs was recorded. A Mann-Whitney U test was used to test for difference between grades. Diagnostic accuracy was assessed by using receiver operating characteristic analysis. Vp_ Φ and K(trans)_Φ values were lower for grade II compared with grade III astrocytomas (P < .05). Vp_SI and K(trans)_SI were not significantly different between grade II and grade III astrocytomas (P = .08-0.15). Relative CBV and dynamic contrast-enhanced MR imaging parameters except for K(trans)_SI were lower for grade III compared with grade IV (P ≤ .05). In differentiating low- and high-grade astrocytomas, we found no statistically significant difference in diagnostic accuracy between relative CBV and dynamic contrast-enhanced MR imaging parameters. In the preoperative grading of astrocytomas, the diagnostic accuracy of dynamic contrast-enhanced MR imaging parameters is similar to that of relative CBV. © 2015 by American Journal of Neuroradiology.

SU-E-I-43: Pediatric CT Dose and Image Quality Optimization

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

Stevens, G; Singh, R

2014-06-01

Purpose: To design an approach to optimize radiation dose and image quality for pediatric CT imaging, and to evaluate expected performance. Methods: A methodology was designed to quantify relative image quality as a function of CT image acquisition parameters. Image contrast and image noise were used to indicate expected conspicuity of objects, and a wide-cone system was used to minimize scan time for motion avoidance. A decision framework was designed to select acquisition parameters as a weighted combination of image quality and dose. Phantom tests were used to acquire images at multiple techniques to demonstrate expected contrast, noise and dose.more » Anthropomorphic phantoms with contrast inserts were imaged on a 160mm CT system with tube voltage capabilities as low as 70kVp. Previously acquired clinical images were used in conjunction with simulation tools to emulate images at different tube voltages and currents to assess human observer preferences. Results: Examination of image contrast, noise, dose and tube/generator capabilities indicates a clinical task and object-size dependent optimization. Phantom experiments confirm that system modeling can be used to achieve the desired image quality and noise performance. Observer studies indicate that clinical utilization of this optimization requires a modified approach to achieve the desired performance. Conclusion: This work indicates the potential to optimize radiation dose and image quality for pediatric CT imaging. In addition, the methodology can be used in an automated parameter selection feature that can suggest techniques given a limited number of user inputs. G Stevens and R Singh are employees of GE Healthcare.« less

Supervised variational model with statistical inference and its application in medical image segmentation.

PubMed

Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

2015-01-01

Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

Pain-related somatosensory evoked potentials and functional brain magnetic resonance in the evaluation of neurologic recovery after cardiac arrest: a case study of three patients.

PubMed

Zanatta, Paolo; Messerotti Benvenuti, Simone; Baldanzi, Fabrizio; Bendini, Matteo; Saccavini, Marsilio; Tamari, Wadih; Palomba, Daniela; Bosco, Enrico

2012-03-31

This case series investigates whether painful electrical stimulation increases the early prognostic value of both somatosensory-evoked potentials and functional magnetic resonance imaging in comatose patients after cardiac arrest. Three single cases with hypoxic-ischemic encephalopathy were considered. A neurophysiological evaluation with an electroencephalogram and somatosensory-evoked potentials during increased electrical stimulation in both median nerves was performed within five days of cardiac arrest. Each patient also underwent a functional magnetic resonance imaging evaluation with the same neurophysiological protocol one month after cardiac arrest. One patient, who completely recovered, showed a middle latency component at a high intensity of stimulation and the activation of all brain areas involved in cerebral pain processing. One patient in a minimally conscious state only showed the cortical somatosensory response and the activation of the primary somatosensory cortex. The last patient, who was in a vegetative state, did not show primary somatosensory evoked potentials; only the activation of subcortical brain areas occurred. These preliminary findings suggest that the pain-related somatosensory evoked potentials performed to increase the prognosis of comatose patients after cardiac arrest are associated with regional brain activity showed by functional magnetic resonance imaging during median nerves electrical stimulation. More importantly, this cases report also suggests that somatosensory evoked potentials and functional magnetic resonance imaging during painful electrical stimulation may be sensitive and complementary methods to predict the neurological outcome in the acute phase of coma. Thus, pain-related somatosensory-evoked potentials may be a reliable and a cost-effective tool for planning the early diagnostic evaluation of comatose patients.

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Penalized weighted least-squares approach for low-dose x-ray computed tomography

NASA Astrophysics Data System (ADS)

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-03-01

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Karhunen-Loeve (KL) transform can be used to de-correlate the signal among the neighboring views. In each KL component, a penalized weighted least-squares (PWLS) objective function can be constructed and optimal sinogram can be estimated by minimizing the objective function, followed by filtered backprojection (FBP) for CT image reconstruction. In this work, we compared the KL-PWLS method with an iterative image reconstruction algorithm, which uses the Gauss-Seidel iterative calculation to minimize the PWLS objective function in image domain. We also compared the KL-PWLS with an iterative sinogram smoothing algorithm, which uses the iterated conditional mode calculation to minimize the PWLS objective function in sinogram space, followed by FBP for image reconstruction. Phantom experiments show a comparable performance of these three PWLS methods in suppressing the noise-induced artifacts and preserving resolution in reconstructed images. Computer simulation concurs with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS noise reduction may have the advantage in computation for low-dose CT imaging, especially for dynamic high-resolution studies.

Evaluation of DICOM viewer software for workflow integration in clinical trials

NASA Astrophysics Data System (ADS)

Haak, Daniel; Page, Charles E.; Kabino, Klaus; Deserno, Thomas M.

2015-03-01

The digital imaging and communications in medicine (DICOM) protocol is nowadays the leading standard for capture, exchange and storage of image data in medical applications. A broad range of commercial, free, and open source software tools supporting a variety of DICOM functionality exists. However, different from patient's care in hospital, DICOM has not yet arrived in electronic data capture systems (EDCS) for clinical trials. Due to missing integration, even just the visualization of patient's image data in electronic case report forms (eCRFs) is impossible. Four increasing levels for integration of DICOM components into EDCS are conceivable, raising functionality but also demands on interfaces with each level. Hence, in this paper, a comprehensive evaluation of 27 DICOM viewer software projects is performed, investigating viewing functionality as well as interfaces for integration. Concerning general, integration, and viewing requirements the survey involves the criteria (i) license, (ii) support, (iii) platform, (iv) interfaces, (v) two-dimensional (2D) and (vi) three-dimensional (3D) image viewing functionality. Optimal viewers are suggested for applications in clinical trials for 3D imaging, hospital communication, and workflow. Focusing on open source solutions, the viewers ImageJ and MicroView are superior for 3D visualization, whereas GingkoCADx is advantageous for hospital integration. Concerning workflow optimization in multi-centered clinical trials, we suggest the open source viewer Weasis. Covering most use cases, an EDCS and PACS interconnection with Weasis is suggested.

Evaluation of a hyperspectral image database for demosaicking purposes

NASA Astrophysics Data System (ADS)

Larabi, Mohamed-Chaker; Süsstrunk, Sabine

2011-01-01

We present a study on the the applicability of hyperspectral images to evaluate color filter array (CFA) design and the performance of demosaicking algorithms. The aim is to simulate a typical digital still camera processing pipe-line and to compare two different scenarios: evaluate the performance of demosaicking algorithms applied to raw camera RGB values before color rendering to sRGB, and evaluate the performance of demosaicking algorithms applied on the final sRGB color rendered image. The second scenario is the most frequently used one in literature because CFA design and algorithms are usually tested on a set of existing images that are already rendered, such as the Kodak Photo CD set containing the well-known lighthouse image. We simulate the camera processing pipe-line with measured spectral sensitivity functions of a real camera. Modeling a Bayer CFA, we select three linear demosaicking techniques in order to perform the tests. The evaluation is done using CMSE, CPSNR, s-CIELAB and MSSIM metrics to compare demosaicking results. We find that the performance, and especially the difference between demosaicking algorithms, is indeed significant depending if the mosaicking/demosaicking is applied to camera raw values as opposed to already rendered sRGB images. We argue that evaluating the former gives a better indication how a CFA/demosaicking combination will work in practice, and that it is in the interest of the community to create a hyperspectral image dataset dedicated to that effect.

Development of a Hybrid Magnetic Resonance and Ultrasound Imaging System

PubMed Central

Sherwood, Victoria; Rivens, Ian; Collins, David J.; Leach, Martin O.; ter Haar, Gail R.

2014-01-01

A system which allows magnetic resonance (MR) and ultrasound (US) image data to be acquired simultaneously has been developed. B-mode and Doppler US were performed inside the bore of a clinical 1.5 T MRI scanner using a clinical 1–4 MHz US transducer with an 8-metre cable. Susceptibility artefacts and RF noise were introduced into MR images by the US imaging system. RF noise was minimised by using aluminium foil to shield the transducer. A study of MR and B-mode US image signal-to-noise ratio (SNR) as a function of transducer-phantom separation was performed using a gel phantom. This revealed that a 4 cm separation between the phantom surface and the transducer was sufficient to minimise the effect of the susceptibility artefact in MR images. MR-US imaging was demonstrated in vivo with the aid of a 2 mm VeroWhite 3D-printed spherical target placed over the thigh muscle of a rat. The target allowed single-point registration of MR and US images in the axial plane to be performed. The system was subsequently demonstrated as a tool for the targeting and visualisation of high intensity focused ultrasound exposure in the rat thigh muscle. PMID:25177702

Reconstruction of fluorescence molecular tomography with a cosinoidal level set method.

PubMed

Zhang, Xuanxuan; Cao, Xu; Zhu, Shouping

2017-06-27

Implicit shape-based reconstruction method in fluorescence molecular tomography (FMT) is capable of achieving higher image clarity than image-based reconstruction method. However, the implicit shape method suffers from a low convergence speed and performs unstably due to the utilization of gradient-based optimization methods. Moreover, the implicit shape method requires priori information about the number of targets. A shape-based reconstruction scheme of FMT with a cosinoidal level set method is proposed in this paper. The Heaviside function in the classical implicit shape method is replaced with a cosine function, and then the reconstruction can be accomplished with the Levenberg-Marquardt method rather than gradient-based methods. As a result, the priori information about the number of targets is not required anymore and the choice of step length is avoided. Numerical simulations and phantom experiments were carried out to validate the proposed method. Results of the proposed method show higher contrast to noise ratios and Pearson correlations than the implicit shape method and image-based reconstruction method. Moreover, the number of iterations required in the proposed method is much less than the implicit shape method. The proposed method performs more stably, provides a faster convergence speed than the implicit shape method, and achieves higher image clarity than the image-based reconstruction method.

A general framework for regularized, similarity-based image restoration.

PubMed

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

Fluorinated colloidal gold immunolabels for imaging select proteins in parallel with lipids using high-resolution secondary ion mass spectrometry

PubMed Central

Wilson, Robert L.; Frisz, Jessica F.; Hanafin, William P.; Carpenter, Kevin J.; Hutcheon, Ian D.; Weber, Peter K.; Kraft, Mary L.

2014-01-01

The local abundance of specific lipid species near a membrane protein is hypothesized to influence the protein’s activity. The ability to simultaneously image the distributions of specific protein and lipid species in the cell membrane would facilitate testing these hypotheses. Recent advances in imaging the distribution of cell membrane lipids with mass spectrometry have created the desire for membrane protein probes that can be simultaneously imaged with isotope labeled lipids. Such probes would enable conclusive tests of whether specific proteins co-localize with particular lipid species. Here, we describe the development of fluorine-functionalized colloidal gold immunolabels that facilitate the detection and imaging of specific proteins in parallel with lipids in the plasma membrane using high-resolution SIMS performed with a NanoSIMS. First, we developed a method to functionalize colloidal gold nanoparticles with a partially fluorinated mixed monolayer that permitted NanoSIMS detection and rendered the functionalized nanoparticles dispersible in aqueous buffer. Then, to allow for selective protein labeling, we attached the fluorinated colloidal gold nanoparticles to the nonbinding portion of antibodies. By combining these functionalized immunolabels with metabolic incorporation of stable isotopes, we demonstrate that influenza hemagglutinin and cellular lipids can be imaged in parallel using NanoSIMS. These labels enable a general approach to simultaneously imaging specific proteins and lipids with high sensitivity and lateral resolution, which may be used to evaluate predictions of protein co-localization with specific lipid species. PMID:22284327

Large-field-of-view, modular, stabilized, adaptive-optics-based scanning laser ophthalmoscope.

PubMed

Burns, Stephen A; Tumbar, Remy; Elsner, Ann E; Ferguson, Daniel; Hammer, Daniel X

2007-05-01

We describe the design and performance of an adaptive optics retinal imager that is optimized for use during dynamic correction for eye movements. The system incorporates a retinal tracker and stabilizer, a wide-field line scan scanning laser ophthalmoscope (SLO), and a high-resolution microelectromechanical-systems-based adaptive optics SLO. The detection system incorporates selection and positioning of confocal apertures, allowing measurement of images arising from different portions of the double pass retinal point-spread function (psf). System performance was excellent. The adaptive optics increased the brightness and contrast for small confocal apertures by more than 2x and decreased the brightness of images obtained with displaced apertures, confirming the ability of the adaptive optics system to improve the psf. The retinal image was stabilized to within 18 microm 90% of the time. Stabilization was sufficient for cross-correlation techniques to automatically align the images.

Kinesthetic alexia due to left parietal lobe lesions.

PubMed

Ihori, Nami; Kawamura, Mitsuru; Araki, Shigeo; Kawachi, Juro

2002-01-01

To investigate the neuropsychological mechanisms of kinesthetic alexia, we asked 7 patients who showed kinesthetic alexia with preserved visual reading after damage to the left parietal region to perform tasks consisting of kinesthetic written reproduction (writing down the same letter as the kinesthetic stimulus), kinesthetic reading aloud, visual written reproduction (copying letters), and visual reading aloud of hiragana (Japanese phonograms). We compared the performance in these tasks and the lesion sites in each patient. The results suggested that deficits in any one of the following functions might cause kinesthetic alexia: (1) the retrieval of kinesthetic images (motor engrams) of characters from kinesthetic stimuli, (2) kinesthetic images themselves, (3) access to cross-modal association from kinesthetic images, and (4) cross-modal association itself (retrieval of auditory and visual images from kinesthetic images of characters). Each of these factors seemed to be related to different lesion sites in the left parietal lobe. Copyright 2002 S. Karger AG, Basel

White matter structural connectivity is associated with sensorimotor function in stroke survivors☆

PubMed Central

Kalinosky, Benjamin T.; Schindler-Ivens, Sheila; Schmit, Brian D.

2013-01-01

Purpose Diffusion tensor imaging (DTI) provides functionally relevant information about white matter structure. Local anatomical connectivity information combined with fractional anisotropy (FA) and mean diffusivity (MD) may predict functional outcomes in stroke survivors. Imaging methods for predicting functional outcomes in stroke survivors are not well established. This work uses DTI to objectively assess the effects of a stroke lesion on white matter structure and sensorimotor function. Methods A voxel-based approach is introduced to assess a stroke lesion's global impact on motor function. Anatomical T1-weighted and diffusion tensor images of the brain were acquired for nineteen subjects (10 post-stroke and 9 age-matched controls). A manually selected volume of interest was used to alleviate the effects of stroke lesions on image registration. Images from all subjects were registered to the images of the control subject that was anatomically closest to Talairach space. Each subject's transformed image was uniformly seeded for DTI tractography. Each seed was inversely transformed into the individual subject space, where DTI tractography was conducted and then the results were transformed back to the reference space. A voxel-wise connectivity matrix was constructed from the fibers, which was then used to calculate the number of directly and indirectly connected neighbors of each voxel. A novel voxel-wise indirect structural connectivity (VISC) index was computed as the average number of direct connections to a voxel's indirect neighbors. Voxel-based analyses (VBA) were performed to compare VISC, FA, and MD for the detection of lesion-induced changes in sensorimotor function. For each voxel, a t-value was computed from the differences between each stroke brain and the 9 controls. A series of linear regressions was performed between Fugl-Meyer (FM) assessment scores of sensorimotor impairment and each DTI metric's log number of voxels that differed from the control group. Results Correlation between the logarithm of the number of significant voxels in the ipsilesional hemisphere and total Fugl-Meyer score was moderate for MD (R2 = 0.512), and greater for VISC (R2 = 0.796) and FA (R2 = 0.674). The slopes of FA (p = 0.0036), VISC (p = 0.0005), and MD (p = 0.0199) versus the total FM score were significant. However, these correlations were driven by the upper extremity motor component of the FM score (VISC: R2 = 0.879) with little influence of the lower extremity motor component (FA: R2 = 0.177). Conclusion The results suggest that a voxel-wise metric based on DTI tractography can predict upper extremity sensorimotor function of stroke survivors, and that supraspinal intraconnectivity may have a less dominant role in lower extremity function. PMID:24179827

A smartphone-based chip-scale microscope using ambient illumination.

PubMed

Lee, Seung Ah; Yang, Changhuei

2014-08-21

Portable chip-scale microscopy devices can potentially address various imaging needs in mobile healthcare and environmental monitoring. Here, we demonstrate the adaptation of a smartphone's camera to function as a compact lensless microscope. Unlike other chip-scale microscopy schemes, this method uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is based on the shadow imaging technique where the sample is placed on the surface of the image sensor, which captures direct shadow images under illumination. To improve the image resolution beyond the pixel size, we perform pixel super-resolution reconstruction with multiple images at different angles of illumination, which are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. The lensless imaging scheme allows for sub-micron resolution imaging over an ultra-wide field-of-view (FOV). Image acquisition and reconstruction are performed on the device using a custom-built Android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system.

A smartphone-based chip-scale microscope using ambient illumination

PubMed Central

Lee, Seung Ah; Yang, Changhuei

2014-01-01

Portable chip-scale microscopy devices can potentially address various imaging needs in mobile healthcare and environmental monitoring. Here, we demonstrate the adaptation of a smartphone’s camera to function as a compact lensless microscope. Unlike other chip-scale microscopy schemes, this method uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is based on the shadow imaging technique where the sample is placed on the surface of the image sensor, which captures direct shadow images under illumination. To improve the imaging resolution beyond the pixel size, we perform pixel super-resolution reconstruction with multiple images at different angles of illumination, which are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. The lensless imaging scheme allows for sub-micron resolution imaging over an ultra-wide field-of-view (FOV). Image acquisition and reconstruction is performed on the device using a custom-built android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system. PMID:24964209

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

Time-frequency analysis of functional optical mammographic images

NASA Astrophysics Data System (ADS)

Barbour, Randall L.; Graber, Harry L.; Schmitz, Christoph H.; Tarantini, Frank; Khoury, Georges; Naar, David J.; Panetta, Thomas F.; Lewis, Theophilus; Pei, Yaling

2003-07-01

We have introduced working technology that provides for time-series imaging of the hemoglobin signal in large tissue structures. In this study we have explored our ability to detect aberrant time-frequency responses of breast vasculature for subjects with Stage II breast cancer at rest and in response to simple provocations. The hypothesis being explored is that time-series imaging will be sensitive to the known structural and functional malformations of the tumor vasculature. Mammographic studies were conducted using an adjustable hemisheric measuring head containing 21 source and 21 detector locations (441 source-detector pairs). Simultaneous dual-wavelength studies were performed at 760 and 830 nm at a framing rate of ~2.7 Hz. Optical measures were performed on women lying prone with the breast hanging in a pendant position. Two class of measures were performed: (1) 20- minute baseline measure wherein the subject was at rest; (2) provocation studies wherein the subject was asked to perform some simple breathing maneuvers. Collected data were analyzed to identify the time-frequency structure and central tendencies of the detector responses and those of the image time series. Imaging data were generated using the Normalized Difference Method (Pei et al., Appl. Opt. 40, 5755-5769, 2001). Results obtained clearly document three classes of anomalies when compared to the normal contralateral breast. 1) Breast tumors exhibit altered oxygen supply/demand imbalance in response to an oxidative challenge (breath hold). 2) The vasomotor response of the tumor vasculature is mainly depressed and exhibits an altered modulation. 3) The affected area of the breast wherein the altered vasomotor signature is seen extends well beyond the limits of the tumor itself.

Brain imaging and cognition in young narcoleptic patients.

PubMed

Huang, Yu-Shu; Liu, Feng-Yuan; Lin, Chin-Yang; Hsiao, Ing-Tsung; Guilleminault, Christian

2016-08-01

The relationship between functional brain images and performances in narcoleptic patients and controls is a new field of investigation. We studied 71 young, type 1 narcoleptic patients and 20 sex- and age-matched control individuals using brain positron emission tomography (PET) images and neurocognitive testing. Clinical investigation was carried out using sleep-wake evaluation questionnaires; a sleep-wake study was conducted with actigraphy, polysomnography, multiple sleep latency test (MSLT), and blood tests (with human leukocyte antigen typing). The continuous performance test (CPT) and Wisconsin card sorting test (WCST) were administered on the same day as the PET study. PET data were analyzed using Statistical Parametric Mapping (version 8) software. Correlation of brain imaging and neurocognitive function was performed by Pearson's correlation. Statistical analyses (Student's t-test) were conducted with SPSS version-18. Seventy-one narcoleptic patients (mean age: 16.15 years, 41 boys (57.7%)) and 20 controls (mean age: 15.1 years, 12 boys (60%)) were studied. Results from the CPT and WCST showed significantly worse scores in narcoleptic patients than in controls (P < 0.05). Compared to controls, narcoleptic patients presented with hypometabolism in the right mid-frontal lobe and angular gyrus (P < 0.05) and significant hypermetabolism in the olfactory lobe, hippocampus, parahippocampus, amygdala, fusiform, left inferior parietal lobe, left superior temporal lobe, striatum, basal ganglia and thalamus, right hypothalamus, and pons (P < 0.05) in the PET study. Changes in brain metabolic activity in narcoleptic patients were positively correlated with results from the sleepiness scales and performance tests. Young, type 1 narcoleptic patients face a continuous cognitive handicap. Our imaging cognitive test protocol can be useful for investigating the effects of treatment trials in these patients. Copyright © 2016 Elsevier B.V. All rights reserved.

SPARX, a new environment for Cryo-EM image processing.

PubMed

Hohn, Michael; Tang, Grant; Goodyear, Grant; Baldwin, P R; Huang, Zhong; Penczek, Pawel A; Yang, Chao; Glaeser, Robert M; Adams, Paul D; Ludtke, Steven J

2007-01-01

SPARX (single particle analysis for resolution extension) is a new image processing environment with a particular emphasis on transmission electron microscopy (TEM) structure determination. It includes a graphical user interface that provides a complete graphical programming environment with a novel data/process-flow infrastructure, an extensive library of Python scripts that perform specific TEM-related computational tasks, and a core library of fundamental C++ image processing functions. In addition, SPARX relies on the EMAN2 library and cctbx, the open-source computational crystallography library from PHENIX. The design of the system is such that future inclusion of other image processing libraries is a straightforward task. The SPARX infrastructure intelligently handles retention of intermediate values, even those inside programming structures such as loops and function calls. SPARX and all dependencies are free for academic use and available with complete source.

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

NASA Astrophysics Data System (ADS)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease.

PubMed

Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B

2016-01-01

Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

Fast globally optimal segmentation of cells in fluorescence microscopy images.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2011-01-01

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Performance of SEM scintillation detector evaluated by modulation transfer function and detective quantum efficiency function.

PubMed

Bok, Jan; Schauer, Petr

2014-01-01

In the paper, the SEM detector is evaluated by the modulation transfer function (MTF) which expresses the detector's influence on the SEM image contrast. This is a novel approach, since the MTF was used previously to describe only the area imaging detectors, or whole imaging systems. The measurement technique and calculation of the MTF for the SEM detector are presented. In addition, the measurement and calculation of the detective quantum efficiency (DQE) as a function of the spatial frequency for the SEM detector are described. In this technique, the time modulated e-beam is used in order to create well-defined input signal for the detector. The MTF and DQE measurements are demonstrated on the Everhart-Thornley scintillation detector. This detector was alternated using the YAG:Ce, YAP:Ce, and CRY18 single-crystal scintillators. The presented MTF and DQE characteristics show good imaging properties of the detectors with the YAP:Ce or CRY18 scintillator, especially for a specific type of the e-beam scan. The results demonstrate the great benefit of the description of SEM detectors using the MTF and DQE. In addition, point-by-point and continual-sweep e-beam scans in SEM were discussed and their influence on the image quality was revealed using the MTF. © 2013 Wiley Periodicals, Inc.

Metric for evaluation of filter efficiency in spectral cameras.

PubMed

Nahavandi, Alireza Mahmoudi; Tehran, Mohammad Amani

2016-11-10

Although metric functions that show the performance of a colorimetric imaging device have been investigated, a metric for performance analysis of a set of filters in wideband filter-based spectral cameras has rarely been studied. Based on a generalization of Vora's Measure of Goodness (MOG) and the spanning theorem, a single function metric that estimates the effectiveness of a filter set is introduced. The improved metric, named MMOG, varies between one, for a perfect, and zero, for the worst possible set of filters. Results showed that MMOG exhibits a trend that is more similar to the mean square of spectral reflectance reconstruction errors than does Vora's MOG index, and it is robust to noise in the imaging system. MMOG as a single metric could be exploited for further analysis of manufacturing errors.

Effects of aging on perception of motion

NASA Astrophysics Data System (ADS)

Kaur, Manpreet; Wilder, Joseph; Hung, George; Julesz, Bela

1997-09-01

Driving requires two basic visual components: 'visual sensory function' and 'higher order skills.' Among the elderly, it has been observed that when attention must be divided in the presence of multiple objects, their attentional skills and relational processes, along with impairment of basic visual sensory function, are markedly impaired. A high frame rate imaging system was developed to assess the elderly driver's ability to locate and distinguish computer generated images of vehicles and to determine their direction of motion in a simulated intersection. Preliminary experiments were performed at varying target speeds and angular displacements to study the effect of these parameters on motion perception. Results for subjects in four different age groups, ranging from mid- twenties to mid-sixties, show significantly better performance for the younger subjects as compared to the older ones.