Optimising μCT imaging of the middle and inner cat ear.

PubMed

Seifert, H; Röher, U; Staszyk, C; Angrisani, N; Dziuba, D; Meyer-Lindenberg, A

2012-04-01

This study's aim was to determine the optimal scan parameters for imaging the middle and inner ear of the cat with micro-computertomography (μCT). Besides, the study set out to assess whether adequate image quality can be obtained to use μCT in diagnostics and research on cat ears. For optimisation, μCT imaging of two cat skull preparations was performed using 36 different scanning protocols. The μCT-scans were evaluated by four experienced experts with regard to the image quality and detail detectability. By compiling a ranking of the results, the best possible scan parameters could be determined. From a third cat's skull, a μCT-scan, using these optimised scan parameters, and a comparative clinical CT-scan were acquired. Afterwards, histological specimens of the ears were produced which were compared to the μCT-images. The comparison shows that the osseous structures are depicted in detail. Although soft tissues cannot be differentiated, the osseous structures serve as valuable spatial orientation of relevant nerves and muscles. Clinical CT can depict many anatomical structures which can also be seen on μCT-images, but these appear a lot less sharp and also less detailed than with μCT. © 2011 Blackwell Verlag GmbH.

Updated MDRIZTAB Parameters for ACS/WFC

NASA Astrophysics Data System (ADS)

Hoffman, S. L.; Avila, R. J.

2017-03-01

The Mikulski Archive for Space Telescopes (MAST) pipeline performs geometric distortion corrections, associated image combinations, and cosmic ray rejections with AstroDrizzle. The MDRIZTAB reference table contains a list of relevant parameters that controls this program. This document details our photometric analysis of Advanced Camera for Surveys Wide Field Channel (ACS/WFC) data processed by AstroDrizzle. Based on this analysis, we update the MDRIZTAB table to improve the quality of the drizzled products delivered by MAST.

Spatiotemporal Imaging of Magnetization Dynamics at the Nanoscale: Breaking the Diffraction Limit

DTIC Science & Technology

2016-03-09

modulations frequency. In the future under our new AFOSR contract, we plan to fabricate a new generation of devices with appropriate impedance match to a...quantitatively extract relevant thermal parameters from our experiment including the temperature change and the magnto- thermoelectric coefficient. Response

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

From plastic to gold: a unified classification scheme for reference standards in medical image processing

NASA Astrophysics Data System (ADS)

Lehmann, Thomas M.

2002-05-01

Reliable evaluation of medical image processing is of major importance for routine applications. Nonetheless, evaluation is often omitted or methodically defective when novel approaches or algorithms are introduced. Adopted from medical diagnosis, we define the following criteria to classify reference standards: 1. Reliance, if the generation or capturing of test images for evaluation follows an exactly determined and reproducible protocol. 2. Equivalence, if the image material or relationships considered within an algorithmic reference standard equal real-life data with respect to structure, noise, or other parameters of importance. 3. Independence, if any reference standard relies on a different procedure than that to be evaluated, or on other images or image modalities than that used routinely. This criterion bans the simultaneous use of one image for both, training and test phase. 4. Relevance, if the algorithm to be evaluated is self-reproducible. If random parameters or optimization strategies are applied, reliability of the algorithm must be shown before the reference standard is applied for evaluation. 5. Significance, if the number of reference standard images that are used for evaluation is sufficient large to enable statistically founded analysis. We demand that a true gold standard must satisfy the Criteria 1 to 3. Any standard only satisfying two criteria, i.e., Criterion 1 and Criterion 2 or Criterion 1 and Criterion 3, is referred to as silver standard. Other standards are termed to be from plastic. Before exhaustive evaluation based on gold or silver standards is performed, its relevance must be shown (Criterion 4) and sufficient tests must be carried out to found statistical analysis (Criterion 5). In this paper, examples are given for each class of reference standards.

SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

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

Zhao, T; Ruan, D

Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject tomore » random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be correlated with the performance of relevant atlas selection and ultimate label fusion.« less

Registering parameters and granules of wave observations: IMAGE RPI success story

NASA Astrophysics Data System (ADS)

Galkin, I. A.; Charisi, A.; Fung, S. F.; Benson, R. F.; Reinisch, B. W.

2015-12-01

Modern metadata systems strive to help scientists locate data relevant to their research and then retrieve them quickly. Success of this mission depends on the organization and completeness of metadata. Each relevant data resource has to be registered; each content has to be described; each data file has to be accessible. Ultimately, data discoverability is about the practical ability to describe data content and location. Correspondingly, data registration has a "Parameter" level, at which content is specified by listing available observed properties (parameters), and a "Granule" level, at which download links are given to data records (granules). Until recently, both parameter- and granule-level data registrations were accomplished at NASA Virtual System Observatory easily by listing provided parameters and building Granule documents with URLs to the datafile locations, usually those at NASA CDAWeb data warehouse. With the introduction of the Virtual Wave Observatory (VWO), however, the parameter/granule concept faced a scalability challenge. The wave phenomenon content is rich with descriptors of the wave generation, propagation, interaction with propagation media, and observation processes. Additionally, the wave phenomenon content varies from record to record, reflecting changes in the constituent processes, making it necessary to generate granule documents at sub-minute resolution. We will present the first success story of registering 234,178 records of IMAGE Radio Plasma Imager (RPI) plasmagram data and Level 2 derived data products in ESPAS (near-Earth Space Data Infrastructure for e-Science), using the VWO-inspired wave ontology. The granules are arranged in overlapping display and numerical data collections. Display data include (a) auto-prospected plasmagrams of potential interest, (b) interesting plasmagrams annotated by human analysts or software, and (c) spectacular plasmagrams annotated by analysts as publication-quality examples of the RPI science. Numerical data products include plasmagram-derived records containing signatures of local and remote signal propagation, as well as field-aligned profiles of electron density in the plasmasphere. Registered granules of RPI observations are available in ESPAS for their content-targeted search and retrieval.

Functionality and operation of fluoroscopic automatic brightness control/automatic dose rate control logic in modern cardiovascular and interventional angiography systems: A Report of Task Group 125 Radiography/Fluoroscopy Subcommittee, Imaging Physics Committee, Science Council

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

Rauch, Phillip; Lin, Pei-Jan Paul; Balter, Stephen

2012-05-15

Task Group 125 (TG 125) was charged with investigating the functionality of fluoroscopic automatic dose rate and image quality control logic in modern angiographic systems, paying specific attention to the spectral shaping filters and variations in the selected radiologic imaging parameters. The task group was also charged with describing the operational aspects of the imaging equipment for the purpose of assisting the clinical medical physicist with clinical set-up and performance evaluation. Although there are clear distinctions between the fluoroscopic operation of an angiographic system and its acquisition modes (digital cine, digital angiography, digital subtraction angiography, etc.), the scope of thismore » work was limited to the fluoroscopic operation of the systems studied. The use of spectral shaping filters in cardiovascular and interventional angiography equipment has been shown to reduce patient dose. If the imaging control algorithm were programmed to work in conjunction with the selected spectral filter, and if the generator parameters were optimized for the selected filter, then image quality could also be improved. Although assessment of image quality was not included as part of this report, it was recognized that for fluoroscopic imaging the parameters that influence radiation output, differential absorption, and patient dose are also the same parameters that influence image quality. Therefore, this report will utilize the terminology ''automatic dose rate and image quality'' (ADRIQ) when describing the control logic in modern interventional angiographic systems and, where relevant, will describe the influence of controlled parameters on the subsequent image quality. A total of 22 angiography units were investigated by the task group and of these one each was chosen as representative of the equipment manufactured by GE Healthcare, Philips Medical Systems, Shimadzu Medical USA, and Siemens Medical Systems. All equipment, for which measurement data were included in this report, was manufactured within the three year period from 2006 to 2008. Using polymethylmethacrylate (PMMA) plastic to simulate patient attenuation, each angiographic imaging system was evaluated by recording the following parameters: tube potential in units of kilovolts peak (kVp), tube current in units of milliamperes (mA), pulse width (PW) in units of milliseconds (ms), spectral filtration setting, and patient air kerma rate (PAKR) as a function of the attenuator thickness. Data were graphically plotted to reveal the manner in which the ADRIQ control logic responded to changes in object attenuation. There were similarities in the manner in which the ADRIQ control logic operated that allowed the four chosen devices to be divided into two groups, with two of the systems in each group. There were also unique approaches to the ADRIQ control logic that were associated with some of the systems, and these are described in the report. The evaluation revealed relevant information about the testing procedure and also about the manner in which different manufacturers approach the utilization of spectral filtration, pulsed fluoroscopy, and maximum PAKR limitation. This information should be particularly valuable to the clinical medical physicist charged with acceptance testing and performance evaluation of modern angiographic systems.« less

Functionality and operation of fluoroscopic automatic brightness control/automatic dose rate control logic in modern cardiovascular and interventional angiography systems: a report of Task Group 125 Radiography/Fluoroscopy Subcommittee, Imaging Physics Committee, Science Council.

PubMed

Rauch, Phillip; Lin, Pei-Jan Paul; Balter, Stephen; Fukuda, Atsushi; Goode, Allen; Hartwell, Gary; LaFrance, Terry; Nickoloff, Edward; Shepard, Jeff; Strauss, Keith

2012-05-01

Task Group 125 (TG 125) was charged with investigating the functionality of fluoroscopic automatic dose rate and image quality control logic in modern angiographic systems, paying specific attention to the spectral shaping filters and variations in the selected radiologic imaging parameters. The task group was also charged with describing the operational aspects of the imaging equipment for the purpose of assisting the clinical medical physicist with clinical set-up and performance evaluation. Although there are clear distinctions between the fluoroscopic operation of an angiographic system and its acquisition modes (digital cine, digital angiography, digital subtraction angiography, etc.), the scope of this work was limited to the fluoroscopic operation of the systems studied. The use of spectral shaping filters in cardiovascular and interventional angiography equipment has been shown to reduce patient dose. If the imaging control algorithm were programmed to work in conjunction with the selected spectral filter, and if the generator parameters were optimized for the selected filter, then image quality could also be improved. Although assessment of image quality was not included as part of this report, it was recognized that for fluoroscopic imaging the parameters that influence radiation output, differential absorption, and patient dose are also the same parameters that influence image quality. Therefore, this report will utilize the terminology "automatic dose rate and image quality" (ADRIQ) when describing the control logic in modern interventional angiographic systems and, where relevant, will describe the influence of controlled parameters on the subsequent image quality. A total of 22 angiography units were investigated by the task group and of these one each was chosen as representative of the equipment manufactured by GE Healthcare, Philips Medical Systems, Shimadzu Medical USA, and Siemens Medical Systems. All equipment, for which measurement data were included in this report, was manufactured within the three year period from 2006 to 2008. Using polymethylmethacrylate (PMMA) plastic to simulate patient attenuation, each angiographic imaging system was evaluated by recording the following parameters: tube potential in units of kilovolts peak (kVp), tube current in units of milliamperes (mA), pulse width (PW) in units of milliseconds (ms), spectral filtration setting, and patient air kerma rate (PAKR) as a function of the attenuator thickness. Data were graphically plotted to reveal the manner in which the ADRIQ control logic responded to changes in object attenuation. There were similarities in the manner in which the ADRIQ control logic operated that allowed the four chosen devices to be divided into two groups, with two of the systems in each group. There were also unique approaches to the ADRIQ control logic that were associated with some of the systems, and these are described in the report. The evaluation revealed relevant information about the testing procedure and also about the manner in which different manufacturers approach the utilization of spectral filtration, pulsed fluoroscopy, and maximum PAKR limitation. This information should be particularly valuable to the clinical medical physicist charged with acceptance testing and performance evaluation of modern angiographic systems.

Effect of low-dose CT and iterative reconstruction on trabecular bone microstructure assessment

NASA Astrophysics Data System (ADS)

Kopp, Felix K.; Baum, Thomas; Nasirudin, Radin A.; Mei, Kai; Garcia, Eduardo G.; Burgkart, Rainer; Rummeny, Ernst J.; Bauer, Jan S.; Noël, Peter B.

2016-03-01

The trabecular bone microstructure is an important factor in the development of osteoporosis. It is well known that its deterioration is one effect when osteoporosis occurs. Previous research showed that the analysis of trabecular bone microstructure enables more precise diagnoses of osteoporosis compared to a sole measurement of the mineral density. Microstructure parameters are assessed on volumetric images of the bone acquired either with high-resolution magnetic resonance imaging, high-resolution peripheral quantitative computed tomography or high-resolution computed tomography (CT), with only CT being applicable to the spine, which is one of clinically most relevant fracture sites. However, due to the high radiation exposure for imaging the whole spine these measurements are not applicable in current clinical routine. In this work, twelve vertebrae from three different donors were scanned with standard and low radiation dose. Trabecular bone microstructure parameters were assessed for CT images reconstructed with statistical iterative reconstruction (SIR) and analytical filtered backprojection (FBP). The resulting structure parameters were correlated to the biomechanically determined fracture load of each vertebra. Microstructure parameters assessed for low-dose data reconstructed with SIR significantly correlated with fracture loads as well as parameters assessed for standard-dose data reconstructed with FBP. Ideal results were achieved with low to zero regularization strength yielding microstructure parameters not significantly different from those assessed for standard-dose FPB data. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

Smart Contrast Agents for Magnetic Resonance Imaging.

PubMed

Bonnet, Célia S; Tóth, Éva

2016-01-01

By visualizing bioactive molecules or biological parameters in vivo, molecular imaging is searching for information at the molecular level in living organisms. In addition to contributing to earlier and more personalized diagnosis in medicine, it also helps understand and rationalize the molecular factors underlying physiological and pathological processes. In magnetic resonance imaging (MRI), complexes of paramagnetic metal ions, mostly lanthanides, are commonly used to enhance the intrinsic image contrast. They rely either on the relaxation effect of these metal chelates (T(1) agents), or on the phenomenon of paramagnetic chemical exchange saturation transfer (PARACEST agents). In both cases, responsive molecular magnetic resonance imaging probes can be designed to report on various biomarkers of biological interest. In this context, we review recent work in the literature and from our group on responsive T(1) and PARACEST MRI agents for the detection of biogenic metal ions (such as calcium or zinc), enzymatic activities, or neurotransmitter release. These examples illustrate the general strategies that can be applied to create molecular imaging agents with an MRI detectable response to biologically relevant parameters.

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

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

Szczykutowicz, T; Rubert, N; Ranallo, F

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specificmore » anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.« less

Improving Image Drizzling in the HST Archive: Advanced Camera for Surveys

NASA Astrophysics Data System (ADS)

Hoffmann, Samantha L.; Avila, Roberto J.

2017-06-01

The Mikulski Archive for Space Telescopes (MAST) pipeline performs geometric distortion corrections, associated image combinations, and cosmic ray rejections with AstroDrizzle on Hubble Space Telescope (HST) data. The MDRIZTAB reference table contains a list of relevant parameters that controls this program. This document details our photometric analysis of Advanced Camera for Surveys Wide Field Channel (ACS/WFC) data processed by AstroDrizzle. Based on this analysis, we update the MDRIZTAB table to improve the quality of the drizzled products delivered by MAST.

Rapid Confined Mixing with Transverse Jets Part 1: Single Jet

NASA Astrophysics Data System (ADS)

Salazar, David; Forliti, David

2012-11-01

Transverse jets have been studied extensively due to their relevance and efficiency in fluid mixing applications. Gas turbine burners, film cooling, and chemical reactors are some examples of rapid transverse jet mixing. Motivated by a lack of universal scaling laws for confined and unconfined transverse jets, a newly developed momentum transfer parameter was found to improve correlation of literature data. Jet column drag and entrainment arguments for momentum transfer are made to derive the parameter. A liquid-phase mixing study was conducted to investigate confined mixing for a low number of jets. Planar laser induced fluorescence was implemented to measure mixture fraction for a single confined transverse jet. Time-averaged cross-sectional images were taken with a light sheet located three diameters downstream of transverse injection. A mixture of water and sodium fluorescein was used to distinguish jet fluid from main flow fluid for the test section images. Image data suggest regimes for under- and overpenetration of jet fluid into the main flow. The scaling parameter is found to correlate optimum unmixedness for multiple diameter ratios at a parameter value of 0.75. Distribution A: Public Release, Public Affairs Clearance Number: 12655.

Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis

PubMed Central

Ghanian, Zahra; Staniszewski, Kevin; Jamali, Nasim; Sepehr, Reyhaneh; Wang, Shoujian; Sorenson, Christine M.; Sheibani, Nader; Ranji, Mahsa

2016-01-01

A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. PMID:27186534

[Computer simulation of a clinical magnet resonance tomography scanner for training purposes].

PubMed

Hackländer, T; Mertens, H; Cramer, B M

2004-08-01

The idea for this project was born by the necessity to offer medical students an easy approach to the theoretical basics of magnetic resonance imaging. The aim was to simulate the features and functions of such a scanner on a commercially available computer by means of a computer program. The simulation was programmed in pure Java under the GNU General Public License and is freely available for a commercially available computer with Windows, Macintosh or Linux operating system. The graphic user interface is oriented to a real scanner. In an external program parameter, images for the proton density and the relaxation times T1 and T2 are calculated on the basis of clinical examinations. From this, the image calculation is carried out in the simulation program pixel by pixel on the basis of a pulse sequence chosen and modified by the user. The images can be stored and printed. In addition, it is possible to display and modify k-space images. Seven classes of pulse sequences are implemented and up to 14 relevant sequence parameters, such as repetition time and echo time, can be altered. Aliasing and motion artifacts can be simulated. As the image calculation only takes a few seconds, interactive working is possible. The simulation has been used in the university education for more than 1 year, successfully illustrating the dependence of the MR images on the measuring parameters. This should facititate the approach of students to the understanding MR imaging in the future.

[Improvement of the microcinematography technic for the study of cell cycles].

PubMed

Gueulette, J; Beauduin, M; Grégoire, V; Van Dorpe, J C; Wambersie, A

1984-10-01

An improvement of time-lapse microcinematography technique is described. It consists in directly printing the time on the microscopical frame, at the moment of the shooting. The time (digital watch), as well as other relevant parameters (temperature etc.) are displayed on a "parameter board", the image of which is encrusted into the microscopical frame by means of an auxiliary two-component lens system. These lenses (current type of microscopical and photographical objectives) are centered on an axis perpendicular to the microscope-camera axis and provide a reduced image of the "parameter board", which is projected on the film edge after deflection by a 45 degree mirror. The latter (aluminized perspex sheet) is located above the photographical eyepiece; it is pierced at the place of the eyepoint in order to give way to the light rays coming out of the cellular culture.

The Impact of Optimal Respiratory Gating and Image Noise on Evaluation of Intratumor Heterogeneity on 18F-FDG PET Imaging of Lung Cancer.

PubMed

Grootjans, Willem; Tixier, Florent; van der Vos, Charlotte S; Vriens, Dennis; Le Rest, Catherine C; Bussink, Johan; Oyen, Wim J G; de Geus-Oei, Lioe-Fee; Visvikis, Dimitris; Visser, Eric P

2016-11-01

Accurate measurement of intratumor heterogeneity using parameters of texture on PET images is essential for precise characterization of cancer lesions. In this study, we investigated the influence of respiratory motion and varying noise levels on quantification of textural parameters in patients with lung cancer. We used an optimal-respiratory-gating algorithm on the list-mode data of 60 lung cancer patients who underwent 18 F-FDG PET. The images were reconstructed using a duty cycle of 35% (percentage of the total acquired PET data). In addition, nongated images of varying statistical quality (using 35% and 100% of the PET data) were reconstructed to investigate the effects of image noise. Several global image-derived indices and textural parameters (entropy, high-intensity emphasis, zone percentage, and dissimilarity) that have been associated with patient outcome were calculated. The clinical impact of optimal respiratory gating and image noise on assessment of intratumor heterogeneity was evaluated using Cox regression models, with overall survival as the outcome measure. The threshold for statistical significance was adjusted for multiple comparisons using Bonferroni correction. In the lower lung lobes, respiratory motion significantly affected quantification of intratumor heterogeneity for all textural parameters (P < 0.007) except entropy (P > 0.007). The mean increase in entropy, dissimilarity, zone percentage, and high-intensity emphasis was 1.3% ± 1.5% (P = 0.02), 11.6% ± 11.8% (P = 0.006), 2.3% ± 2.2% (P = 0.002), and 16.8% ± 17.2% (P = 0.006), respectively. No significant differences were observed for lesions in the upper lung lobes (P > 0.007). Differences in the statistical quality of the PET images affected the textural parameters less than respiratory motion, with no significant difference observed. The median follow-up time was 35 mo (range, 7-39 mo). In multivariate analysis for overall survival, total lesion glycolysis and high-intensity emphasis were the two most relevant image-derived indices and were considered to be independent significant covariates for the model regardless of the image type considered. The tested textural parameters are robust in the presence of respiratory motion artifacts and varying levels of image noise. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Kinetic modeling in PET imaging of hypoxia

PubMed Central

Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas

2014-01-01

Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200

Color normalization for robust evaluation of microscopy images

NASA Astrophysics Data System (ADS)

Švihlík, Jan; Kybic, Jan; Habart, David

2015-09-01

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either lαβ or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation.

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

Real-time high dynamic range laser scanning microscopy

NASA Astrophysics Data System (ADS)

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-04-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Modulate chopper technique used in pyroelectric uncooled focal plane array thermal imager

NASA Astrophysics Data System (ADS)

He, Yuqing; Jin, Weiqi; Liu, Guangrong; Gao, Zhiyun; Wang, Xia; Wang, Lingxue

2002-09-01

Pyroelectric uncooled focal plane array (FPA) thermal imager has the advantages of low cost, small size, high responsibility and can work under room temperature, so it has great progress in recent years. As a matched technique, the modulate chopper has become one of the key techniques in uncooled FPA thermal imaging system. Now the Archimedes spiral cord chopper technique is mostly used. When it works, the chopper pushing scans the detector's pixel array, thus makes the pixels being exposed continuously. This paper simulates the shape of this kind of chopper, analyses the exposure time of the detector's every pixel, and also analyses the whole detector pixels' exposure sequence. From the analysis we can get the results: the parameter of Archimedes spiral cord, the detector's thermal time constant, the detector's geometrical dimension, the relative position of the detector to the chopper's spiral cord are the system's important parameters, they will affect the chopper's exposure efficiency and uniformity. We should design the chopper's relevant parameter according to the practical request to achieve the chopper's appropriate structure.

Fast and accurate denoising method applied to very high resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Masse, Antoine; Lefèvre, Sébastien; Binet, Renaud; Artigues, Stéphanie; Lassalle, Pierre; Blanchet, Gwendoline; Baillarin, Simon

2017-10-01

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

Determining appropriate imaging parameters for kilovoltage intrafraction monitoring: an experimental phantom study

NASA Astrophysics Data System (ADS)

Wallace, D.; Ng, J. A.; Keall, P. J.; O'Brien, R. T.; Poulsen, P. R.; Juneja, P.; Booth, J. T.

2015-06-01

Kilovoltage intrafraction monitoring (KIM) utilises the kV imager during treatment for real-time tracking of prostate fiducial markers. However, its effectiveness relies on sufficient image quality for the fiducial tracking task. To guide the performance characterisation of KIM under different clinically relevant conditions, the effect of different kV parameters and patient size on image quality, and quantification of MV scatter from the patient to the kV detector panel were investigated in this study. Image quality was determined for a range of kV acquisition frame rates, kV exposure, MV dose rates and patient sizes. Two methods were used to determine image quality; the ratio of kV signal through the patient to the MV scatter from the patient incident on the kilovoltage detector, and the signal-to-noise ratio (SNR). The effect of patient size and frame rate on MV scatter was evaluated in a homogeneous CIRS pelvis phantom and marker segmentation was determined utilising the Rando phantom with embedded markers. MV scatter incident on the detector was shown to be dependent on patient thickness and frame rate. The segmentation code was shown to be successful for all frame rates above 3 Hz for the Rando phantom corresponding to a kV to MV ratio of 0.16 and an SNR of 1.67. For a maximum patient dimension less than 36.4 cm the conservative kV parameters of 5 Hz at 1 mAs can be used to reduce dose while retaining image quality, where the current baseline kV parameters of 10 Hz at 1 mAs is shown to be adequate for marker segmentation up to a patient dimension of 40 cm. In conclusion, the MV scatter component of image quality noise for KIM has been quantified. For most prostate patients, use of KIM with 10 Hz imaging at 1 mAs is adequate however image quality can be maintained and imaging dose reduced by altering existing acquisition parameters.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Evaluation of automatic dose rate control for flat panel imaging using a spatial frequency domain figure of merit.

PubMed

Dehairs, M; Bosmans, H; Desmet, W; Marshall, N W

2017-07-31

Current automatic dose rate controls (ADRCs) of dynamic x-ray imaging systems adjust their acquisition parameters in response to changes in patient thickness in order to achieve a constant signal level in the image receptor. This work compares a 3 parameter (3P) ADRC control to a more flexible 5-parameter (5P) method to meet this goal. A phantom composed of 15 composite poly(methyl) methacrylate (PMMA)/aluminium (Al) plates was imaged on a Siemens Artis Q dynamic system using standard 3P and 5P ADRC techniques. Phantom thickness covered a water equivalent thickness (WET) range of 2.5 cm to 37.5 cm. Acquisition parameter settings (tube potential, tube current, pulse length, copper filtration and focus size) and phantom entrance air kerma rate (EAKR) were recorded as the thickness changed. Signal difference to noise ratio (SDNR) was measured using a 0.3 mm iron insert centred in the PMMA stack, positioned at the system isocentre. SDNR was then multiplied by modulation transfer function (MTF) based correction factors for focal spot penumbral blurring and motion blurring, to give a spatial frequency dependent parameter, SDNR(u). These MTF correction factors were evaluated for an object motion of 25 mm s -1 and at a spatial frequency of 1.4 mm -1 in the object plane, typical for cardiac imaging. The figure of merit (FOM) was calculated as SDNR(u)²/EAKR for the two ADRC regimes. Using 5P versus 3P technique showed clear improvements over all thicknesses. Averaged over clinically relevant adult WET values (20 cm-37.5 cm), EAKR was reduced by 13% and 27% for fluoroscopy and acquisition modes, respectively, while the SDNR(u) based FOM increased by 16% and 34% for fluoroscopy and acquisition. In conclusion, the generalized FOM, taking into account the influence of focus size and object motion, showed benefit in terms of image quality and patient dose for the 5-parameter control over 3-parameter method for the ADRC programming of dynamic x-ray imaging systems.

Evaluation of automatic dose rate control for flat panel imaging using a spatial frequency domain figure of merit

NASA Astrophysics Data System (ADS)

Dehairs, M.; Bosmans, H.; Desmet, W.; Marshall, N. W.

2017-08-01

Current automatic dose rate controls (ADRCs) of dynamic x-ray imaging systems adjust their acquisition parameters in response to changes in patient thickness in order to achieve a constant signal level in the image receptor. This work compares a 3 parameter (3P) ADRC control to a more flexible 5-parameter (5P) method to meet this goal. A phantom composed of 15 composite poly(methyl) methacrylate (PMMA)/aluminium (Al) plates was imaged on a Siemens Artis Q dynamic system using standard 3P and 5P ADRC techniques. Phantom thickness covered a water equivalent thickness (WET) range of 2.5 cm to 37.5 cm. Acquisition parameter settings (tube potential, tube current, pulse length, copper filtration and focus size) and phantom entrance air kerma rate (EAKR) were recorded as the thickness changed. Signal difference to noise ratio (SDNR) was measured using a 0.3 mm iron insert centred in the PMMA stack, positioned at the system isocentre. SDNR was then multiplied by modulation transfer function (MTF) based correction factors for focal spot penumbral blurring and motion blurring, to give a spatial frequency dependent parameter, SDNR(u). These MTF correction factors were evaluated for an object motion of 25 mm s-1 and at a spatial frequency of 1.4 mm-1 in the object plane, typical for cardiac imaging. The figure of merit (FOM) was calculated as SDNR(u)²/EAKR for the two ADRC regimes. Using 5P versus 3P technique showed clear improvements over all thicknesses. Averaged over clinically relevant adult WET values (20 cm-37.5 cm), EAKR was reduced by 13% and 27% for fluoroscopy and acquisition modes, respectively, while the SDNR(u) based FOM increased by 16% and 34% for fluoroscopy and acquisition. In conclusion, the generalized FOM, taking into account the influence of focus size and object motion, showed benefit in terms of image quality and patient dose for the 5-parameter control over 3-parameter method for the ADRC programming of dynamic x-ray imaging systems.

Image-based spectroscopy for environmental monitoring

NASA Astrophysics Data System (ADS)

Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

2014-03-01

An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

PubMed

Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

2007-01-01

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

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

Real-time high dynamic range laser scanning microscopy

PubMed Central

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-01-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging. PMID:27032979

Characterizing Uncertainty In Electrical Resistivity Tomography Images Due To Subzero Temperature Variability

NASA Astrophysics Data System (ADS)

Herring, T.; Cey, E. E.; Pidlisecky, A.

2017-12-01

Time-lapse electrical resistivity tomography (ERT) is used to image changes in subsurface electrical conductivity (EC), e.g. due to a saline contaminant plume. Temperature variation also produces an EC response, which interferes with the signal of interest. Temperature compensation requires the temperature distribution and the relationship between EC and temperature, but this relationship at subzero temperatures is not well defined. The goal of this study is to examine how uncertainty in the subzero EC/temperature relationship manifests in temperature corrected ERT images, especially with respect to relevant plume parameters (location, contaminant mass, etc.). First, a lab experiment was performed to determine the EC of fine-grained glass beads over a range of temperatures (-20° to 20° C) and saturations. The measured EC/temperature relationship was then used to add temperature effects to a hypothetical EC model of a conductive plume. Forward simulations yielded synthetic field data to which temperature corrections were applied. Varying the temperature/EC relationship used in the temperature correction and comparing the temperature corrected ERT results to the synthetic model enabled a quantitative analysis of the error of plume parameters associated with temperature variability. Modeling possible scenarios in this way helps to establish the feasibility of different time-lapse ERT applications by quantifying the uncertainty associated with parameter(s) of interest.

Fully automatic registration and segmentation of first-pass myocardial perfusion MR image sequences.

PubMed

Gupta, Vikas; Hendriks, Emile A; Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2010-11-01

Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation of the myocardium in a large number of images. To reduce the manual interaction and expedite the perfusion analysis, we propose an automatic registration and segmentation method for the derivation of perfusion linked parameters. A complete automation was accomplished by first registering misaligned images using a method based on independent component analysis, and then using the registered data to automatically segment the myocardium with active appearance models. We used 18 perfusion studies (100 images per study) for validation in which the automatically obtained (AO) contours were compared with expert drawn contours on the basis of point-to-curve error, Dice index, and relative perfusion upslope in the myocardium. Visual inspection revealed successful segmentation in 15 out of 18 studies. Comparison of the AO contours with expert drawn contours yielded 2.23 ± 0.53 mm and 0.91 ± 0.02 as point-to-curve error and Dice index, respectively. The average difference between manually and automatically obtained relative upslope parameters was found to be statistically insignificant (P = .37). Moreover, the analysis time per slice was reduced from 20 minutes (manual) to 1.5 minutes (automatic). We proposed an automatic method that significantly reduced the time required for analysis of first-pass cardiac magnetic resonance perfusion images. The robustness and accuracy of the proposed method were demonstrated by the high spatial correspondence and statistically insignificant difference in perfusion parameters, when AO contours were compared with expert drawn contours. Copyright © 2010 AUR. Published by Elsevier Inc. All rights reserved.

[Principles of the EOS™ X-ray machine and its use in daily orthopedic practice].

PubMed

Illés, Tamás; Somoskeöy, Szabolcs

2012-02-26

The EOS™ X-ray machine, based on a Nobel prize-winning invention in Physics in the field of particle detection, is capable of simultaneously capturing biplanar X-ray images by slot scanning of the whole body in an upright, physiological load-bearing position, using ultra low radiation doses. The simultaneous capture of spatially calibrated anterioposterior and lateral images allows the performance of a three-dimensional (3D) surface reconstruction of the skeletal system by a special software. Parts of the skeletal system in X-ray images and 3D-reconstructed models appear in true 1:1 scale for size and volume, thus spinal and vertebral parameters, lower limb axis lengths and angles, as well as any relevant clinical parameters in orthopedic practice could be very precisely measured and calculated. Visualization of 3D reconstructed models in various views by the sterEOS 3D software enables the presentation of top view images, through which one can analyze the rotational conditions of lower limbs, joints and spine deformities in horizontal plane and this provides revolutionary novel possibilities in orthopedic surgery, especially in spine surgery.

NanoTopoChip: High-throughput nanotopographical cell instruction.

PubMed

Hulshof, Frits F B; Zhao, Yiping; Vasilevich, Aliaksei; Beijer, Nick R M; de Boer, Meint; Papenburg, Bernke J; van Blitterswijk, Clemens; Stamatialis, Dimitrios; de Boer, Jan

2017-10-15

Surface topography is able to influence cell phenotype in numerous ways and offers opportunities to manipulate cells and tissues. In this work, we develop the Nano-TopoChip and study the cell instructive effects of nanoscale topographies. A combination of deep UV projection lithography and conventional lithography was used to fabricate a library of more than 1200 different defined nanotopographies. To illustrate the cell instructive effects of nanotopography, actin-RFP labeled U2OS osteosarcoma cells were cultured and imaged on the Nano-TopoChip. Automated image analysis shows that of many cell morphological parameters, cell spreading, cell orientation and actin morphology are mostly affected by the nanotopographies. Additionally, by using modeling, the changes of cell morphological parameters could by predicted by several feature shape parameters such as lateral size and spacing. This work overcomes the technological challenges of fabricating high quality defined nanoscale features on unprecedented large surface areas of a material relevant for tissue culture such as PS and the screening system is able to infer nanotopography - cell morphological parameter relationships. Our screening platform provides opportunities to identify and study the effect of nanotopography with beneficial properties for the culture of various cell types. The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which demonstrates how cells are affected by nanotopographies. The large dataset, acquired by quantitative high-content imaging, allowed us to use predictive modeling to describe how feature dimensions affect cell morphology. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The evolution of phase holographic imaging from a research idea to publicly traded company

NASA Astrophysics Data System (ADS)

Egelberg, Peter

2018-02-01

Recognizing the value and unmet need for label-free kinetic cell analysis, Phase Holograhic Imaging defines its market segment as automated, easy to use and affordable time-lapse cytometry. The process of developing new technology, meeting customer expectations, sources of corporate funding and R&D adjustments prompted by field experience will be reviewed. Additionally, it is discussed how relevant biological information can be extracted from a sequence of quantitative phase images, with negligible user assistance and parameter tweaking, to simultaneously provide cell culture characteristics such as cell growth rate, viability, division rate, mitosis duration, phagocytosis rate, migration, motility and cell-cell adherence without requiring any artificial cell manipulation.

Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

PubMed

Lam, Van K; Nguyen, Thanh C; Chung, Byung M; Nehmetallah, George; Raub, Christopher B

2018-03-01

The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several morphologies related to the mode of migration and substrate stiffness, relevant to mechanisms of cancer invasiveness in vivo. The quantitative phase information from DHM may accurately classify adhesive cancer cell subpopulations with clinical relevance. To test this, cells from the invasive breast cancer MDA-MB-231 cell line were cultured on glass, tissue-culture treated polystyrene, and collagen hydrogels, and imaged with DHM followed by epifluorescence microscopy after staining F-actin and nuclei. Trends in cell phase parameters were tracked on the different substrates, during cell division, and during matrix adhesion, relating them to F-actin features. Support vector machine learning algorithms were trained and tested using parameters from holographic phase reconstructions and cell geometric features from conventional phase images, and used to distinguish between elongated and rounded cell morphologies. DHM was able to distinguish between elongated and rounded morphologies of MDA-MB-231 cells with 94% accuracy, compared to 83% accuracy using cell geometric features from conventional brightfield microscopy. This finding indicates the potential of DHM to detect and monitor cancer cell morphologies relevant to cell cycle phase status, substrate adhesion, and motility. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

PubMed

Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana

2015-11-01

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.

Caracterisation des occupations du sol en milieu urbain par imagerie radar

NASA Astrophysics Data System (ADS)

Codjia, Claude

This study aims to test the relevance of medium and high-resolution SAR images on the characterization of the types of land use in urban areas. To this end, we have relied on textural approaches based on second-order statistics. Specifically, we look for texture parameters most relevant for discriminating urban objects. We have used in this regard Radarsat-1 in fine polarization mode and Radarsat-2 HH fine mode in dual and quad polarization and ultrafine mode HH polarization. The land uses sought were dense building, medium density building, low density building, industrial and institutional buildings, low density vegetation, dense vegetation and water. We have identified nine texture parameters for analysis, grouped into families according to their mathematical definitions in a first step. The parameters of similarity / dissimilarity include Homogeneity, Contrast, the Differential Inverse Moment and Dissimilarity. The parameters of disorder are Entropy and the Second Angular Momentum. The Standard Deviation and Correlation are the dispersion parameters and the Average is a separate family. It is clear from experience that certain combinations of texture parameters from different family used in classifications yield good results while others produce kappa of very little interest. Furthermore, we realize that if the use of several texture parameters improves classifications, its performance ceils from three parameters. The calculation of correlations between the textures and their principal axes confirm the results. Despite the good performance of this approach based on the complementarity of texture parameters, systematic errors due to the cardinal effects remain on classifications. To overcome this problem, a radiometric compensation model was developed based on the radar cross section (SER). A radar simulation from the digital surface model of the environment allowed us to extract the building backscatter zones and to analyze the related backscatter. Thus, we were able to devise a strategy of compensation of cardinal effects solely based on the responses of the objects according to their orientation from the plane of illumination through the radar's beam. It appeared that a compensation algorithm based on the radar cross section was appropriate. Some examples of the application of this algorithm on HH polarized RADARSAT-2 images are presented as well. Application of this algorithm will allow considerable gains with regard to certain forms of automation (classification and segmentation) at the level of radar imagery thus generating a higher level of quality in regard to visual interpretation. Application of this algorithm on RADARSAT-1 and RADARSAT-2 images with HH, HV, VH, and VV polarisations helped make considerable gains and eliminate most of the classification errors due to the cardinal effects.

Optic disc boundary segmentation from diffeomorphic demons registration of monocular fundus image sequences versus 3D visualization of stereo fundus image pairs for automated early stage glaucoma assessment

NASA Astrophysics Data System (ADS)

Gatti, Vijay; Hill, Jason; Mitra, Sunanda; Nutter, Brian

2014-03-01

Despite the current availability in resource-rich regions of advanced technologies in scanning and 3-D imaging in current ophthalmology practice, world-wide screening tests for early detection and progression of glaucoma still consist of a variety of simple tools, including fundus image-based parameters such as CDR (cup to disc diameter ratio) and CAR (cup to disc area ratio), especially in resource -poor regions. Reliable automated computation of the relevant parameters from fundus image sequences requires robust non-rigid registration and segmentation techniques. Recent research work demonstrated that proper non-rigid registration of multi-view monocular fundus image sequences could result in acceptable segmentation of cup boundaries for automated computation of CAR and CDR. This research work introduces a composite diffeomorphic demons registration algorithm for segmentation of cup boundaries from a sequence of monocular images and compares the resulting CAR and CDR values with those computed manually by experts and from 3-D visualization of stereo pairs. Our preliminary results show that the automated computation of CDR and CAR from composite diffeomorphic segmentation of monocular image sequences yield values comparable with those from the other two techniques and thus may provide global healthcare with a cost-effective yet accurate tool for management of glaucoma in its early stage.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

EOS microdose protocol for the radiological follow-up of adolescent idiopathic scoliosis.

PubMed

Ilharreborde, Brice; Ferrero, Emmanuelle; Alison, Marianne; Mazda, Keyvan

2016-02-01

Imaging plays a key role in adolescent idiopathic scoliosis (AIS) to determine the prognosis and accordingly define the best therapeutic strategy to follow. Conventional radiographs with ionizing radiation have been associated with 1-2 % increased lifetime risk of developing cancer in children, and physicians, therefore, need a sensitive but harmless way to explore patients at risk, according to the "as low as reasonably achievable" concept. The EOS system (EOS imaging, Paris, France) is available in routine clinical use since 2007, and allows 3D reconstructions of the trunk in standing position with significant radiation reduction. With recent technical advances, further dose reduction can be obtained, but at the cost of image quality that might alter the reliability of 3D reconstructions. The aim of the present study was to analyze the reproducibility of a "microdose" protocol, and evaluate its use in clinical practice. 32 consecutive patients followed for AIS were prospectively included. Biplanar radiographs were obtained with the EOS system according to the new microdose protocol. From the microdose images obtained, three experienced operators performed 3D reconstructions, two times for each subject in a random order (total, 192 reconstructions). The intraoperator repeatability and interoperator reproducibility were evaluated, as recommended by the International Organization for Standardization, for the most clinically relevant 3D radiological parameters. The identification of the required anatomical landmarks for the "fast spine" reconstruction process was possible in all cases. None of the patients required a second acquisition for 3D analysis. Mean time for reconstruction was 5 ± 2 min. The intraoperator repeatability was better than interoperator reproducibility for all parameters, with values ranging between 3° and 8° for frontal and sagittal spinal parameters, and between 1° and 8° for pelvic measurements. The agreement was very good for all clinical measurements. No correlation was found between the BMI and the reliability of the measurements. Because children are notably more sensitive to the carcinogenic effects of ionizing radiation, judicious use of imaging methods and a search for newer technologies remain necessary. Results of the current study show that the new microdose acquisition protocol can be used in clinical practice without altering the quality of the images. Relevant clinical measurements can be made manually, but the landmarks are also visible enough to allow accurate 3D reconstructions (ICC >0.91 for all parameters). The resulting radiation exposure was 5.5 times lower than that received with the prior protocol, corresponding now to a 45-fold reduction compared to conventional radiographs, and can, therefore, almost be considered negligible.

Parsing Stem Cell Lineage Development Using High Content Image Analysis of Epigenetic Spatial Markers.

PubMed

Kim, Joseph J; Moghe, Prabhas V

2018-06-14

This unit describes a protocol for acquiring and analyzing high-content super-resolution images of human stem cell nuclei for the characterization and classification of the cell differentiation paths based on distinct patterns of epigenetic mark organization. Here, we describe the cell culture, immunocytochemical labeling, super-resolution imaging parameters, and MATLAB-based quantitative image analysis approaches for monitoring human mesenchymal stem cells (hMSCs) and human induced pluripotent stem cells (hiPSCs) as the cells differentiate towards various lineages. Although this protocol uses specific cell types as examples, this approach could be easily extended to a variety of cell types and nuclear epigenetic and mechanosensitive biomarkers that are relevant to specific cell developmental scenarios. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Similarity estimation for reference image retrieval in mammograms using convolutional neural network

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

2018-02-01

Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

Validation of elastic registration algorithms based on adaptive irregular grids for medical applications

NASA Astrophysics Data System (ADS)

Franz, Astrid; Carlsen, Ingwer C.; Renisch, Steffen; Wischmann, Hans-Aloys

2006-03-01

Elastic registration of medical images is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited for a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at a few landmarks, which is not sufficient for elastic transformations described by a huge number of parameters. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points.

Fully automated motion correction in first-pass myocardial perfusion MR image sequences.

PubMed

Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2008-11-01

This paper presents a novel method for registration of cardiac perfusion magnetic resonance imaging (MRI). The presented method is capable of automatically registering perfusion data, using independent component analysis (ICA) to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of that ICA. This reference image is used in a two-pass registration framework. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Despite varying image quality and motion patterns in the evaluation set, validation of the method showed a reduction of the average right ventricle (LV) motion from 1.26+/-0.87 to 0.64+/-0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65+/-7.89% to 0.87+/-3.88% between registered data and manual gold standard. Comparison of clinically relevant parameters computed using registered data and the manual gold standard show a good agreement. Additional tests with a simulated free-breathing protocol showed robustness against considerable deviations from a standard breathing protocol. We conclude that this fully automatic ICA-based method shows an accuracy, a robustness and a computation speed adequate for use in a clinical environment.

Echocardiographic strain and strain-rate imaging: a new tool to study regional myocardial function.

PubMed

D'hooge, Jan; Bijnens, Bart; Thoen, Jan; Van de Werf, Frans; Sutherland, George R; Suetens, Paul

2002-09-01

Ultrasonic imaging is the noninvasive clinical imaging modality of choice for diagnosing heart disease. At present, two-dimensional ultrasonic grayscale images provide a relatively cheap, fast, bedside method to study the morphology of the heart. Several methods have been proposed to assess myocardial function. These have been based on either grayscale or motion (velocity) information measured in real-time. However, the quantitative assessment of regional myocardial function remains an important goal in clinical cardiology. To do this, ultrasonic strain and strain-rate imaging have been introduced. In the clinical setting, these techniques currently only allow one component of the true three-dimensional deformation to be measured. Clinical, multidimensional strain (rate) information can currently thus only be obtained by combining data acquired using different transducer positions. Nevertheless, given the appropriate postprocessing, the clinical value of these techniques has already been shown. Moreover, multidimensional strain and strain-rate estimation of the heart in vivo by means of a single ultrasound acquisition has been shown to be feasible. In this paper, the new techniques of ultrasonic strain rate and strain imaging of the heart are reviewed in terms of definitions, data acquisition, strain-rate estimation, postprocessing, and parameter extraction. Their clinical validation and relevance will be discussed using clinical examples on relevant cardiac pathology. Based on these examples, suggestions are made for future developments of these techniques.

Finding regions of interest in pathological images: an attentional model approach

NASA Astrophysics Data System (ADS)

Gómez, Francisco; Villalón, Julio; Gutierrez, Ricardo; Romero, Eduardo

2009-02-01

This paper introduces an automated method for finding diagnostic regions-of-interest (RoIs) in histopathological images. This method is based on the cognitive process of visual selective attention that arises during a pathologist's image examination. Specifically, it emulates the first examination phase, which consists in a coarse search for tissue structures at a "low zoom" to separate the image into relevant regions.1 The pathologist's cognitive performance depends on inherent image visual cues - bottom-up information - and on acquired clinical medicine knowledge - top-down mechanisms -. Our pathologist's visual attention model integrates the latter two components. The selected bottom-up information includes local low level features such as intensity, color, orientation and texture information. Top-down information is related to the anatomical and pathological structures known by the expert. A coarse approximation to these structures is achieved by an oversegmentation algorithm, inspired by psychological grouping theories. The algorithm parameters are learned from an expert pathologist's segmentation. Top-down and bottom-up integration is achieved by calculating a unique index for each of the low level characteristics inside the region. Relevancy is estimated as a simple average of these indexes. Finally, a binary decision rule defines whether or not a region is interesting. The method was evaluated on a set of 49 images using a perceptually-weighted evaluation criterion, finding a quality gain of 3dB when comparing to a classical bottom-up model of attention.

MRI vs. CT for orthodontic applications: comparison of two MRI protocols and three CT (multislice, cone-beam, industrial) technologies.

PubMed

Detterbeck, Andreas; Hofmeister, Michael; Hofmann, Elisabeth; Haddad, Daniel; Weber, Daniel; Hölzing, Astrid; Zabler, Simon; Schmid, Matthias; Hiller, Karl-Heinz; Jakob, Peter; Engel, Jens; Hiller, Jochen; Hirschfelder, Ursula

2016-07-01

To examine the relative usefulness and suitability of magnetic resonance imaging (MRI) in daily clinical practice as compared to various technologies of computed tomography (CT) in addressing questions of orthodontic interest. Three blinded raters evaluated 2D slices and 3D reconstructions created from scans of two pig heads. Five imaging modalities were used, including three CT technologies-multislice (MSCT), cone-beam CT (CBCT), and industrial (µCT)-and two MRI protocols with different scan durations. Defined orthodontic parameters were rated one by one on the 2D slices and the 3D reconstructions, followed by final overall ratings for each modality. A mixed linear model was used for statistical analysis. Based on the 2D slices, the parameter of visualizing tooth-germ topography did not yield any significantly different ratings for MRI versus any of the CT scans. While some ratings for the other parameters did involve significant differences, how these should be interpreted depends greatly on the relevance of each parameter. Based on the 3D reconstructions, the only significant difference between technologies was noted for the parameter of visualizing root-surface morphology. Based on the final overall ratings, the imaging performance of the standard MRI protocol was noninferior to the performance of the three CT technologies. On comparing the imaging performance of MRI and CT scans, it becomes clear that MRI has a huge potential for applications in daily clinical practice. Given its additional benefits of a good contrast ratio and complete absence of ionizing radiation, further studies are needed to explore this clinical potential in greater detail.

Exploring the nutrient inputs and cycles in Tampa Bay and coastal watersheds using MODIS images and data mining

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin

2011-09-01

Excessive nutrients, which may be represented as Total Nitrogen (TN) and Total Phosphorus (TP) levels, in natural water systems have proven to cause high levels of algae production. The process of phytoplankton growth which consumes the excess TN and TP in a water body can also be related to the changing water quality levels, such as Dissolved Oxygen (DO), chlorophyll-a, and turbidity, associated with their changes in absorbance of natural radiation. This paper explores spatiotemporal nutrient patterns in Tampa Bay, Florida with the aid of Moderate Resolution Imaging Spectroradiometer or MODIS images and Genetic Programming (GP) models that are deigned to link those relevant water quality parameters in aquatic environments.

Monte Carlo modeling of light-tissue interactions in narrow band imaging.

PubMed

Le, Du V N; Wang, Quanzeng; Ramella-Roman, Jessica C; Pfefer, T Joshua

2013-01-01

Light-tissue interactions that influence vascular contrast enhancement in narrow band imaging (NBI) have not been the subject of extensive theoretical study. In order to elucidate relevant mechanisms in a systematic and quantitative manner we have developed and validated a Monte Carlo model of NBI and used it to study the effect of device and tissue parameters, specifically, imaging wavelength (415 versus 540 nm) and vessel diameter and depth. Simulations provided quantitative predictions of contrast-including up to 125% improvement in small, superficial vessel contrast for 415 over 540 nm. Our findings indicated that absorption rather than scattering-the mechanism often cited in prior studies-was the dominant factor behind spectral variations in vessel depth-selectivity. Narrow-band images of a tissue-simulating phantom showed good agreement in terms of trends and quantitative values. Numerical modeling represents a powerful tool for elucidating the factors that affect the performance of spectral imaging approaches such as NBI.

2D dose distribution images of a hybrid low field MRI-γ detector

NASA Astrophysics Data System (ADS)

Abril, A.; Agulles-Pedrós, L.

2016-07-01

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the 99mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.

Better safe than sorry: simplistic fear-relevant stimuli capture attention.

PubMed

Forbes, Sarah J; Purkis, Helena M; Lipp, Ottmar V

2011-08-01

It has been consistently demonstrated that fear-relevant images capture attention preferentially over fear-irrelevant images. Current theory suggests that this faster processing could be mediated by an evolved module that allows certain stimulus features to attract attention automatically, prior to the detailed processing of the image. The present research investigated whether simplified images of fear-relevant stimuli would produce interference with target detection in a visual search task. In Experiment 1, silhouettes and degraded silhouettes of fear-relevant animals produced more interference than did the fear-irrelevant images. Experiment 2, compared the effects of fear-relevant and fear-irrelevant distracters and confirmed that the interference produced by fear-relevant distracters was not an effect of novelty. Experiment 3 suggested that fear-relevant stimuli produced interference regardless of whether participants were instructed as to the content of the images. The three experiments indicate that even very simplistic images of fear-relevant animals can divert attention.

Estimating skin blood saturation by selecting a subset of hyperspectral imaging data

NASA Astrophysics Data System (ADS)

Ewerlöf, Maria; Salerud, E. Göran; Strömberg, Tomas; Larsson, Marcus

2015-03-01

Skin blood haemoglobin saturation (?b) can be estimated with hyperspectral imaging using the wavelength (λ) range of 450-700 nm where haemoglobin absorption displays distinct spectral characteristics. Depending on the image size and photon transport algorithm, computations may be demanding. Therefore, this work aims to evaluate subsets with a reduced number of wavelengths for ?b estimation. White Monte Carlo simulations are performed using a two-layered tissue model with discrete values for epidermal thickness (?epi) and the reduced scattering coefficient (μ's ), mimicking an imaging setup. A detected intensity look-up table is calculated for a range of model parameter values relevant to human skin, adding absorption effects in the post-processing. Skin model parameters, including absorbers, are; μ's (λ), ?epi, haemoglobin saturation (?b), tissue fraction blood (?b) and tissue fraction melanin (?mel). The skin model paired with the look-up table allow spectra to be calculated swiftly. Three inverse models with varying number of free parameters are evaluated: A(?b, ?b), B(?b, ?b, ?mel) and C(all parameters free). Fourteen wavelength candidates are selected by analysing the maximal spectral sensitivity to ?b and minimizing the sensitivity to ?b. All possible combinations of these candidates with three, four and 14 wavelengths, as well as the full spectral range, are evaluated for estimating ?b for 1000 randomly generated evaluation spectra. The results show that the simplified models A and B estimated ?b accurately using four wavelengths (mean error 2.2% for model B). If the number of wavelengths increased, the model complexity needed to be increased to avoid poor estimations.

Ultra-high-speed variable focus optics for novel applications in advanced imaging

NASA Astrophysics Data System (ADS)

Kang, S.; Dotsenko, E.; Amrhein, D.; Theriault, C.; Arnold, C. B.

2018-02-01

With the advancement of ultra-fast manufacturing technologies, high speed imaging with high 3D resolution has become increasingly important. Here we show the use of an ultra-high-speed variable focus optical element, the TAG Lens, to enable new ways to acquire 3D information from an object. The TAG Lens uses sound to adjust the index of refraction profile in a liquid and thereby can achieve focal scanning rates greater than 100 kHz. When combined with a high-speed pulsed LED and a high-speed camera, we can exploit this phenomenon to achieve high-resolution imaging through large depths. By combining the image acquisition with digital image processing, we can extract relevant parameters such as tilt and angle information from objects in the image. Due to the high speeds at which images can be collected and processed, we believe this technique can be used as an efficient method of industrial inspection and metrology for high throughput applications.

Slide Set: Reproducible image analysis and batch processing with ImageJ.

PubMed

Nanes, Benjamin A

2015-11-01

Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.

PET imaging of urokinase-type plasminogen activator receptor (uPAR) in prostate cancer: current status and future perspectives.

PubMed

Skovgaard, Dorthe; Persson, Morten; Kjaer, Andreas

2016-01-01

Overexpression of urokinase-type plasminogen activator receptors (uPAR) represents an important biomarker for aggressiveness in most common malignant diseases, including prostate cancer (PC). Accordingly, uPAR expression either assessed directly in malignant PC tissue or assessed directly in plasma (intact/cleaved forms)-provides independent additional clinical information to that contributed by PSA, Gleason score, and other relevant pathological and clinical parameters. In this respect, non-invasive molecular imaging by positron emission tomography (PET) offers a very attractive technology platform, which can provide the required quantitative information on the uPAR expression profile, without the need for invasive procedures and the risk of missing the target due to tumor heterogeneity. These observations support non-invasive PET imaging of uPAR in PC as a clinically relevant diagnostic and prognostic imaging method. In this review, we will focus on the recent development of uPAR PET and the relevance within prostate cancer imaging. Novel antibody and small-molecule radiotracers-targeting uPAR, including a series of uPAR-targeting PET ligands, based on the high affinity peptide ligand AE105, have been synthesized and tested in vitro and in vivo in preclinical murine xenograft models and, recently, in a first-ever clinical uPAR PET study in cancer patients, including patients with PC. In this phase I study, a high and specific uptake of the tracer 64 Cu-DOTA-AE105 was found in both primary tumors and lymph node metastases. The results are encouraging and support large-scale clinical trials to determine the utility of uPAR PET in the management of patients with PC with the goal of improving outcome.

Wavelets for sign language translation

NASA Astrophysics Data System (ADS)

Wilson, Beth J.; Anspach, Gretel

1993-10-01

Wavelet techniques are applied to help extract the relevant parameters of sign language from video images of a person communicating in American Sign Language or Signed English. The compression and edge detection features of two-dimensional wavelet analysis are exploited to enhance the algorithms under development to classify the hand motion, hand location with respect to the body, and handshape. These three parameters have different processing requirements and complexity issues. The results are described for applying various quadrature mirror filter designs to a filterbank implementation of the desired wavelet transform. The overall project is to develop a system that will translate sign language to English to facilitate communication between deaf and hearing people.

TU-F-9A-01: Balancing Image Quality and Dose in Radiography

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

Peck, D; Pasciak, A

2014-06-15

Emphasis is often placed on minimizing radiation dose in diagnostic imaging without a complete consideration of the effect on image quality, especially those that affect diagnostic accuracy. This session will include a patient image-based review of diagnostic quantities important to radiologists in conventional radiography, including the effects of body habitus, age, positioning, and the clinical indication of the exam. The relationships between image quality, radiation dose, and radiation risk will be discussed, specifically addressing how these factors are affected by image protocols and acquisition parameters and techniques. This session will also discuss some of the actual and perceived radiation riskmore » associated with diagnostic imaging. Regardless if the probability for radiation-induced cancer is small, the fear associated with radiation persists. Also when a risk has a benefit to an individual or to society, the risk may be justified with respect to the benefit. But how do you convey the risks and the benefits to people? This requires knowledge of how people perceive risk and how to communicate the risk and the benefit to different populations. In this presentation the sources of errors in estimating risk from radiation and some methods used to convey risks are reviewed. Learning Objectives: Understand the image quality metrics that are clinically relevant to radiologists. Understand how acquisition parameters and techniques affect image quality and radiation dose in conventional radiology. Understand the uncertainties in estimates of radiation risk from imaging exams. Learn some methods for effectively communicating radiation risk to the public.« less

Left ventricular eccentricity index measured with SPECT myocardial perfusion imaging: An additional parameter of adverse cardiac remodeling.

PubMed

Gimelli, Alessia; Liga, Riccardo; Clemente, Alberto; Marras, Gavino; Kusch, Annette; Marzullo, Paolo

2017-01-12

Single-photon emission computed-tomography (SPECT) allows the quantification of LV eccentricity index (EI), a measure of cardiac remodeling. We sought to evaluate the feasibility of EI measurement with SPECT myocardial perfusion imaging and its interactions with relevant LV functional and structural parameters. Four-hundred and fifty-six patients underwent myocardial perfusion imaging on a Cadmium-Zinc-Telluride (CZT) camera. The summed rest, stress, and difference scores were calculated. From rest images, the LV end-diastolic (EDV) and end-systolic volumes, ejection fraction (EF), and peak filling rate (PFR) were calculated. In every patient, the EI, ranging from 0 (sphere) to 1 (line), was computed using a dedicated software (QGS/QPS; Cedars-Sinai Medical Center). Three-hundred and thirty-eight/456 (74%) patients showed a normal EF (>50%), while 26% had LV systolic dysfunction. The EI was computed from CZT images with excellent reproducibility (interclass correlation coefficient: 0.99, 95% CI 0.98-0.99). More impaired EI values correlated with the presence of a more abnormal LV perfusion (P < .001), function (EF and PFR, P < .001), and structure (EDV, P < .001). On multivariate analysis, higher EDV (P < .001) and depressed EF (P = .014) values were independent predictors of abnormal EI. The evaluation of LV eccentricity is feasible on gated CZT images. Abnormal EI associates with significant cardiac structural and functional abnormalities.

Quantitative real-time optical imaging of the tissue metabolic rate of oxygen consumption

NASA Astrophysics Data System (ADS)

Ghijsen, Michael; Lentsch, Griffin R.; Gioux, Sylvain; Brenner, Matthew; Durkin, Anthony J.; Choi, Bernard; Tromberg, Bruce J.

2018-03-01

The tissue metabolic rate of oxygen consumption (tMRO2) is a clinically relevant marker for a number of pathologies including cancer and arterial occlusive disease. We present and validate a noncontact method for quantitatively mapping tMRO2 over a wide, scalable field of view at 16 frames / s. We achieve this by developing a dual-wavelength, near-infrared coherent spatial frequency-domain imaging (cSFDI) system to calculate tissue optical properties (i.e., absorption, μa, and reduced scattering, μs‧, parameters) as well as the speckle flow index (SFI) at every pixel. Images of tissue oxy- and deoxyhemoglobin concentration ( [ HbO2 ] and [HHb]) are calculated from optical properties and combined with SFI to calculate tMRO2. We validate the system using a series of yeast-hemoglobin tissue-simulating phantoms and conduct in vivo tests in humans using arterial occlusions that demonstrate sensitivity to tissue metabolic oxygen debt and its repayment. Finally, we image the impact of cyanide exposure and toxicity reversal in an in vivo rabbit model showing clear instances of mitochondrial uncoupling and significantly diminished tMRO2. We conclude that dual-wavelength cSFDI provides rapid, quantitative, wide-field mapping of tMRO2 that can reveal unique spatial and temporal dynamics relevant to tissue pathology and viability.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries.

PubMed

Noor, Siti Salwa Md; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-11-16

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability.

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

PubMed

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Multiple sclerosis: changes in microarchitecture of white matter tracts after training with a video game balance board.

PubMed

Prosperini, Luca; Fanelli, Fulvia; Petsas, Nikolaos; Sbardella, Emilia; Tona, Francesca; Raz, Eytan; Fortuna, Deborah; De Angelis, Floriana; Pozzilli, Carlo; Pantano, Patrizia

2014-11-01

To determine if high-intensity, task-oriented, visual feedback training with a video game balance board (Nintendo Wii) induces significant changes in diffusion-tensor imaging ( DTI diffusion-tensor imaging ) parameters of cerebellar connections and other supratentorial associative bundles and if these changes are related to clinical improvement in patients with multiple sclerosis. The protocol was approved by local ethical committee; each participant provided written informed consent. In this 24-week, randomized, two-period crossover pilot study, 27 patients underwent static posturography and brain magnetic resonance (MR) imaging at study entry, after the first 12-week period, and at study termination. Thirteen patients started a 12-week training program followed by a 12-week period without any intervention, while 14 patients received the intervention in reverse order. Fifteen healthy subjects also underwent MR imaging once and underwent static posturography. Virtual dissection of white matter tracts was performed with streamline tractography; values of DTI diffusion-tensor imaging parameters were then obtained for each dissected tract. Repeated measures analyses of variance were performed to evaluate whether DTI diffusion-tensor imaging parameters significantly changed after intervention, with false discovery rate correction for multiple hypothesis testing. There were relevant differences between patients and healthy control subjects in postural sway and DTI diffusion-tensor imaging parameters (P < .05). Significant main effects of time by group interaction for fractional anisotropy and radial diffusivity of the left and right superior cerebellar peduncles were found (F2,23 range, 5.555-3.450; P = .036-.088 after false discovery rate correction). These changes correlated with objective measures of balance improvement detected at static posturography (r = -0.381 to 0.401, P < .05). However, both clinical and DTI diffusion-tensor imaging changes did not persist beyond 12 weeks after training. Despite the low statistical power (35%) due to the small sample size, the results showed that training with the balance board system modified the microstructure of superior cerebellar peduncles. The clinical improvement observed after training might be mediated by enhanced myelination-related processes, suggesting that high-intensity, task-oriented exercises could induce favorable microstructural changes in the brains of patients with multiple sclerosis.

Evaluation of reconstruction techniques in regional cerebral blood flow SPECT using trade-off plots: a Monte Carlo study.

PubMed

Olsson, Anna; Arlig, Asa; Carlsson, Gudrun Alm; Gustafsson, Agnetha

2007-09-01

The image quality of single photon emission computed tomography (SPECT) depends on the reconstruction algorithm used. The purpose of the present study was to evaluate parameters in ordered subset expectation maximization (OSEM) and to compare systematically with filtered back-projection (FBP) for reconstruction of regional cerebral blood flow (rCBF) SPECT, incorporating attenuation and scatter correction. The evaluation was based on the trade-off between contrast recovery and statistical noise using different sizes of subsets, number of iterations and filter parameters. Monte Carlo simulated SPECT studies of a digital human brain phantom were used. The contrast recovery was calculated as measured contrast divided by true contrast. Statistical noise in the reconstructed images was calculated as the coefficient of variation in pixel values. A constant contrast level was reached above 195 equivalent maximum likelihood expectation maximization iterations. The choice of subset size was not crucial as long as there were > or = 2 projections per subset. The OSEM reconstruction was found to give 5-14% higher contrast recovery than FBP for all clinically relevant noise levels in rCBF SPECT. The Butterworth filter, power 6, achieved the highest stable contrast recovery level at all clinically relevant noise levels. The cut-off frequency should be chosen according to the noise level accepted in the image. Trade-off plots are shown to be a practical way of deciding the number of iterations and subset size for the OSEM reconstruction and can be used for other examination types in nuclear medicine.

Separation of ballistic and diffusive fluorescence photons in confocal Light-Sheet Microscopy of Arabidopsis roots.

PubMed

Meinert, Tobias; Tietz, Olaf; Palme, Klaus J; Rohrbach, Alexander

2016-08-24

Image quality in light-sheet fluorescence microscopy is strongly affected by the shape of the illuminating laser beam inside embryos, plants or tissue. While the phase of Gaussian or Bessel beams propagating through thousands of cells can be partly controlled holographically, the propagation of fluorescence light to the detector is difficult to control. With each scatter process a fluorescence photon loses information necessary for the image generation. Using Arabidopsis root tips we demonstrate that ballistic and diffusive fluorescence photons can be separated by analyzing the image spectra in each plane without a priori knowledge. We introduce a theoretical model allowing to extract typical scattering parameters of the biological material. This allows to attenuate image contributions from diffusive photons and to amplify the relevant image contributions from ballistic photons through a depth dependent deconvolution. In consequence, image contrast and resolution are significantly increased and scattering artefacts are minimized especially for Bessel beams with confocal line detection.

Separation of ballistic and diffusive fluorescence photons in confocal Light-Sheet Microscopy of Arabidopsis roots

PubMed Central

Meinert, Tobias; Tietz, Olaf; Palme, Klaus J.; Rohrbach, Alexander

2016-01-01

Image quality in light-sheet fluorescence microscopy is strongly affected by the shape of the illuminating laser beam inside embryos, plants or tissue. While the phase of Gaussian or Bessel beams propagating through thousands of cells can be partly controlled holographically, the propagation of fluorescence light to the detector is difficult to control. With each scatter process a fluorescence photon loses information necessary for the image generation. Using Arabidopsis root tips we demonstrate that ballistic and diffusive fluorescence photons can be separated by analyzing the image spectra in each plane without a priori knowledge. We introduce a theoretical model allowing to extract typical scattering parameters of the biological material. This allows to attenuate image contributions from diffusive photons and to amplify the relevant image contributions from ballistic photons through a depth dependent deconvolution. In consequence, image contrast and resolution are significantly increased and scattering artefacts are minimized especially for Bessel beams with confocal line detection. PMID:27553506

Calibration-free quantitative surface topography reconstruction in scanning electron microscopy.

PubMed

Faber, E T; Martinez-Martinez, D; Mansilla, C; Ocelík, V; Hosson, J Th M De

2015-01-01

This work presents a new approach to obtain reliable surface topography reconstructions from 2D Scanning Electron Microscopy (SEM) images. In this method a set of images taken at different tilt angles are compared by means of digital image correlation (DIC). It is argued that the strength of the method lies in the fact that precise knowledge about the nature of the rotation (vector and/or magnitude) is not needed. Therefore, the great advantage is that complex calibrations of the measuring equipment are avoided. The paper presents the necessary equations involved in the methods, including derivations and solutions. The method is illustrated with examples of 3D reconstructions followed by a discussion on the relevant experimental parameters. Copyright © 2014 Elsevier B.V. All rights reserved.

A simulation study of spectral Čerenkov luminescence imaging for tumour margin estimation

NASA Astrophysics Data System (ADS)

Calvert, Nick; Helo, Yusef; Mertzanidou, Thomy; Tuch, David S.; Arridge, Simon R.; Stoyanov, Danail

2017-03-01

Breast cancer is the most common cancer in women in the world. Breast-conserving surgery (BCS) is a standard surgical treatment for breast cancer with the key objective of removing breast tissue, maintaining a negative surgical margin and providing a good cosmetic outcome. A positive surgical margin, meaning the presence of cancerous tissues on the surface of the breast specimen after surgery, is associated with local recurrence after therapy. In this study, we investigate a new imaging modality based on Cerenkov luminescence imaging (CLI) for the purpose of detecting positive surgical margins during BCS. We develop Monte Carlo (MC) simulations using the Geant4 nuclear physics simulation toolbox to study the spectrum of photons emitted given 18F-FDG and breast tissue properties. The resulting simulation spectra show that the CLI signal contains information that may be used to estimate whether the cancerous cells are at a depth of less than 1 mm or greater than 1 mm given appropriate imaging system design and sensitivity. The simulation spectra also show that when the source is located within 1 mm of the surface, the tissue parameters are not relevant to the model as the spectra do not vary significantly. At larger depths, however, the spectral information varies significantly with breast optical parameters, having implications for further studies and system design. While promising, further studies are needed to quantify the CLI response to more accurately incorporate tissue specific parameters and patient specific anatomical details.

Development of a dual-energy computed tomography quality control program: Characterization of scanner response and definition of relevant parameters for a fast-kVp switching dual-energy computed tomography system.

PubMed

Nute, Jessica L; Jacobsen, Megan C; Stefan, Wolfgang; Wei, Wei; Cody, Dianna D

2018-04-01

A prototype QC phantom system and analysis process were developed to characterize the spectral capabilities of a fast kV-switching dual-energy computed tomography (DECT) scanner. This work addresses the current lack of quantitative oversight for this technology, with the goal of identifying relevant scan parameters and test metrics instrumental to the development of a dual-energy quality control (DEQC). A prototype elliptical phantom (effective diameter: 35 cm) was designed with multiple material inserts for DECT imaging. Inserts included tissue equivalent and material rods (including iodine and calcium at varying concentrations). The phantom was scanned on a fast kV-switching DECT system using 16 dual-energy acquisitions (CTDIvol range: 10.3-62 mGy) with varying pitch, rotation time, and tube current. The circular head phantom (22 cm diameter) was scanned using a similar protocol (12 acquisitions; CTDIvol range: 36.7-132.6 mGy). All acquisitions were reconstructed at 50, 70, 110, and 140 keV and using a water-iodine material basis pair. The images were evaluated for iodine quantification accuracy, stability of monoenergetic reconstruction CT number, noise, and positional constancy. Variance component analysis was used to identify technique parameters that drove deviations in test metrics. Variances were compared to thresholds derived from manufacturer tolerances to determine technique parameters that had a nominally significant effect on test metrics. Iodine quantification error was largely unaffected by any of the technique parameters investigated. Monoenergetic HU stability was found to be affected by mAs, with a threshold under which spectral separation was unsuccessful, diminishing the utility of DECT imaging. Noise was found to be affected by CTDIvol in the DEQC body phantom, and CTDIvol and mA in the DEQC head phantom. Positional constancy was found to be affected by mAs in the DEQC body phantom and mA in the DEQC head phantom. A streamlined scan protocol was developed to further investigate the effects of CTDIvol and rotation time while limiting data collection to the DEQC body phantom. Further data collection will be pursued to determine baseline values and statistically based failure thresholds for the validation of long-term DECT scanner performance. © 2018 American Association of Physicists in Medicine.

An Efficient Algorithm for Mapping Imaging Data to 3D Unstructured Grids in Computational Biomechanics

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

Einstein, Daniel R.; Kuprat, Andrew P.; Jiao, Xiangmin

2013-01-01

Geometries for organ scale and multiscale simulations of organ function are now routinely derived from imaging data. However, medical images may also contain spatially heterogeneous information other than geometry that are relevant to such simulations either as initial conditions or in the form of model parameters. In this manuscript, we present an algorithm for the efficient and robust mapping of such data to imaging based unstructured polyhedral grids in parallel. We then illustrate the application of our mapping algorithm to three different mapping problems: 1) the mapping of MRI diffusion tensor data to an unstuctured ventricular grid; 2) the mappingmore » of serial cyro-section histology data to an unstructured mouse brain grid; and 3) the mapping of CT-derived volumetric strain data to an unstructured multiscale lung grid. Execution times and parallel performance are reported for each case.« less

Low-Cost Optical Mapping Systems for Panoramic Imaging of Complex Arrhythmias and Drug-Action in Translational Heart Models

NASA Astrophysics Data System (ADS)

Lee, Peter; Calvo, Conrado J.; Alfonso-Almazán, José M.; Quintanilla, Jorge G.; Chorro, Francisco J.; Yan, Ping; Loew, Leslie M.; Filgueiras-Rama, David; Millet, José

2017-02-01

Panoramic optical mapping is the primary method for imaging electrophysiological activity from the entire outer surface of Langendorff-perfused hearts. To date, it is the only method of simultaneously measuring multiple key electrophysiological parameters, such as transmembrane voltage and intracellular free calcium, at high spatial and temporal resolution. Despite the impact it has already had on the fields of cardiac arrhythmias and whole-heart computational modeling, present-day system designs precludes its adoption by the broader cardiovascular research community because of their high costs. Taking advantage of recent technological advances, we developed and validated low-cost optical mapping systems for panoramic imaging using Langendorff-perfused pig hearts, a clinically-relevant model in basic research and bioengineering. By significantly lowering financial thresholds, this powerful cardiac electrophysiology imaging modality may gain wider use in research and, even, teaching laboratories, which we substantiated using the lower-cost Langendorff-perfused rabbit heart model.

Low-Cost Optical Mapping Systems for Panoramic Imaging of Complex Arrhythmias and Drug-Action in Translational Heart Models.

PubMed

Lee, Peter; Calvo, Conrado J; Alfonso-Almazán, José M; Quintanilla, Jorge G; Chorro, Francisco J; Yan, Ping; Loew, Leslie M; Filgueiras-Rama, David; Millet, José

2017-02-27

Panoramic optical mapping is the primary method for imaging electrophysiological activity from the entire outer surface of Langendorff-perfused hearts. To date, it is the only method of simultaneously measuring multiple key electrophysiological parameters, such as transmembrane voltage and intracellular free calcium, at high spatial and temporal resolution. Despite the impact it has already had on the fields of cardiac arrhythmias and whole-heart computational modeling, present-day system designs precludes its adoption by the broader cardiovascular research community because of their high costs. Taking advantage of recent technological advances, we developed and validated low-cost optical mapping systems for panoramic imaging using Langendorff-perfused pig hearts, a clinically-relevant model in basic research and bioengineering. By significantly lowering financial thresholds, this powerful cardiac electrophysiology imaging modality may gain wider use in research and, even, teaching laboratories, which we substantiated using the lower-cost Langendorff-perfused rabbit heart model.

Atomic force microscopy as an advanced tool in neuroscience

PubMed Central

Jembrek, Maja Jazvinšćak; Šimić, Goran; Hof, Patrick R.; Šegota, Suzana

2015-01-01

This review highlights relevant issues about applications and improvements of atomic force microscopy (AFM) toward a better understanding of neurodegenerative changes at the molecular level with the hope of contributing to the development of effective therapeutic strategies for neurodegenerative illnesses. The basic principles of AFM are briefly discussed in terms of evaluation of experimental data, including the newest PeakForce Quantitative Nanomechanical Mapping (QNM) and the evaluation of Young’s modulus as the crucial elasticity parameter. AFM topography, revealed in imaging mode, can be used to monitor changes in live neurons over time, representing a valuable tool for high-resolution detection and monitoring of neuronal morphology. The mechanical properties of living cells can be quantified by force spectroscopy as well as by new AFM. A variety of applications are described, and their relevance for specific research areas discussed. In addition, imaging as well as non-imaging modes can provide specific information, not only about the structural and mechanical properties of neuronal membranes, but also on the cytoplasm, cell nucleus, and particularly cytoskeletal components. Moreover, new AFM is able to provide detailed insight into physical structure and biochemical interactions in both physiological and pathophysiological conditions. PMID:28123795

A general framework to learn surrogate relevance criterion for atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-09-01

Multi-atlas based image segmentation sees great opportunities in the big data era but also faces unprecedented challenges in identifying positive contributors from extensive heterogeneous data. To assess data relevance, image similarity criteria based on various image features widely serve as surrogates for the inaccessible geometric agreement criteria. This paper proposes a general framework to learn image based surrogate relevance criteria to better mimic the behaviors of segmentation based oracle geometric relevance. The validity of its general rationale is verified in the specific context of fusion set selection for image segmentation. More specifically, we first present a unified formulation for surrogate relevance criteria and model the neighborhood relationship among atlases based on the oracle relevance knowledge. Surrogates are then trained to be small for geometrically relevant neighbors and large for irrelevant remotes to the given targets. The proposed surrogate learning framework is verified in corpus callosum segmentation. The learned surrogates demonstrate superiority in inferring the underlying oracle value and selecting relevant fusion set, compared to benchmark surrogates.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2001-01-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Kulkarni, Ajinkya; Maskey, Manil; Bakare, Rohan; Basyal, Sabin; Li, Xiang; Flynn, Shannon

2014-01-01

Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.

Time-Optimized High-Resolution Readout-Segmented Diffusion Tensor Imaging

PubMed Central

Reishofer, Gernot; Koschutnig, Karl; Langkammer, Christian; Porter, David; Jehna, Margit; Enzinger, Christian; Keeling, Stephen; Ebner, Franz

2013-01-01

Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min) generates results comparable to the un-regularized data with three averages (48 min). This significant reduction in scan time renders high resolution (1×1×2.5 mm3) diffusion tensor imaging of the entire brain applicable in a clinical context. PMID:24019951

Digitization of medical documents: an X-Windows application for fast scanning.

PubMed

Muñoz, A; Salvador, C H; Gonzalez, M A; Dueñas, A

1992-01-01

This paper deals with digitization, using a commercial scanner, of medical documents as still images for introduction into a computer-based Information System. Document management involves storing, editing and transmission. This task has usually been approached from the perspective of the difficulties posed by radiologic images because of their indisputable qualitative and quantitative significance. However, healthcare activities require the management of many other types of documents and involve the requirements of numerous users. One key to document management will be the availability of a digitizer to deal with the greatest possible number of different types of documents. This paper describes the relevant aspects of documents and the technical specifications that digitizers must fulfill. The concept of document type is introduced as the ideal set of digitizing parameters for a given document. The use of document type parameters can drastically reduce the time the user spends in scanning sessions. Presentation is made of an application based on Unix, X-Windows and OSF/Motif, with a GPIB interface, implemented around the document type concept. Finally, the results of the evaluation of the application are presented, focusing on the user interface, as well as on the viewing of color images in an X-Windows environment and the use of lossy algorithms in the compression of medical images.

Classification of trabeculae into three-dimensional rodlike and platelike structures via local inertial anisotropy.

PubMed

Vasilić, Branimir; Rajapakse, Chamith S; Wehrli, Felix W

2009-07-01

Trabecular bone microarchitecture is a significant determinant of the bone's mechanical properties and is thus of major clinical relevance in predicting fracture risk. The three-dimensional nature of trabecular bone is characterized by parameters describing scale, topology, and orientation of structural elements. However, none of the current methods calculates all three types of parameters simultaneously and in three dimensions. Here the authors present a method that produces a continuous classification of voxels as belonging to platelike or rodlike structures that determines their orientation and estimates their thickness. The method, dubbed local inertial anisotropy (LIA), treats the image as a distribution of mass density and the orientation of trabeculae is determined from a locally calculated tensor of inertia at each voxel. The orientation entropies of rods and plates are introduced, which can provide new information about microarchitecture not captured by existing parameters. The robustness of the method to noise corruption, resolution reduction, and image rotation is demonstrated. Further, the method is compared with established three-dimensional parameters including the structure-model index and topological surface-to-curve ratio. Finally, the method is applied to data acquired in a previous translational pilot study showing that the trabecular bone of untreated hypogonadal men is less platelike than that of their eugonadal peers.

Successful treatment of severe Clostridium difficile infection by administration of crushed fidaxomicin via a nasogastric tube in a critically ill patient.

PubMed

Arends, Sven; Defosse, Jerome; Diaz, Cori; Wappler, Frank; Sakka, Samir G

2017-02-01

To report the successful use of crushed fidaxomicin via a nasogastric tube for treatment of a severe Clostridium difficile infection in a critically ill patient. Clinical observation of a patient, images of abdominal computed tomography, antimicrobial therapy and course of infection parameters. Relevant information contained in the medical observation of the patient and selection of image and laboratory parameters performed in the patient. We report a case of a 79-year old patient who developed septic shock with an increasing need for norepinephrine and acute renal failure due to a severe Clostridium difficile infection. Antimicrobial therapy with vancomycin via a nasogastric tube and metronidazole i.v. did not lead to improvement, infection parameters further increased, and the clinical condition became increasingly impaired. After 10 days, antimicrobial therapy was changed to fidaxomicin, crushed and administered via nasogastric tube. Within 24hours, infection parameters decreased. Further diarrhoea ceased and stool samples were negative for Clostridium difficile antigen. Our case confirms that administration of fidaxomicin via a nasogastric tube was safe and effective in this patient. Further studies are needed to evaluate the efficacy of this strategy in critically ill patients systematically. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Image quality phantom and parameters for high spatial resolution small-animal SPECT

NASA Astrophysics Data System (ADS)

Visser, Eric P.; Harteveld, Anita A.; Meeuwis, Antoi P. W.; Disselhorst, Jonathan A.; Beekman, Freek J.; Oyen, Wim J. G.; Boerman, Otto C.

2011-10-01

At present, generally accepted standards to characterize small-animal single photon emission tomographs (SPECT) do not exist. Whereas for small-animal positron emission tomography (PET), the NEMA NU 4-2008 guidelines are available, such standards are still lacking for small-animal SPECT. More specifically, a dedicated image quality (IQ) phantom and corresponding IQ parameters are absent. The structures of the existing PET IQ phantom are too large to fully characterize the sub-millimeter spatial resolution of modern multi-pinhole SPECT scanners, and its diameter will not fit into all scanners when operating in high spatial resolution mode. We therefore designed and constructed an adapted IQ phantom with smaller internal structures and external diameter, and a facility to guarantee complete filling of the smallest rods. The associated IQ parameters were adapted from NEMA NU 4. An additional parameter, effective whole-body sensitivity, was defined since this was considered relevant in view of the variable size of the field of view and the use of multiple bed positions as encountered in modern small-animal SPECT scanners. The usefulness of the phantom was demonstrated for 99mTc in a USPECT-II scanner operated in whole-body scanning mode using a multi-pinhole mouse collimator with 0.6 mm pinhole diameter.

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE PAGES

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni; ...

2015-05-13

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

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

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

PubMed

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Photometric correction for an optical CCD-based system based on the sparsity of an eight-neighborhood gray gradient.

PubMed

Zhang, Yuzhong; Zhang, Yan

2016-07-01

In an optical measurement and analysis system based on a CCD, due to the existence of optical vignetting and natural vignetting, photometric distortion, in which the intensity falls off away from the image center, affects the subsequent processing and measuring precision severely. To deal with this problem, an easy and straightforward method used for photometric distortion correction is presented in this paper. This method introduces a simple polynomial fitting model of the photometric distortion function and employs a particle swarm optimization algorithm to get these model parameters by means of a minimizing eight-neighborhood gray gradient. Compared with conventional calibration methods, this method can obtain the profile information of photometric distortion from only a single common image captured by the optical CCD-based system, with no need for a uniform luminance area source used as a standard reference source and relevant optical and geometric parameters in advance. To illustrate the applicability of this method, numerical simulations and photometric distortions with different lens parameters are evaluated using this method in this paper. Moreover, the application example of temperature field correction for casting billets also demonstrates the effectiveness of this method. The experimental results show that the proposed method is able to achieve the maximum absolute error for vignetting estimation of 0.0765 and the relative error for vignetting estimation from different background images of 3.86%.

T2 values of articular cartilage in clinically relevant subregions of the asymptomatic knee.

PubMed

Surowiec, Rachel K; Lucas, Erin P; Fitzcharles, Eric K; Petre, Benjamin M; Dornan, Grant J; Giphart, J Erik; LaPrade, Robert F; Ho, Charles P

2014-06-01

In order for T2 mapping to become more clinically applicable, reproducible subregions and standardized T2 parameters must be defined. This study sought to: (1) define clinically relevant subregions of knee cartilage using bone landmarks identifiable on both MR images and during arthroscopy and (2) determine healthy T2 values and T2 texture parameters within these subregions. Twenty-five asymptomatic volunteers (age 18-35) were evaluated with a sagittal T2 mapping sequence. Manual segmentation was performed by three raters, and cartilage was divided into twenty-one subregions modified from the International Cartilage Repair Society Articular Cartilage Mapping System. Mean T2 values and texture parameters (entropy, variance, contrast, homogeneity) were recorded for each subregion, and inter-rater and intra-rater reliability was assessed. The central regions of the condyles had significantly higher T2 values than the posterior regions (P < 0.05) and higher variance than the posterior region on the medial side (P < 0.001). The central trochlea had significantly greater T2 values than the anterior and posterior condyles. The central lateral plateau had lower T2 values, lower variance, higher homogeneity, and lower contrast than nearly all subregions in the tibia. The central patellar regions had higher entropy than the superior and inferior regions (each P ≤ 0.001). Repeatability was good to excellent for all subregions. Significant differences in mean T2 values and texture parameters were found between subregions in this carefully selected asymptomatic population, which suggest that there is normal variation of T2 values within the knee joint. The clinically relevant subregions were found to be robust as demonstrated by the overall high repeatability.

EOS Terra Validation Program

NASA Technical Reports Server (NTRS)

Starr, David

2000-01-01

The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multi-Angle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Measurements of Pollution in the Troposphere (MOPITT). In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS) AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2 though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community.

Combining aneuploidy and dysplasia for colitis' cancer risk assessment outperforms current surveillance efficiency: a meta-analysis.

PubMed

Meyer, Rüdiger; Freitag-Wolf, Sandra; Blindow, Silke; Büning, Jürgen; Habermann, Jens K

2017-02-01

Cancer risk assessment for ulcerative colitis patients by evaluating histological changes through colonoscopy surveillance is still challenging. Thus, additional parameters of high prognostic impact for the development of colitis-associated carcinoma are necessary. This meta-analysis was conducted to clarify the value of aneuploidy as predictor for individual cancer risk compared with current surveillance parameters. A systematic web-based search identified studies published in English that addressed the relevance of the ploidy status for individual cancer risk during surveillance in comparison to neoplastic mucosal changes. The resulting data were included into a meta-analysis, and odds ratios (OR) were calculated for aneuploidy or dysplasia or aneuploidy plus dysplasia. Twelve studies addressing the relevance of aneuploidy compared to dyplasia were comprehensively evaluated and further used for meta-analysis. The meta-analysis revealed that aneuploidy (OR 5.31 [95 % CI 2.03, 13.93]) is an equally effective parameter for cancer risk assessment in ulcerative colitis patients as dysplasia (OR 4.93 [1.61, 15.11]). Strikingly, the combined assessment of dysplasia and aneuploidy is superior compared to applying each parameter alone (OR 8.99 [3.08, 26.26]). This meta-analysis reveals that aneuploidy is an equally effective parameter for individual cancer risk assessment in ulcerative colitis as the detection of dysplasia. More important, the combined assessment of dysplasia and aneuploidy outperforms the use of each parameter alone. We suggest image cytometry for ploidy assessment to become an additional feature of consensus criteria to individually assess cancer risk in UC.

[Research as attractiveness parameter for young surgeons].

PubMed

Vollmar, B

2012-04-01

Increasing concern has been expressed about the significant shortage of new trainees in surgery. As research in the context of surgical education and training is an essential element of attraction for the field of surgery, there is an urgent priority to implement clear room for research in the concepts of education and training. In this article the relevance of both the thesis accompanying the study and research training during surgical residency for the clinical self-image, personal satisfaction and academic development of young surgeons will be presented.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries

PubMed Central

Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-01-01

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability. PMID:29144388

Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients.

PubMed

Mayer, Markus A; Hornegger, Joachim; Mardin, Christian Y; Tornow, Ralf P

2010-11-08

Automated measurements of the retinal nerve fiber layer thickness on circular OCT B-Scans provide physicians additional parameters for glaucoma diagnosis. We propose a novel retinal nerve fiber layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms. A quantitative evaluation comparing the automated segmentation results to manually corrected segmentations from three reviewers is performed. A total of 72 scans from glaucoma patients and 132 scans from normal subjects, all from different persons, composed the database for the evaluation of the segmentation algorithm. A mean absolute error per A-Scan of 2.9 µm was achieved on glaucomatous eyes, and 3.6 µm on healthy eyes. The mean absolute segmentation error over all A-Scans lies below 10 µm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis.

Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients

PubMed Central

Mayer, Markus A.; Hornegger, Joachim; Mardin, Christian Y.; Tornow, Ralf P.

2010-01-01

Automated measurements of the retinal nerve fiber layer thickness on circular OCT B-Scans provide physicians additional parameters for glaucoma diagnosis. We propose a novel retinal nerve fiber layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms. A quantitative evaluation comparing the automated segmentation results to manually corrected segmentations from three reviewers is performed. A total of 72 scans from glaucoma patients and 132 scans from normal subjects, all from different persons, composed the database for the evaluation of the segmentation algorithm. A mean absolute error per A-Scan of 2.9 µm was achieved on glaucomatous eyes, and 3.6 µm on healthy eyes. The mean absolute segmentation error over all A-Scans lies below 10 µm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis. PMID:21258556

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

NASA Technical Reports Server (NTRS)

Kiang, Richard; Adimi, Farida; Kempler, Steven

2008-01-01

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Flame analysis using image processing techniques

NASA Astrophysics Data System (ADS)

Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

2018-04-01

This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Litjens, G. J. S.; Elliott, R.; Shih, N.; Feldman, M.; Barentsz, J. O.; Hulsbergen-van de Kaa, C. A.; Kovacs, I.; Huisman, H. J.; Madabhushi, A.

2014-03-01

Learning how to separate benign confounders from prostate cancer is important because the imaging characteristics of these confounders are poorly understood. Furthermore, the typical representations of the MRI parameters might not be enough to allow discrimination. The diagnostic uncertainty this causes leads to a lower diagnostic accuracy. In this paper a new cascaded classifier is introduced to separate prostate cancer and benign confounders on MRI in conjunction with specific computer-extracted features to distinguish each of the benign classes (benign prostatic hyperplasia (BPH), inflammation, atrophy or prostatic intra-epithelial neoplasia (PIN). In this study we tried to (1) calculate different mathematical representations of the MRI parameters which more clearly express subtle differences between different classes, (2) learn which of the MRI image features will allow to distinguish specific benign confounders from prostate cancer, and (2) find the combination of computer-extracted MRI features to best discriminate cancer from the confounding classes using a cascaded classifier. One of the most important requirements for identifying MRI signatures for adenocarcinoma, BPH, atrophy, inflammation, and PIN is accurate mapping of the location and spatial extent of the confounder and cancer categories from ex vivo histopathology to MRI. Towards this end we employed an annotated prostatectomy data set of 31 patients, all of whom underwent a multi-parametric 3 Tesla MRI prior to radical prostatectomy. The prostatectomy slides were carefully co-registered to the corresponding MRI slices using an elastic registration technique. We extracted texture features from the T2-weighted imaging, pharmacokinetic features from the dynamic contrast enhanced imaging and diffusion features from the diffusion-weighted imaging for each of the confounder classes and prostate cancer. These features were selected because they form the mainstay of clinical diagnosis. Relevant features for each of the classes were selected using maximum relevance minimum redundancy feature selection, allowing us to perform classifier independent feature selection. The selected features were then incorporated in a cascading classifier, which can focus on easier sub-tasks at each stage, leaving the more difficult classification tasks for later stages. Results show that distinct features are relevant for each of the benign classes, for example the fraction of extra-vascular, extra-cellular space in a voxel is a clear discriminator for inflammation. Furthermore, the cascaded classifier outperforms both multi-class and one-shot classifiers in overall accuracy for discriminating confounders from cancer: 0.76 versus 0.71 and 0.62.

Tag-Based Social Image Search: Toward Relevant and Diverse Results

NASA Astrophysics Data System (ADS)

Yang, Kuiyuan; Wang, Meng; Hua, Xian-Sheng; Zhang, Hong-Jiang

Recent years have witnessed a great success of social media websites. Tag-based image search is an important approach to access the image content of interest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the content of images and their associated tags. First, it estimates the relevance scores of images with respect to the query term based on both visual information of images and semantic information of associated tags. Then semantic similarities of social images are estimated based on their tags. Based on the relevance scores and the similarities, the ranking list is generated by a greedy ordering algorithm which optimizes Average Diverse Precision (ADP), a novel measure that is extended from the conventional Average Precision (AP). Comprehensive experiments and user studies demonstrate the effectiveness of the approach.

Imaging characteristics of photogrammetric camera systems

USGS Publications Warehouse

Welch, R.; Halliday, J.

1973-01-01

In view of the current interest in high-altitude and space photographic systems for photogrammetric mapping, the United States Geological Survey (U.S.G.S.) undertook a comprehensive research project designed to explore the practical aspects of applying the latest image quality evaluation techniques to the analysis of such systems. The project had two direct objectives: (1) to evaluate the imaging characteristics of current U.S.G.S. photogrammetric camera systems; and (2) to develop methodologies for predicting the imaging capabilities of photogrammetric camera systems, comparing conventional systems with new or different types of systems, and analyzing the image quality of photographs. Image quality was judged in terms of a number of evaluation factors including response functions, resolving power, and the detectability and measurability of small detail. The limiting capabilities of the U.S.G.S. 6-inch and 12-inch focal length camera systems were established by analyzing laboratory and aerial photographs in terms of these evaluation factors. In the process, the contributing effects of relevant parameters such as lens aberrations, lens aperture, shutter function, image motion, film type, and target contrast procedures for analyzing image quality and predicting and comparing performance capabilities. ?? 1973.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Can we trust the calculation of texture indices of CT images? A phantom study.

PubMed

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

PubMed

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Oncologic relevance of magnetic resonance imaging-detected threatened mesorectal fascia for patients with mid or low rectal cancer: A longitudinal analysis before and after long-course, concurrent chemoradiotherapy.

PubMed

Son, Il Tae; Kim, Young Hoon; Lee, Kyoung Ho; Kang, Sung Il; Kim, Duck-Woo; Shin, Eun; Lee, Keun-Wook; Ahn, Soyeon; Kim, Jae-Sung; Kang, Sung-Bum

2017-07-01

The oncologic importance of threatened mesorectal fascia detected with magnetic resonance imaging is obscured by the heterogeneity of preoperative treatments. We evaluated the oncologic relevance of threatened mesorectal fascia detected with consecutive magnetic resonance imaging performed before and after long-course, concurrent chemoradiotherapy (LCRT) for mid or low rectal cancer. We evaluated 196 patients who underwent total mesorectal excision with LCRT. Threatened mesorectal fascia was defined as a shortest distance from tumor to mesorectal fascia of ≤ 1 mm on magnetic resonance imaging. Multivariate analyses for disease-free survival using magnetic resonance imaging-based parameters were conducted with a Cox proportional hazard model before and after LCRT, respectively. The pathologic positivity of the circumferential resection margin was greater for threatened mesorectal fascia than for clear mesorectal fascia (pre-LCRT, 14.8% vs 3.0%, P = .004; post-LCRT, 15.4% vs 4.5%, P = .025). At a median follow-up of 68 months, 3-year disease-free survival was worse for threatened mesorectal fascia than for clear mesorectal fascia (pre-LCRT, 77.0% vs 88.1%, P = .023; post-LCRT, 76.9% vs 86.6%, P = .029). On multivariate analyses, threatened mesorectal fascia on pre-LCRT magnetic resonance imaging was an independent factor for poor disease-free survival (hazard ratio = 2.153, 95% confidence interval, 1.07-4.32, P = .031), whereas threatened mesorectal fascia on post-LCRT magnetic resonance imaging was not (hazard ratio = 1.689, 95% confidence interval, 0.77-3.66, P = .189). This study confirms that magnetic resonance imaging-detected threatened mesorectal fascia predicts poor oncologic outcomes for mid or low rectal cancer and shows that the diagnostic performance of pre-LCRT magnetic resonance imaging is different from that of post-LCRT magnetic resonance imaging. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling enzymatic hydrolysis of lignocellulosic substrates using confocal fluorescence microscopy I: filter paper cellulose.

PubMed

Luterbacher, Jeremy S; Moran-Mirabal, Jose M; Burkholder, Eric W; Walker, Larry P

2015-01-01

Enzymatic hydrolysis is one of the critical steps in depolymerizing lignocellulosic biomass into fermentable sugars for further upgrading into fuels and/or chemicals. However, many studies still rely on empirical trends to optimize enzymatic reactions. An improved understanding of enzymatic hydrolysis could allow research efforts to follow a rational design guided by an appropriate theoretical framework. In this study, we present a method to image cellulosic substrates with complex three-dimensional structure, such as filter paper, undergoing hydrolysis under conditions relevant to industrial saccharification processes (i.e., temperature of 50°C, using commercial cellulolytic cocktails). Fluorescence intensities resulting from confocal images were used to estimate parameters for a diffusion and reaction model. Furthermore, the observation of a relatively constant bound enzyme fluorescence signal throughout hydrolysis supported our modeling assumption regarding the structure of biomass during hydrolysis. The observed behavior suggests that pore evolution can be modeled as widening of infinitely long slits. The resulting model accurately predicts the concentrations of soluble carbohydrates obtained from independent saccharification experiments conducted in bulk, demonstrating its relevance to biomass conversion work. © 2014 Wiley Periodicals, Inc.

Investigation of optimization-based reconstruction with an image-total-variation constraint in PET

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Ye, Jinghan; Chen, Buxin; Perkins, Amy E.; Rose, Sean; Sidky, Emil Y.; Kao, Chien-Min; Xia, Dan; Tung, Chi-Hua; Pan, Xiaochuan

2016-08-01

Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.

Non-invasive neuroimaging using near-infrared light

NASA Technical Reports Server (NTRS)

Strangman, Gary; Boas, David A.; Sutton, Jeffrey P.

2002-01-01

This article reviews diffuse optical brain imaging, a technique that employs near-infrared light to non-invasively probe the brain for changes in parameters relating to brain function. We describe the general methodology, including types of measurements and instrumentation (including the tradeoffs inherent in the various instrument components), and the basic theory required to interpret the recorded data. A brief review of diffuse optical applications is included, with an emphasis on research that has been done with psychiatric populations. Finally, we discuss some practical issues and limitations that are relevant when conducting diffuse optical experiments. We find that, while diffuse optics can provide substantial advantages to the psychiatric researcher relative to the alternative brain imaging methods, the method remains substantially underutilized in this field.

Hubble Space Telescope: Faint object camera instrument handbook. Version 2.0

NASA Technical Reports Server (NTRS)

Paresce, Francesco (Editor)

1990-01-01

The Faint Object Camera (FOC) is a long focal ratio, photon counting device designed to take high resolution two dimensional images of areas of the sky up to 44 by 44 arcseconds squared in size, with pixel dimensions as small as 0.0007 by 0.0007 arcseconds squared in the 1150 to 6500 A wavelength range. The basic aim of the handbook is to make relevant information about the FOC available to a wide range of astronomers, many of whom may wish to apply for HST observing time. The FOC, as presently configured, is briefly described, and some basic performance parameters are summarized. Also included are detailed performance parameters and instructions on how to derive approximate FOC exposure times for the proposed targets.

Dose, image quality and spine modeling assessment of biplanar EOS micro-dose radiographs for the follow-up of in-brace adolescent idiopathic scoliosis patients.

PubMed

Morel, Baptiste; Moueddeb, Sonia; Blondiaux, Eleonore; Richard, Stephen; Bachy, Manon; Vialle, Raphael; Ducou Le Pointe, Hubert

2018-05-01

The aim of this study was to compare the radiation dose, image quality and 3D spine parameter measurements of EOS low-dose and micro-dose protocols for in-brace adolescent idiopathic scoliosis (AIS) patients. We prospectively included 25 consecutive patients (20 females, 5 males) followed for AIS and undergoing brace treatment. The mean age was 12 years (SD 2 years, range 8-15 years). For each patient, in-brace biplanar EOS radiographs were acquired in a standing position using both the conventional low-dose and micro-dose protocols. Dose area product (DAP) was systematically recorded. Diagnostic image quality was qualitatively assessed by two radiologists for visibility of anatomical structures. The reliability of 3D spine modeling between two operators was quantitatively evaluated for the most clinically relevant 3D radiological parameters using intraclass correlation coefficient (ICC). The mean DAP for the posteroanterior and lateral acquisitions was 300 ± 134 and 433 ± 181 mGy cm 2 for the low-dose radiographs, and 41 ± 19 and 81 ± 39 mGy cm 2 for micro-dose radiographs. Image quality was lower with the micro-dose protocol. The agreement was "good" to "very good" for all measured clinical parameters when comparing the low-dose and micro-dose protocols (ICC > 0.73). The micro-dose protocol substantially reduced the delivered dose (by a factor of 5-7 compared to the low-dose protocol) in braced children with AIS. Although image quality was reduced, the micro-dose protocol proved to be adapted to radiological follow-up, with adequate image quality and reliable clinical measurements. These slides can be retrieved under Electronic Supplementary Material.

A suite of phantom-based test methods for assessing image quality of photoacoustic tomography systems

NASA Astrophysics Data System (ADS)

Vogt, William C.; Jia, Congxian; Wear, Keith A.; Garra, Brian S.; Pfefer, T. Joshua

2017-03-01

As Photoacoustic Tomography (PAT) matures and undergoes clinical translation, objective performance test methods are needed to facilitate device development, regulatory clearance and clinical quality assurance. For mature medical imaging modalities such as CT, MRI, and ultrasound, tissue-mimicking phantoms are frequently incorporated into consensus standards for performance testing. A well-validated set of phantom-based test methods is needed for evaluating performance characteristics of PAT systems. To this end, we have constructed phantoms using a custom tissue-mimicking material based on PVC plastisol with tunable, biologically-relevant optical and acoustic properties. Each phantom is designed to enable quantitative assessment of one or more image quality characteristics including 3D spatial resolution, spatial measurement accuracy, ultrasound/PAT co-registration, uniformity, penetration depth, geometric distortion, sensitivity, and linearity. Phantoms contained targets including high-intensity point source targets and dye-filled tubes. This suite of phantoms was used to measure the dependence of performance of a custom PAT system (equipped with four interchangeable linear array transducers of varying design) on design parameters (e.g., center frequency, bandwidth, element geometry). Phantoms also allowed comparison of image artifacts, including surface-generated clutter and bandlimited sensing artifacts. Results showed that transducer design parameters create strong variations in performance including a trade-off between resolution and penetration depth, which could be quantified with our method. This study demonstrates the utility of phantom-based image quality testing in device performance assessment, which may guide development of consensus standards for PAT systems.

Semi-automation of Doppler Spectrum Image Analysis for Grading Aortic Valve Stenosis Severity.

PubMed

Niakšu, O; Balčiunaitė, G; Kizlaitis, R J; Treigys, P

2016-01-01

Doppler echocardiography analysis has become a golden standard in the modern diagnosis of heart diseases. In this paper, we propose a set of techniques for semi-automated parameter extraction for aortic valve stenosis severity grading. The main objectives of the study is to create echocardiography image processing techniques, which minimize manual image processing work of clinicians and leads to reduced human error rates. Aortic valve and left ventricle output tract spectrogram images have been processed and analyzed. A novel method was developed to trace systoles and to extract diagnostic relevant features. The results of the introduced method have been compared to the findings of the participating cardiologists. The experimental results showed the accuracy of the proposed method is comparable to the manual measurement performed by medical professionals. Linear regression analysis of the calculated parameters and the measurements manually obtained by the cardiologists resulted in the strongly correlated values: peak systolic velocity's and mean pressure gradient's R2 both equal to 0.99, their means' differences equal to 0.02 m/s and 4.09 mmHg, respectively, and aortic valve area's R2 of 0.89 with the two methods means' difference of 0.19 mm. The introduced Doppler echocardiography images processing method can be used as a computer-aided assistance in the aortic valve stenosis diagnostics. In our future work, we intend to improve precision of left ventricular outflow tract spectrogram measurements and apply data mining methods to propose a clinical decision support system for diagnosing aortic valve stenosis.

Multiparametric evaluation of hindlimb ischemia using time-series indocyanine green fluorescence imaging.

PubMed

Guang, Huizhi; Cai, Chuangjian; Zuo, Simin; Cai, Wenjuan; Zhang, Jiulou; Luo, Jianwen

2017-03-01

Peripheral arterial disease (PAD) can further cause lower limb ischemia. Quantitative evaluation of the vascular perfusion in the ischemic limb contributes to diagnosis of PAD and preclinical development of new drug. In vivo time-series indocyanine green (ICG) fluorescence imaging can noninvasively monitor blood flow and has a deep tissue penetration. The perfusion rate estimated from the time-series ICG images is not enough for the evaluation of hindlimb ischemia. The information relevant to the vascular density is also important, because angiogenesis is an essential mechanism for post-ischemic recovery. In this paper, a multiparametric evaluation method is proposed for simultaneous estimation of multiple vascular perfusion parameters, including not only the perfusion rate but also the vascular perfusion density and the time-varying ICG concentration in veins. The target method is based on a mathematical model of ICG pharmacokinetics in the mouse hindlimb. The regression analysis performed on the time-series ICG images obtained from a dynamic reflectance fluorescence imaging system. The results demonstrate that the estimated multiple parameters are effective to quantitatively evaluate the vascular perfusion and distinguish hypo-perfused tissues from well-perfused tissues in the mouse hindlimb. The proposed multiparametric evaluation method could be useful for PAD diagnosis. The estimated perfusion rate and vascular perfusion density maps (left) and the time-varying ICG concentration in veins of the ankle region (right) of the normal and ischemic hindlimbs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic optimization high-speed high-resolution OCT retinal imaging at 1μm

NASA Astrophysics Data System (ADS)

Cua, Michelle; Liu, Xiyun; Miao, Dongkai; Lee, Sujin; Lee, Sieun; Bonora, Stefano; Zawadzki, Robert J.; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2015-03-01

High-resolution OCT retinal imaging is important in providing visualization of various retinal structures to aid researchers in better understanding the pathogenesis of vision-robbing diseases. However, conventional optical coherence tomography (OCT) systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking optical coherence tomography (OCT) system with automatic optimization for high-resolution, extended-focal-range clinical retinal imaging. A variable-focus liquid lens was added to correct for de-focus in real-time. A GPU-accelerated segmentation and optimization was used to provide real-time layer-specific enface visualization as well as depth-specific focus adjustment. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the ONH, from which we extracted clinically-relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Imaging single cells in a beam of live cyanobacteria with an X-ray laser.

PubMed

van der Schot, Gijs; Svenda, Martin; Maia, Filipe R N C; Hantke, Max; DePonte, Daniel P; Seibert, M Marvin; Aquila, Andrew; Schulz, Joachim; Kirian, Richard; Liang, Mengning; Stellato, Francesco; Iwan, Bianca; Andreasson, Jakob; Timneanu, Nicusor; Westphal, Daniel; Almeida, F Nunes; Odic, Dusko; Hasse, Dirk; Carlsson, Gunilla H; Larsson, Daniel S D; Barty, Anton; Martin, Andrew V; Schorb, Sebastian; Bostedt, Christoph; Bozek, John D; Rolles, Daniel; Rudenko, Artem; Epp, Sascha; Foucar, Lutz; Rudek, Benedikt; Hartmann, Robert; Kimmel, Nils; Holl, Peter; Englert, Lars; Duane Loh, Ne-Te; Chapman, Henry N; Andersson, Inger; Hajdu, Janos; Ekeberg, Tomas

2015-02-11

There exists a conspicuous gap of knowledge about the organization of life at mesoscopic levels. Ultra-fast coherent diffractive imaging with X-ray free-electron lasers can probe structures at the relevant length scales and may reach sub-nanometer resolution on micron-sized living cells. Here we show that we can introduce a beam of aerosolised cyanobacteria into the focus of the Linac Coherent Light Source and record diffraction patterns from individual living cells at very low noise levels and at high hit ratios. We obtain two-dimensional projection images directly from the diffraction patterns, and present the results as synthetic X-ray Nomarski images calculated from the complex-valued reconstructions. We further demonstrate that it is possible to record diffraction data to nanometer resolution on live cells with X-ray lasers. Extension to sub-nanometer resolution is within reach, although improvements in pulse parameters and X-ray area detectors will be necessary to unlock this potential.

Effects of pipette modulation and imaging distances on ion currents measured with scanning ion conductance microscopy (SICM).

PubMed

Chen, Chiao-Chen; Baker, Lane A

2011-01-07

Local conductance variations can be estimated by measuring ion current magnitudes with scanning ion conductance microscopy (SICM). Factors which influence image quality and quantitation of ion currents measured with SICM have been evaluated. Specifically, effects of probe-sample separation and pipette modulation have been systematically studied for the case of imaging conductance variations at pores in a polymer membrane under transmembrane concentration gradients. The influence of probe-sample separation on ion current images was evaluated using distance-modulated (ac) feedback. Approach curves obtained using non-modulated (dc) feedback were also recorded to determine the relative influence of pipette-generated convection by comparison of ion currents measured with both ac and dc feedback modes. To better interpret results obtained, comparison to a model based on a disk-shaped geometry for nanopores in the membrane, as well as relevant position-dependent parameters of the experiment is described. These results advance our current understanding of conductance measurements with SICM.

Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey

PubMed Central

Almazroa, Ahmed; Burman, Ritambhar; Raahemifar, Kaamran; Lakshminarayanan, Vasudevan

2015-01-01

Glaucoma is the second leading cause of loss of vision in the world. Examining the head of optic nerve (cup-to-disc ratio) is very important for diagnosing glaucoma and for patient monitoring after diagnosis. Images of optic disc and optic cup are acquired by fundus camera as well as Optical Coherence Tomography. The optic disc and optic cup segmentation techniques are used to isolate the relevant parts of the retinal image and to calculate the cup-to-disc ratio. The main objective of this paper is to review segmentation methodologies and techniques for the disc and cup boundaries which are utilized to calculate the disc and cup geometrical parameters automatically and accurately to help the professionals in the glaucoma to have a wide view and more details about the optic nerve head structure using retinal fundus images. We provide a brief description of each technique, highlighting its classification and performance metrics. The current and future research directions are summarized and discussed. PMID:26688751

Combined Néel and Brown rotational Langevin dynamics in magnetic particle imaging, sensing, and therapy

NASA Astrophysics Data System (ADS)

Reeves, Daniel B.; Weaver, John B.

2015-11-01

Magnetic nanoparticles have been studied intensely because of their possible uses in biomedical applications. Biosensing using the rotational freedom of particles has been used to detect biomarkers for cancer, hyperthermia therapy has been used to treat tumors, and magnetic particle imaging is a promising new imaging modality that can spatially resolve the concentration of nanoparticles. There are two mechanisms by which the magnetization of a nanoparticle can rotate, a fact that poses a challenge for applications that rely on precisely one mechanism. The challenge is exacerbated by the high sensitivity of the dominant mechanism to applied fields. Here, we demonstrate stochastic Langevin equation simulations for the combined rotation in magnetic nanoparticles exposed to oscillating applied fields typical to these applications to both highlight the existing relevant theory and quantify which mechanism should occur in various parameter ranges.

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

PubMed

del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

2015-06-17

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

a Method for the Registration of Hemispherical Photographs and Tls Intensity Images

NASA Astrophysics Data System (ADS)

Schmidt, A.; Schilling, A.; Maas, H.-G.

2012-07-01

Terrestrial laser scanners generate dense and accurate 3D point clouds with minimal effort, which represent the geometry of real objects, while image data contains texture information of object surfaces. Based on the complementary characteristics of both data sets, a combination is very appealing for many applications, including forest-related tasks. In the scope of our research project, independent data sets of a plain birch stand have been taken by a full-spherical laser scanner and a hemispherical digital camera. Previously, both kinds of data sets have been considered separately: Individual trees were successfully extracted from large 3D point clouds, and so-called forest inventory parameters could be determined. Additionally, a simplified tree topology representation was retrieved. From hemispherical images, leaf area index (LAI) values, as a very relevant parameter for describing a stand, have been computed. The objective of our approach is to merge a 3D point cloud with image data in a way that RGB values are assigned to each 3D point. So far, segmentation and classification of TLS point clouds in forestry applications was mainly based on geometrical aspects of the data set. However, a 3D point cloud with colour information provides valuable cues exceeding simple statistical evaluation of geometrical object features and thus may facilitate the analysis of the scan data significantly.

Wrinkle and roughness measurement by the Antera 3D and its application for evaluation of cosmetic products.

PubMed

Messaraa, C; Metois, A; Walsh, M; Hurley, S; Doyle, L; Mansfield, A; O'Connor, C; Mavon, A

2018-01-24

Skin topographic measurements are of paramount importance in the field of dermo-cosmetic evaluation. The aim of this study was to investigate how the Antera 3D, a multi-purpose handheld camera, correlates with other topographic techniques and changes in skin topography following the use of a cosmetic product. Skin topographic measurements were collected on 26 female volunteers aged 45-70 years with the Antera 3D, the DermaTOP and image analysis on parallel-polarized pictures. Different filters for analysis from the Antera 3D were investigated for repeatability, correlations with other imaging techniques and ability to detect improvements of skin topography following application of a serum. Most of Antera 3D parameters were found to be strongly correlated with the DermaTOP parameters. No association was found between the Antera 3D parameters and measurements on parallel-polarized photographs. The measurements repeatability was comparable among the different filters for analysis, with the exception of wrinkle max depth and roughness Rt. Following a single application of a tightening serum, both Antera 3D wrinkles and texture parameters were able to record significant improvements, with the best improvements observed with the large filter. The Antera 3D demonstrated its relevance for cosmetic product evaluation. We also provide recommendations for the analysis based on our findings. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.

PubMed

Nketiah, Gabriel; Elschot, Mattijs; Kim, Eugene; Teruel, Jose R; Scheenen, Tom W; Bathen, Tone F; Selnæs, Kirsten M

2017-07-01

To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (K trans and V e ) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with K trans and V e . GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, K trans , and V e . The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

Spectral embedding finds meaningful (relevant) structure in image and microarray data

PubMed Central

Higgs, Brandon W; Weller, Jennifer; Solka, Jeffrey L

2006-01-01

Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method). This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent classification method, enabling the possibility of valid cross-experiment comparisons. Conclusion Results from the spectral method presented here exhibit the desirable properties of preserving meaningful nonlinear relationships in lower dimensional space and requiring minimal parameter fitting, providing a useful algorithm for purposes of visualization and classification across diverse datasets, a common challenge in systems biology. PMID:16483359

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feasibility of a low-dose orbital CT protocol with a knowledge-based iterative model reconstruction algorithm for evaluating Graves' orbitopathy.

PubMed

Lee, Ho-Joon; Kim, Jinna; Kim, Ki Wook; Lee, Seung-Koo; Yoon, Jin Sook

2018-06-23

To evaluate the clinical feasibility of low-dose orbital CT with a knowledge-based iterative model reconstruction (IMR) algorithm for evaluating Graves' orbitopathy. Low-dose orbital CT was performed with a CTDI vol of 4.4 mGy. In 12 patients for whom prior or subsequent non-low-dose orbital CT data obtained within 12 months were available, background noise, SNR, and CNR were compared for images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose 4 ), and IMR and non-low-dose CT images. Comparison of clinically relevant measurements for Graves' orbitopathy, such as rectus muscle thickness and retrobulbar fat area, was performed in a subset of 6 patients who underwent CT for causes other than Graves' orbitopathy, by using the Wilcoxon signed-rank test. The lens dose estimated from skin dosimetry on a phantom was 4.13 mGy, which was on average 59.34% lower than that of the non-low-dose protocols. Image quality in terms of background noise, SNR, and CNR was the best for IMR, followed by non-low-dose CT, iDose 4 , and FBP, in descending order. A comparison of clinically relevant measurements revealed no significant difference in the retrobulbar fat area and the inferior and medial rectus muscle thicknesses between the low-dose and non-low-dose CT images. Low-dose CT with IMR may be performed without significantly affecting the measurement of prognostic parameters for Graves' orbitopathy while lowering the lens dose and image noise. Copyright © 2018 Elsevier Inc. All rights reserved.

A programmable light engine for quantitative single molecule TIRF and HILO imaging.

PubMed

van 't Hoff, Marcel; de Sars, Vincent; Oheim, Martin

2008-10-27

We report on a simple yet powerful implementation of objective-type total internal reflection fluorescence (TIRF) and highly inclined and laminated optical sheet (HILO, a type of dark-field) illumination. Instead of focusing the illuminating laser beam to a single spot close to the edge of the microscope objective, we are scanning during the acquisition of a fluorescence image the focused spot in a circular orbit, thereby illuminating the sample from various directions. We measure parameters relevant for quantitative image analysis during fluorescence image acquisition by capturing an image of the excitation light distribution in an equivalent objective backfocal plane (BFP). Operating at scan rates above 1 MHz, our programmable light engine allows directional averaging by circular spinning the spot even for sub-millisecond exposure times. We show that restoring the symmetry of TIRF/HILO illumination reduces scattering and produces an evenly lit field-of-view that affords on-line analysis of evanescnt-field excited fluorescence without pre-processing. Utilizing crossed acousto-optical deflectors, our device generates arbitrary intensity profiles in BFP, permitting variable-angle, multi-color illumination, or objective lenses to be rapidly exchanged.

WE-AB-204-05: Harmonizing PET/CT Quantification in Multicenter Studies: A Case Study

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

Marques da Silva, A; Fischer, A

2015-06-15

Purpose: To present the implementation of a strategy to harmonize FDG PET/CT quantification (SUV), performed with different scanner models and manufacturers. Methods: The strategy was based on Boellaard (2011) and EARL FDG-PET/CT accreditation program, that propose quality control measurements for harmonizing scanner performance. A NEMA IEC Body phantom study was performed using four different devices: PHP-1 (Gemini TF Base, Philips); PHP-2 (Gemini GXL, Philips); GEH (Discovery 600, General Electric); SMS (Biograph Hi-Rez 16, Siemens). The SUV Recovery Coefficient (RC) was calculated using the clinical protocol and other clinically relevant reconstruction parameters. The most appropriate reconstruction parameters (MARP) for SUV harmonization,more » in each scanner, are those which achieve EARL harmonizing standards. They were identified using the lowest root mean square errors (RMSE). To evaluate the strategy’s effectiveness, the Maximum Differences (MD) between the clinical and MARP RC values were calculated. Results: The reconstructions parameters that obtained the lowest RMSE are: FBP 5mm (PHP-1); LOR-RAMLA 2i0.008l (PHP-2); VuePointHD 2i32s10mm (GEH); and FORE+OSEM 4i8s6mm (SMS). Thus, to ensure that quantitative PET image measurements are interchangeable between these sites, images must be reconstructed with the above-mentioned parameters. Although, a decoupling between the best image for PET/CT qualitative analysis and the best image for quantification studies was observed. The MD showed that the strategy was effective in reducing the variability of SUV quantification for small structures (<17mm). Conclusion: The harmonization strategy of the SUV quantification implemented with these devices was effective in reducing the variability of small structures quantification, minimizing the inter-scanner and inter-institution differences in quantification. However, it is essential that, in addition to the harmonization of quantification, the standardization of the methodology of patient preparation must be maintained, in order to minimize the SUV variability due to biological factors. Financial support by CAPES.« less

Functional validation and comparison framework for EIT lung imaging.

PubMed

Grychtol, Bartłomiej; Elke, Gunnar; Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.

Studies of mechanisms of decay and recovery in organic dye-doped polymers using spatially resolved white light interferometry

NASA Astrophysics Data System (ADS)

Anderson, Benjamin; Bernhardt, Elizabeth; Kuzyk, Mark

2012-10-01

Several organic dyes have been shown to self heal when doped in a polymer matrix. Most measurements to date use optical absorbance, amplified spontaneous emission, or digital imaging as a probe. Each method determines a subset of the relevant parameters. We have constructed a white light interferometric microscope, which measures the absorption spectrum and change in refractive index during decay and recovery simultaneously at multiple points in the material. We report on preliminary measurements and results concerning the microscopes spatial resolution.

Heat flux estimates of power balance on Proto-MPEX with IR imaging

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

Showers, M., E-mail: mshower1@vols.utk.edu; Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831; Biewer, T. M.

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) at Oak Ridge National Laboratory (ORNL) is a precursor linear plasma device to the Material Plasma Exposure eXperiment (MPEX), which will study plasma material interactions (PMIs) for future fusion reactors. This paper will discuss the initial steps performed towards completing a power balance on Proto-MPEX to quantify where energy is lost from the plasma, including the relevant diagnostic package implemented. Machine operating parameters that will improve Proto-MPEX’s performance may be identified, increasing its PMI research capabilities.

Introduction of a standardized multimodality image protocol for navigation-guided surgery of suspected low-grade gliomas.

PubMed

Mert, Aygül; Kiesel, Barbara; Wöhrer, Adelheid; Martínez-Moreno, Mauricio; Minchev, Georgi; Furtner, Julia; Knosp, Engelbert; Wolfsberger, Stefan; Widhalm, Georg

2015-01-01

OBJECT Surgery of suspected low-grade gliomas (LGGs) poses a special challenge for neurosurgeons due to their diffusely infiltrative growth and histopathological heterogeneity. Consequently, neuronavigation with multimodality imaging data, such as structural and metabolic data, fiber tracking, and 3D brain visualization, has been proposed to optimize surgery. However, currently no standardized protocol has been established for multimodality imaging data in modern glioma surgery. The aim of this study was therefore to define a specific protocol for multimodality imaging and navigation for suspected LGG. METHODS Fifty-one patients who underwent surgery for a diffusely infiltrating glioma with nonsignificant contrast enhancement on MRI and available multimodality imaging data were included. In the first 40 patients with glioma, the authors retrospectively reviewed the imaging data, including structural MRI (contrast-enhanced T1-weighted, T2-weighted, and FLAIR sequences), metabolic images derived from PET, or MR spectroscopy chemical shift imaging, fiber tracking, and 3D brain surface/vessel visualization, to define standardized image settings and specific indications for each imaging modality. The feasibility and surgical relevance of this new protocol was subsequently prospectively investigated during surgery with the assistance of an advanced electromagnetic navigation system in the remaining 11 patients. Furthermore, specific surgical outcome parameters, including the extent of resection, histological analysis of the metabolic hotspot, presence of a new postoperative neurological deficit, and intraoperative accuracy of 3D brain visualization models, were assessed in each of these patients. RESULTS After reviewing these first 40 cases of glioma, the authors defined a specific protocol with standardized image settings and specific indications that allows for optimal and simultaneous visualization of structural and metabolic data, fiber tracking, and 3D brain visualization. This new protocol was feasible and was estimated to be surgically relevant during navigation-guided surgery in all 11 patients. According to the authors' predefined surgical outcome parameters, they observed a complete resection in all resectable gliomas (n = 5) by using contour visualization with T2-weighted or FLAIR images. Additionally, tumor tissue derived from the metabolic hotspot showed the presence of malignant tissue in all WHO Grade III or IV gliomas (n = 5). Moreover, no permanent postoperative neurological deficits occurred in any of these patients, and fiber tracking and/or intraoperative monitoring were applied during surgery in the vast majority of cases (n = 10). Furthermore, the authors found a significant intraoperative topographical correlation of 3D brain surface and vessel models with gyral anatomy and superficial vessels. Finally, real-time navigation with multimodality imaging data using the advanced electromagnetic navigation system was found to be useful for precise guidance to surgical targets, such as the tumor margin or the metabolic hotspot. CONCLUSIONS In this study, the authors defined a specific protocol for multimodality imaging data in suspected LGGs, and they propose the application of this new protocol for advanced navigation-guided procedures optimally in conjunction with continuous electromagnetic instrument tracking to optimize glioma surgery.

Image-based diagnostic aid for interstitial lung disease with secondary data integration

NASA Astrophysics Data System (ADS)

Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine

2007-03-01

Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns. These features show good discriminative properties for the separation of five classes of visual observations.

Optimizing morphology through blood cell image analysis.

PubMed

Merino, A; Puigví, L; Boldú, L; Alférez, S; Rodellar, J

2018-05-01

Morphological review of the peripheral blood smear is still a crucial diagnostic aid as it provides relevant information related to the diagnosis and is important for selection of additional techniques. Nevertheless, the distinctive cytological characteristics of the blood cells are subjective and influenced by the reviewer's interpretation and, because of that, translating subjective morphological examination into objective parameters is a challenge. The use of digital microscopy systems has been extended in the clinical laboratories. As automatic analyzers have some limitations for abnormal or neoplastic cell detection, it is interesting to identify quantitative features through digital image analysis for morphological characteristics of different cells. Three main classes of features are used as follows: geometric, color, and texture. Geometric parameters (nucleus/cytoplasmic ratio, cellular area, nucleus perimeter, cytoplasmic profile, RBC proximity, and others) are familiar to pathologists, as they are related to the visual cell patterns. Different color spaces can be used to investigate the rich amount of information that color may offer to describe abnormal lymphoid or blast cells. Texture is related to spatial patterns of color or intensities, which can be visually detected and quantitatively represented using statistical tools. This study reviews current and new quantitative features, which can contribute to optimize morphology through blood cell digital image processing techniques. © 2018 John Wiley & Sons Ltd.

Cardiovascular magnetic resonance physics for clinicians: part I.

PubMed

Ridgway, John P

2010-11-30

There are many excellent specialised texts and articles that describe the physical principles of cardiovascular magnetic resonance (CMR) techniques. There are also many texts written with the clinician in mind that provide an understandable, more general introduction to the basic physical principles of magnetic resonance (MR) techniques and applications. There are however very few texts or articles that attempt to provide a basic MR physics introduction that is tailored for clinicians using CMR in their daily practice. This is the first of two reviews that are intended to cover the essential aspects of CMR physics in a way that is understandable and relevant to this group. It begins by explaining the basic physical principles of MR, including a description of the main components of an MR imaging system and the three types of magnetic field that they generate. The origin and method of production of the MR signal in biological systems are explained, focusing in particular on the two tissue magnetisation relaxation properties (T1 and T2) that give rise to signal differences from tissues, showing how they can be exploited to generate image contrast for tissue characterisation. The method most commonly used to localise and encode MR signal echoes to form a cross sectional image is described, introducing the concept of k-space and showing how the MR signal data stored within it relates to properties within the reconstructed image. Before describing the CMR acquisition methods in detail, the basic spin echo and gradient pulse sequences are introduced, identifying the key parameters that influence image contrast, including appearances in the presence of flowing blood, resolution and image acquisition time. The main derivatives of these two pulse sequences used for cardiac imaging are then described in more detail. Two of the key requirements for CMR are the need for data acquisition first to be to be synchronised with the subject's ECG and to be fast enough for the subject to be able to hold their breath. Methods of ECG synchronisation using both triggering and retrospective gating approaches, and accelerated data acquisition using turbo or fast spin echo and gradient echo pulse sequences are therefore outlined in some detail. It is shown how double inversion black blood preparation combined with turbo or fast spin echo pulse sequences acquisition is used to achieve high quality anatomical imaging. For functional cardiac imaging using cine gradient echo pulse sequences two derivatives of the gradient echo pulse sequence; spoiled gradient echo and balanced steady state free precession (bSSFP) are compared. In each case key relevant imaging parameters and vendor-specific terms are defined and explained.

Cardiovascular magnetic resonance physics for clinicians: part I

PubMed Central

2010-01-01

There are many excellent specialised texts and articles that describe the physical principles of cardiovascular magnetic resonance (CMR) techniques. There are also many texts written with the clinician in mind that provide an understandable, more general introduction to the basic physical principles of magnetic resonance (MR) techniques and applications. There are however very few texts or articles that attempt to provide a basic MR physics introduction that is tailored for clinicians using CMR in their daily practice. This is the first of two reviews that are intended to cover the essential aspects of CMR physics in a way that is understandable and relevant to this group. It begins by explaining the basic physical principles of MR, including a description of the main components of an MR imaging system and the three types of magnetic field that they generate. The origin and method of production of the MR signal in biological systems are explained, focusing in particular on the two tissue magnetisation relaxation properties (T1 and T2) that give rise to signal differences from tissues, showing how they can be exploited to generate image contrast for tissue characterisation. The method most commonly used to localise and encode MR signal echoes to form a cross sectional image is described, introducing the concept of k-space and showing how the MR signal data stored within it relates to properties within the reconstructed image. Before describing the CMR acquisition methods in detail, the basic spin echo and gradient pulse sequences are introduced, identifying the key parameters that influence image contrast, including appearances in the presence of flowing blood, resolution and image acquisition time. The main derivatives of these two pulse sequences used for cardiac imaging are then described in more detail. Two of the key requirements for CMR are the need for data acquisition first to be to be synchronised with the subject's ECG and to be fast enough for the subject to be able to hold their breath. Methods of ECG synchronisation using both triggering and retrospective gating approaches, and accelerated data acquisition using turbo or fast spin echo and gradient echo pulse sequences are therefore outlined in some detail. It is shown how double inversion black blood preparation combined with turbo or fast spin echo pulse sequences acquisition is used to achieve high quality anatomical imaging. For functional cardiac imaging using cine gradient echo pulse sequences two derivatives of the gradient echo pulse sequence; spoiled gradient echo and balanced steady state free precession (bSSFP) are compared. In each case key relevant imaging parameters and vendor-specific terms are defined and explained. PMID:21118531

Relevant Scatterers Characterization in SAR Images

NASA Astrophysics Data System (ADS)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

Fear conditioning to subliminal fear relevant and non fear relevant stimuli.

PubMed

Lipp, Ottmar V; Kempnich, Clare; Jee, Sang Hoon; Arnold, Derek H

2014-01-01

A growing body of evidence suggests that conscious visual awareness is not a prerequisite for human fear learning. For instance, humans can learn to be fearful of subliminal fear relevant images--images depicting stimuli thought to have been fear relevant in our evolutionary context, such as snakes, spiders, and angry human faces. Such stimuli could have a privileged status in relation to manipulations used to suppress usually salient images from awareness, possibly due to the existence of a designated sub-cortical 'fear module'. Here we assess this proposition, and find it wanting. We use binocular masking to suppress awareness of images of snakes and wallabies (particularly cute, non-threatening marsupials). We find that subliminal presentations of both classes of image can induce differential fear conditioning. These data show that learning, as indexed by fear conditioning, is neither contingent on conscious visual awareness nor on subliminal conditional stimuli being fear relevant.

Sensitivity of F-106B Leading-Edge-Vortex Images to Flight and Vapor-Screen Parameters

NASA Technical Reports Server (NTRS)

Lamar, John E.; Johnson, Thomas D., Jr.

1988-01-01

A flight test was undertaken at NASA Langley Research Center with vapor-screen and image-enhancement techniques to obtain qualitative and quantitative information about near-field vortex flows above the wings of fighter aircraft. In particular, the effects of Reynolds and Mach numbers on the vortex system over an angle-of-attack range were sought. The relevance of these flows stems from their present and future use at many points in the flight envelope, especially during transonic maneuvers. The aircraft used in this flight program was the F-106B because it was available and had sufficient wing sweep (60 deg) to generate a significant leading-edge vortex system. The sensitivity of the visual results to vapor screen hardware and to onset flow changes is discussed.

Automatic parameter selection for feature-based multi-sensor image registration

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

2006-05-01

Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

Analysis of the fractal dimension of volcano geomorphology through Synthetic Aperture Radar (SAR) amplitude images acquired in C and X band.

NASA Astrophysics Data System (ADS)

Pepe, S.; Di Martino, G.; Iodice, A.; Manzo, M.; Pepe, A.; Riccio, D.; Ruello, G.; Sansosti, E.; Tizzani, P.; Zinno, I.

2012-04-01

In the last two decades several aspects relevant to volcanic activity have been analyzed in terms of fractal parameters that effectively describe natural objects geometry. More specifically, these researches have been aimed at the identification of (1) the power laws that governed the magma fragmentation processes, (2) the energy of explosive eruptions, and (3) the distribution of the associated earthquakes. In this paper, the study of volcano morphology via satellite images is dealt with; in particular, we use the complete forward model developed by some of the authors (Di Martino et al., 2012) that links the stochastic characterization of amplitude Synthetic Aperture Radar (SAR) images to the fractal dimension of the imaged surfaces, modelled via fractional Brownian motion (fBm) processes. Based on the inversion of such a model, a SAR image post-processing has been implemented (Di Martino et al., 2010), that allows retrieving the fractal dimension of the observed surfaces, dictating the distribution of the roughness over different spatial scales. The fractal dimension of volcanic structures has been related to the specific nature of materials and to the effects of active geodynamic processes. Hence, the possibility to estimate the fractal dimension from a single amplitude-only SAR image is of fundamental importance for the characterization of volcano structures and, moreover, can be very helpful for monitoring and crisis management activities in case of eruptions and other similar natural hazards. The implemented SAR image processing performs the extraction of the point-by-point fractal dimension of the scene observed by the sensor, providing - as an output product - the map of the fractal dimension of the area of interest. In this work, such an analysis is performed on Cosmo-SkyMed, ERS-1/2 and ENVISAT images relevant to active stratovolcanoes in different geodynamic contexts, such as Mt. Somma-Vesuvio, Mt. Etna, Vulcano and Stromboli in Southern Italy, Shinmoe in Japan, Merapi in Indonesia. Preliminary results reveal that the fractal dimension of natural areas, being related only to the roughness of the observed surface, is very stable as the radar illumination geometry, the resolution and the wavelength change, thus holding a very unique property in SAR data inversion. Such a behavior is not verified in case of non-natural objects. As a matter of fact, when the fractal estimation is performed in the presence of either man-made objects or SAR image features depending on geometrical distortions due to the SAR system acquisition (i.e. layover, shadowing), fractal dimension (D) values outside the range of fractality of natural surfaces (2 < D < 3) are retrieved. These non-fractal characteristics show to be heavily dependent on sensor acquisition parameters (e.g. view angle, resolution). In this work, the behaviour of the maps generated starting from the C- and X- band SAR data, relevant to all the considered volcanoes, is analyzed: the distribution of the obtained fractal dimension values is investigated on different zones of the maps. In particular, it is verified that the fore-slope and back-slope areas of the image share a very similar fractal dimension distribution that is placed around the mean value of D=2.3. We conclude that, in this context, the fractal dimension could be considered as a signature of the identification of the volcano growth as a natural process. The COSMO-SkyMed data used in this study have been processed at IREA-CNR within the SAR4Volcanoes project under Italian Space Agency agreement n. I/034/11/0.

In vivo ultrasound imaging of the bone cortex

NASA Astrophysics Data System (ADS)

Renaud, Guillaume; Kruizinga, Pieter; Cassereau, Didier; Laugier, Pascal

2018-06-01

Current clinical ultrasound scanners cannot be used to image the interior morphology of bones because these scanners fail to address the complicated physics involved for exact image reconstruction. Here, we show that if the physics is properly addressed, bone cortex can be imaged using a conventional transducer array and a programmable ultrasound scanner. We provide in vivo proof for this technique by scanning the radius and tibia of two healthy volunteers and comparing the thickness of the radius bone with high-resolution peripheral x-ray computed tomography. Our method assumes a medium that is composed of different homogeneous layers with unique elastic anisotropy and ultrasonic wave-speed values. The applicable values of these layers are found by optimizing image sharpness and intensity over a range of relevant values. In the algorithm of image reconstruction we take wave refraction between the layers into account using a ray-tracing technique. The estimated values of the ultrasonic wave-speed and anisotropy in cortical bone are in agreement with ex vivo studies reported in the literature. These parameters are of interest since they were proposed as biomarkers for cortical bone quality. In this paper we discuss the physics involved with ultrasound imaging of bone and provide an algorithm to successfully image the first segment of cortical bone.

SU-E-T-473: A Patient-Specific QC Paradigm Based On Trajectory Log Files and DICOM Plan Files

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

DeMarco, J; McCloskey, S; Low, D

Purpose: To evaluate a remote QC tool for monitoring treatment machine parameters and treatment workflow. Methods: The Varian TrueBeamTM linear accelerator is a digital machine that records machine axis parameters and MLC leaf positions as a function of delivered monitor unit or control point. This information is saved to a binary trajectory log file for every treatment or imaging field in the patient treatment session. A MATLAB analysis routine was developed to parse the trajectory log files for a given patient, compare the expected versus actual machine and MLC positions as well as perform a cross-comparison with the DICOM-RT planmore » file exported from the treatment planning system. The parsing routine sorts the trajectory log files based on the time and date stamp and generates a sequential report file listing treatment parameters and provides a match relative to the DICOM-RT plan file. Results: The trajectory log parsing-routine was compared against a standard record and verify listing for patients undergoing initial IMRT dosimetry verification and weekly and final chart QC. The complete treatment course was independently verified for 10 patients of varying treatment site and a total of 1267 treatment fields were evaluated including pre-treatment imaging fields where applicable. In the context of IMRT plan verification, eight prostate SBRT plans with 4-arcs per plan were evaluated based on expected versus actual machine axis parameters. The average value for the maximum RMS MLC error was 0.067±0.001mm and 0.066±0.002mm for leaf bank A and B respectively. Conclusion: A real-time QC analysis program was tested using trajectory log files and DICOM-RT plan files. The parsing routine is efficient and able to evaluate all relevant machine axis parameters during a patient treatment course including MLC leaf positions and table positions at time of image acquisition and during treatment.« less

Performance evaluation of photoacoustic oximetry imaging systems using a dynamic blood flow phantom with tunable oxygen saturation

NASA Astrophysics Data System (ADS)

Vogt, William C.; Zhou, Xuewen; Andriani, Rudy; Wear, Keith A.; Garra, Brian S.; Pfefer, Joshua

2018-02-01

Photoacoustic Imaging (PAI) is an emerging technology with strong potential for broad clinical applications from breast cancer detection to cerebral monitoring due to its ability to compute maps of blood oxygen saturation (SO2) distribution in deep tissues using multispectral imaging. However, no well-validated consensus test methods currently exist for evaluating oximetry-specific performance characteristics of PAI devices. We have developed a phantombased flow system capable of rapid SO2 adjustment to serve as a test bed for elucidation of factors impacting SO2 measurement and quantitative characterization of device performance. The flow system is comprised of a peristaltic pump, membrane oxygenator, oxygen and nitrogen gas, and in-line oxygen, pH, and temperature sensors that enable real-time estimation of SO2 reference values. Bovine blood was delivered through breast-relevant tissue phantoms containing vessel-mimicking fluid channels, which were imaged using a custom multispectral PAI system. Blood was periodically drawn for SO2 measurement in a clinical-grade CO-oximeter. We used this flow phantom system to evaluate the impact of device parameters (e.g.,wavelength-dependent fluence corrections) and tissue parameters (e.g. fluid channel depth, blood SO2, spectral coloring artifacts) on oximetry measurement accuracy. Results elucidated key challenges in PAI oximetry and device design trade-offs, which subsequently allowed for optimization of system performance. This approach provides a robust benchtop test platform that can support PAI oximetry device optimization, performance validation, and clinical translation, and may inform future development of consensus test methods for performance assessment of photoacoustic oximetry imaging systems.

New head equivalent phantom for task and image performance evaluation representative for neurovascular procedures occurring in the Circle of Willis

NASA Astrophysics Data System (ADS)

Ionita, Ciprian N.; Loughran, Brendan; Jain, Amit; Swetadri Vasan, S. N.; Bednarek, Daniel R.; Levy, Elad; Siddiqui, Adnan H.; Snyder, Kenneth V.; Hopkins, L. N.; Rudin, Stephen

2012-03-01

Phantom equivalents of different human anatomical parts are routinely used for imaging system evaluation or dose calculations. The various recommendations on the generic phantom structure given by organizations such as the AAPM, are not always accurate when evaluating a very specific task. When we compared the AAPM head phantom containing 3 mm of aluminum to actual neuro-endovascular image guided interventions (neuro-EIGI) occurring in the Circle of Willis, we found that the system automatic exposure rate control (AERC) significantly underestimated the x-ray parameter selection. To build a more accurate phantom for neuro-EIGI, we reevaluated the amount of aluminum which must be included in the phantom. Human skulls were imaged at different angles, using various angiographic exposures, at kV's relevant to neuro-angiography. An aluminum step wedge was also imaged under identical conditions, and a correlation between the gray values of the imaged skulls and those of the aluminum step thicknesses was established. The average equivalent aluminum thickness for the skull samples for frontal projections in the Circle of Willis region was found to be about 13 mm. The results showed no significant changes in the average equivalent aluminum thickness with kV or mAs variation. When a uniform phantom using 13 mm aluminum and 15 cm acrylic was compared with an anthropomorphic head phantom the x-ray parameters selected by the AERC system were practically identical. These new findings indicate that for this specific task, the amount of aluminum included in the head equivalent must be increased substantially from 3 mm to a value of 13 mm.

Examination of contrast mechanisms in optoacoustic imaging of thermal lesions

NASA Astrophysics Data System (ADS)

Richter, Christian; Spirou, Gloria; Oraevsky, Alexander A.; Whelan, William M.; Kolios, Michael C.

2006-02-01

Optoacoustic Imaging is based on the thermal expansion of tissue caused by a temperature rise due to absorption of short laser pulses. At constant laser fluence, optoacoustic image contrast is proportional to differences in optical absorption and the thermoacoustic efficiency, expressed by the Grueuneisen parameter, Γ. Γ is proportional to the thermal expansion coefficient, the sound velocity squared and the inverse heat capacity at constant pressure. In thermal therapies, these parameters may be modified in the treated area. In this work experiments were performed to examine the influence of these parameters on image contrast. A Laser Optoacoustic Imaging System (LOIS, Fairway Medical Technologies, Houston, Texas) was used to image tissue phantoms comprised of cylindrical Polyvinyl Chloride Plastisol (PVCP) optical absorbing targets imbedded in either gelatin or PVCP as the background medium. Varying concentrations of Black Plastic Color (BPC) and titanium dioxide (TiO II) were added to targets and background to yield desired tissue relevant optical absorption and effective scattering coefficients, respectively. In thermal therapy experiments, ex-vivo bovine liver was heated with laser fibres (805nm laser at 5 W for 600s) to create regions of tissue coagulation. Lesions formed in the liver tissue were visible using the LOIS system with reasonable correspondence to the actual region of tissue coagulation. In the phantom experiments, contrast could be seen with low optical absorbing targets (μ a of 0.50cm -1 down to 0.13cm-1) embedded in a gelatin background (see manuscript for formula). Therefore, the data suggest that small objects (< 5mm) with low absorption coefficients (in the range < 1cm -1) can be imaged using LOIS. PVCP-targets in gelatin were visible, even with the same optical properties as the gelatin, but different Γ. The enhanced contrast may also be caused by differences in the mechanical properties between the target and the surrounding medium. PVCP-targets imbedded in PVCP produced poorer image contrast than PVCP-targets in gelatin with comparable optical properties. The preliminary investigation in tissue equivalent phantoms indicates that in addition to tissue optical properties, differences in mechanical properties between heated and unheated tissues may be responsible for image contrast. Furthermore, thermal lesions in liver tissue, ex-vivo, can be visualized using an optoacoustic system.

Wavelet optimization for content-based image retrieval in medical databases.

PubMed

Quellec, G; Lamard, M; Cazuguel, G; Cochener, B; Roux, C

2010-04-01

We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize the distribution of wavelet coefficients in each subband of the decomposition. A distance measure is then defined to compare two image signatures and thus retrieve the most similar images in a database when a query image is submitted by a physician. To retrieve relevant images from a medical database, the signatures and the distance measure must be related to the medical interpretation of images. As a consequence, we introduce several degrees of freedom in the system so that it can be tuned to any pathology and image modality. In particular, we propose to adapt the wavelet basis, within the lifting scheme framework, and to use a custom decomposition scheme. Weights are also introduced between subbands. All these parameters are tuned by an optimization procedure, using the medical grading of each image in the database to define a performance measure. The system is assessed on two medical image databases: one for diabetic retinopathy follow up and one for screening mammography, as well as a general purpose database. Results are promising: a mean precision of 56.50%, 70.91% and 96.10% is achieved for these three databases, when five images are returned by the system. Copyright 2009 Elsevier B.V. All rights reserved.

Frequency domain phosphorescence lifetime Imaging measurements and applications by ISS FastFLIM and multi pulse excitation

NASA Astrophysics Data System (ADS)

Coskun, Ulas C.; Lam, Sandra; Sun, Yuansheng; Liao, Shih-Chu Jeff; George, Steven C.; Barbieri, Beniamino

2017-02-01

Phosphorescence probes can have significantly long lifetimes, on the order of micro- to milli-seconds or longer. In addition, environmental changes can affect the lifetimes of these phosphorescence probes. Thus, Phosphorescence Lifetime Imaging Microscopy (PLIM) is a very useful tool to localize the phosphorescence probes based on their lifetimes to study the variance in the lifetimes due to the micro environmental changes. Since the probes respond to the biologically relevant parameters like oxygen concentration, they can be used to study various biologically relevant processes like cellular metabolism, protein interaction etc. In this case, we study the effects of oxygen on Oxyphor G4 with PLIM. Since The Oxyphor G4 can be quenched by O2, it is a good example of such a probe and has a lifetime around 250us. Here we present the digital frequency domain PLIM technique and study the lifetime of the Oxyphor G4 as a function of the O2 concentration. The lifetime data are successfully presented in a phasor plot for various O2 concentrations and are consistent with the time domain data. Overall, we can analyze the oxygen consumption of varying cells using this technique.

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

DOE PAGES

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra; ...

2017-05-23

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splittingmore » of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.« less

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

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

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splittingmore » of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.« less

Evolutionary image simplification for lung nodule classification with convolutional neural networks.

PubMed

Lückehe, Daniel; von Voigt, Gabriele

2018-05-29

Understanding decisions of deep learning techniques is important. Especially in the medical field, the reasons for a decision in a classification task are as crucial as the pure classification results. In this article, we propose a new approach to compute relevant parts of a medical image. Knowing the relevant parts makes it easier to understand decisions. In our approach, a convolutional neural network is employed to learn structures of images of lung nodules. Then, an evolutionary algorithm is applied to compute a simplified version of an unknown image based on the learned structures by the convolutional neural network. In the simplified version, irrelevant parts are removed from the original image. In the results, we show simplified images which allow the observer to focus on the relevant parts. In these images, more than 50% of the pixels are simplified. The simplified pixels do not change the meaning of the images based on the learned structures by the convolutional neural network. An experimental analysis shows the potential of the approach. Besides the examples of simplified images, we analyze the run time development. Simplified images make it easier to focus on relevant parts and to find reasons for a decision. The combination of an evolutionary algorithm employing a learned convolutional neural network is well suited for the simplification task. From a research perspective, it is interesting which areas of the images are simplified and which parts are taken as relevant.

Actin dynamics at the living cell submembrane imaged by total internal reflection fluorescence photobleaching.

PubMed Central

Sund, S E; Axelrod, D

2000-01-01

Although reversible chemistry is crucial to dynamical processes in living cells, relatively little is known about relevant chemical kinetic rates in vivo. Total internal reflection/fluorescence recovery after photobleaching (TIR/FRAP), an established technique previously demonstrated to measure reversible biomolecular kinetic rates at surfaces in vitro, is extended here to measure reversible biomolecular kinetic rates of actin at the cytofacial (subplasma membrane) surface of living cells. For the first time, spatial imaging (with a charge-coupled device camera) is used in conjunction with TIR/FRAP. TIR/FRAP imaging produces both spatial maps of kinetic parameters (off-rates and mobile fractions) and estimates of kinetic correlation distances, cell-wide kinetic gradients, and dependences of kinetic parameters on initial fluorescence intensity. For microinjected rhodamine actin in living cultured smooth muscle (BC3H1) cells, the unbinding rate at or near the cytofacial surface of the plasma membrane (averaged over the entire cell) is measured at 0.032 +/- 0.007 s(-1). The corresponding rate for actin marked by microinjected rhodamine phalloidin is very similar, 0.033 +/- 0.013 s(-1), suggesting that TIR/FRAP is reporting the dynamics of entire filaments or protofilaments. For submembrane fluorescence-marked actin, the intensity, off-rate, and mobile fraction show a positive correlation over a characteristic distance of 1-3 microm and a negative correlation over larger distances greater than approximately 7-14 microm. Furthermore, the kinetic parameters display a statistically significant cell-wide gradient, with the cell having a "fast" and "slow" end with respect to actin kinetics. PMID:10969025

A unified framework for image retrieval using keyword and visual features.

PubMed

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

Enhancing and Archiving the APS Catalog of the POSS I

NASA Technical Reports Server (NTRS)

Humphreys, Roberta M.

2003-01-01

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

The morphometric study of l3-L4 and L4-L5 lumbar spine in Asian population using magnetic resonance imaging: feasibility analysis for transpsoas lumbar interbody fusion.

PubMed

Yusof, Mohd Imran; Nadarajan, Eswaran; Abdullah, Mohd Shafie

2014-06-15

Cross-sectional study on the measurement of relevant magnetic resonance imaging parameters in 100 patients presented for lumbar spine assessment. To determine anatomical position of lumbar plexus and major blood vessels in relation to vertebral body and anterior edge of psoas muscle at L3-L4 and L4-L5 and to define the safe working zone for transpsoas approach for lumbar fusion. Lateral transpsoas lumbar interbody fusion has been shown to be safe and provides alternative for lumbar fusion. However, proximity of neurovascular structures may not allow a safe passage for this procedure in the Asian population. Relevant parameters were measured from axial magnetic resonance images and analyzed, including the psoas muscle and vertebrae endplate diameters, lumbar plexus and psoas muscle distance, lumbar plexus and vertebra body distance, and vena cava to the anterior vertebrae body diameters. The mean anteroposterior diameters of the right and left psoas muscle ranged from 44.0 to 58.6 mm and 44.8 to 54.0 mm, respectively. The mean anteroposterior diameters of vertebra endplate of L3, L4, and L5 were 38.2 mm, 39.3 mm, and 41.4 mm, respectively. The mean distance of posterior border of vena cava from the vertebra body was 4.5 mm at L3-L4 and 14.1 mm at L4-L5. L3-L4 fusion is feasible at both sides in both sexes; however, at L4-L5 level, the procedure is feasible only on the left side. The safe working zone for transpsoas approach to lumbar spine is significantly narrower at L4-L5 in both sexes. Anterior edge of psoas muscle can be used as a reliable guide to locate lumbar plexus within psoas muscle. N/A.

Clinical use of intracoronary imaging. Part 1: guidance and optimization of coronary interventions. An expert consensus document of the European Association of Percutaneous Cardiovascular Interventions: Endorsed by the Chinese Society of Cardiology.

PubMed

Räber, Lorenz; Mintz, Gary S; Koskinas, Konstantinos C; Johnson, Thomas W; Holm, Niels R; Onuma, Yoshinubo; Radu, Maria D; Joner, Michael; Yu, Bo; Jia, Haibo; Menevau, Nicolas; de la Torre Hernandez, Jose M; Escaned, Javier; Hill, Jonathan; Prati, Francesco; Colombo, Antonio; di Mario, Carlo; Regar, Evelyn; Capodanno, Davide; Wijns, William; Byrne, Robert A; Guagliumi, Giulio

2018-05-22

This Consensus Document is the first of two reports summarizing the views of an expert panel organized by the European Association of Percutaneous Cardiovascular Interventions (EAPCI) on the clinical use of intracoronary imaging including intravascular ultrasound (IVUS) and optical coherence tomography (OCT). The first document appraises the role of intracoronary imaging to guide percutaneous coronary interventions (PCIs) in clinical practice. Current evidence regarding the impact of intracoronary imaging guidance on cardiovascular outcomes is summarized, and patients or lesions most likely to derive clinical benefit from an imaging-guided intervention are identified. The relevance of the use of IVUS or OCT prior to PCI for optimizing stent sizing (stent length and diameter) and planning the procedural strategy is discussed. Regarding post-implantation imaging, the consensus group recommends key parameters that characterize an optimal PCI result and provides cut-offs to guide corrective measures and optimize the stenting result. Moreover, routine performance of intracoronary imaging in patients with stent failure (restenosis or stent thrombosis) is recommended. Finally, strengths and limitations of IVUS and OCT for guiding PCI and assessing stent failures and areas that warrant further research are critically discussed.

Surgeon Reported Outcome Measure for Spine Trauma: An International Expert Survey Identifying Parameters Relevant for the Outcome of Subaxial Cervical Spine Injuries.

PubMed

Sadiqi, Said; Verlaan, Jorrit-Jan; Lehr, A Mechteld; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, S; Schnake, Klaus J; Vaccaro, Alexander R; Oner, F Cumhur

2016-12-15

International web-based survey. To identify clinical and radiological parameters that spine surgeons consider most relevant when evaluating clinical and functional outcomes of subaxial cervical spine trauma patients. Although an outcome instrument that reflects the patients' perspective is imperative, there is also a need for a surgeon reported outcome measure to reflect the clinicians' perspective adequately. A cross-sectional online survey was conducted among a selected number of spine surgeons from all five AOSpine International world regions. They were asked to indicate the relevance of a compilation of 21 parameters, both for the short term (3 mo-2 yr) and long term (≥2 yr), on a five-point scale. The responses were analyzed using descriptive statistics, frequency analysis, and Kruskal-Wallis test. Of the 279 AOSpine International and International Spinal Cord Society members who received the survey, 108 (38.7%) participated in the study. Ten parameters were identified as relevant both for short term and long term by at least 70% of the participants. Neurological status, implant failure within 3 months, and patient satisfaction were most relevant. Bony fusion was the only parameter for the long term, whereas five parameters were identified for the short term. The remaining six parameters were not deemed relevant. Minor differences were observed when analyzing the responses according to each world region, or spine surgeons' degree of experience. The perspective of an international sample of highly experienced spine surgeons was explored on the most relevant parameters to evaluate and predict outcomes of subaxial cervical spine trauma patients. These results form the basis for the development of a disease-specific surgeon reported outcome measure, which will be a helpful tool in research and clinical practice. 4.

Comparative analysis of imaging configurations and objectives for Fourier microscopy.

PubMed

Kurvits, Jonathan A; Jiang, Mingming; Zia, Rashid

2015-11-01

Fourier microscopy is becoming an increasingly important tool for the analysis of optical nanostructures and quantum emitters. However, achieving quantitative Fourier space measurements requires a thorough understanding of the impact of aberrations introduced by optical microscopes that have been optimized for conventional real-space imaging. Here we present a detailed framework for analyzing the performance of microscope objectives for several common Fourier imaging configurations. To this end, we model objectives from Nikon, Olympus, and Zeiss using parameters that were inferred from patent literature and confirmed, where possible, by physical disassembly. We then examine the aberrations most relevant to Fourier microscopy, including the alignment tolerances of apodization factors for different objective classes, the effect of magnification on the modulation transfer function, and vignetting-induced reductions of the effective numerical aperture for wide-field measurements. Based on this analysis, we identify an optimal objective class and imaging configuration for Fourier microscopy. In addition, the Zemax files for the objectives and setups used in this analysis have been made publicly available as a resource for future studies.

Radiation Dose Estimation for Pediatric Patients Undergoing Cardiac Catheterization

NASA Astrophysics Data System (ADS)

Wang, Chu

Patients undergoing cardiac catheterization are potentially at risk of radiation-induced health effects from the interventional fluoroscopic X-ray imaging used throughout the clinical procedure. The amount of radiation exposure is highly dependent on the complexity of the procedure and the level of optimization in imaging parameters applied by the clinician. For cardiac catheterization, patient radiation dosimetry, for key organs as well as whole-body effective, is challenging due to the lack of fixed imaging protocols, unlike other common X-ray based imaging modalities. Pediatric patients are at a greater risk compared to adults due to their greater cellular radio-sensitivities as well as longer remaining life-expectancy following the radiation exposure. In terms of radiation dosimetry, they are often more challenging due to greater variation in body size, which often triggers a wider range of imaging parameters in modern imaging systems with automatic dose rate modulation. The overall objective of this dissertation was to develop a comprehensive method of radiation dose estimation for pediatric patients undergoing cardiac catheterization. In this dissertation, the research is divided into two main parts: the Physics Component and the Clinical Component. A proof-of-principle study focused on two patient age groups (Newborn and Five-year-old), one popular biplane imaging system, and the clinical practice of two pediatric cardiologists at one large academic medical center. The Physics Component includes experiments relevant to the physical measurement of patient organ dose using high-sensitivity MOSFET dosimeters placed in anthropomorphic pediatric phantoms. First, the three-dimensional angular dependence of MOSFET detectors in scatter medium under fluoroscopic irradiation was characterized. A custom-made spherical scatter phantom was used to measure response variations in three-dimensional angular orientations. The results were to be used as angular dependence correction factors for the MOSFET organ dose measurements in the following studies. Minor angular dependence (< +/-20% at all angles tested, < +/-10% at clinically relevant angles in cardiac catheterization) was observed. Second, the cardiac dose for common fluoroscopic imaging techniques for pediatric patients in the two age groups was measured. Imaging technique settings with variations of individual key imaging parameters were tested to observe the quantitative effect of imaging optimization or lack thereof. Along with each measurement, the two standard system output indices, the Air Kerma (AK) and Dose-Area Product (DAP), were also recorded and compared to the measured cardiac and skin doses -- the lack of correlation between the indices and the organ doses shed light to the substantial limitation of the indices in representing patient radiation dose, at least within the scope of this dissertation. Third, the effective dose (ED) for Posterior-Anterior and Lateral fluoroscopic imaging techniques for pediatric patients in the two age groups was determined. In addition, the dosimetric effect of removing the anti-scatter grid was studied, for which a factor-of-two ED rate reduction was observed for the imaging techniques. The Clinical Component involved analytical research to develop a validated retrospective cardiac dose reconstruction formulation and to propose the new Optimization Index which evaluates the level of optimization of the clinician's imaging usage during a procedure; and small sample group of actual procedures were used to demonstrate applicability of these formulations. In its entirety, the research represents a first-of-its-kind comprehensive approach in radiation dosimetry for pediatric cardiac catheterization; and separately, it is also modular enough that each individual section can serve as study templates for small-scale dosimetric studies of similar purposes. The data collected and algorithmic formulations developed can be of use in areas of personalized patient dosimetry, clinician training, image quality studies and radiation-associated health effect research.

Functional Validation and Comparison Framework for EIT Lung Imaging

PubMed Central

Meybohm, Patrick; Weiler, Norbert; Frerichs, Inéz; Adler, Andy

2014-01-01

Introduction Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. Methods We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Results and Conclusions Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT. PMID:25110887

A two-step framework for the registration of HE stained and FTIR images

NASA Astrophysics Data System (ADS)

Peñaranda, Francisco; Naranjo, Valery; Verdú, Rafaél.; Lloyd, Gavin R.; Nallala, Jayakrupakar; Stone, Nick

2016-03-01

FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical phenomena that require special processing. Little work has been done in the field with the aim of registering hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant structures that the pathologist may identify in the gold standard HE images. A two-step registration framework is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This representative image, which must have a spatial contrast as similar as possible to a gray image obtained from the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the registration algorithm a similarity transformation is estimated from interest points, which are automatically detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in the frequency domain compensates for local anatomical variations between both images. After a proper tuning of some parameters the proposed registration framework works in an automated way. The method was tested on 7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

SU-E-T-588: Optimization of Imaging Following 223Ra Administration in Targeted Alpha-Emitting Radionuclide Therapy of Bone Metastases

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

Benabdallah, N; Bernardini, M; Desbree, A

Purpose: With a growing demand of alpha-emitting radiopharmaceuticals, especially Xofigo ({sup 223}RaCl{sub 2}) which is used in the treatment of metastatic bone disease, the optimization of dosimetry becomes necessary. Indeed, in Europe, as stated on the council directive 2013/59/euratom, exposures of target volumes for radiotherapeutic purposes shall be individually planned taking into account that doses to non-target volumes and tissues shall be as low as reasonably achievable. To that aim, the possibility of imaging {sup 223}Ra was first investigated. Methods: The experiments were conducted at the Hopital Europeen Georges Pompidou with an Infinia Hawkeye 4 gamma camera, equipped with amore » medium-energy collimator. Imaging parameters, such as sensibility, spatial resolution and energy spectrum, were determined using several physical phantoms with a source of 6 MBq of {sup 223}Ra. Bone metastases were modeled with a NEMA Body Phantom to investigate image degradation based on the concentration of {sup 223}Ra. Results: The acquired energy spectrum allowed to visualize several photon peaks: at 85, 154 and 270 keV. Camera sensitivity measured from the phantom study was 102.3 cps/MBq for the 85 keV ± 20 %, 89.9 cps/MBq for the 154 ± 20 % window and 65.4 cps/MBq for the 270 ± 10 % window. The spatial resolution (full-width at half-maximum) was respectively 1.7, 1.9 and 1.8 cm for the three energy windows. SPECT/CT images of NEMA Body Phantom without and with attenuation have permitted to determine the best reconstruction parameters. Conclusion: This study has demonstrated that it is possible to obtain clinically relevant information from images of {sup 223}Ra. All these results will be valuable to analyze biodistribution imaging of the radiopharmaceutical in the patient body and go further in the reconstruction of patient images in order to personalize the dosimetry.« less

Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles.

PubMed

Barker, Jocelyn; Hoogi, Assaf; Depeursinge, Adrien; Rubin, Daniel L

2016-05-01

Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digital pathology images: first, whole slide pathology images are massive, making computerized analysis inefficient, and second, diverse tissue regions in whole slide images that are not directly relevant to the disease may mislead computerized diagnosis algorithms. We propose a method to overcome both of these challenges that utilizes a coarse-to-fine analysis of the localized characteristics in pathology images. An initial surveying stage analyzes the diversity of coarse regions in the whole slide image. This includes extraction of spatially localized features of shape, color and texture from tiled regions covering the slide. Dimensionality reduction of the features assesses the image diversity in the tiled regions and clustering creates representative groups. A second stage provides a detailed analysis of a single representative tile from each group. An Elastic Net classifier produces a diagnostic decision value for each representative tile. A weighted voting scheme aggregates the decision values from these tiles to obtain a diagnosis at the whole slide level. We evaluated our method by automatically classifying 302 brain cancer cases into two possible diagnoses (glioblastoma multiforme (N = 182) versus lower grade glioma (N = 120)) with an accuracy of 93.1% (p < 0.001). We also evaluated our method in the dataset provided for the 2014 MICCAI Pathology Classification Challenge, in which our method, trained and tested using 5-fold cross validation, produced a classification accuracy of 100% (p < 0.001). Our method showed high stability and robustness to parameter variation, with accuracy varying between 95.5% and 100% when evaluated for a wide range of parameters. Our approach may be useful to automatically differentiate between the two cancer subtypes. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantifying Electromigration Processes in Sn-0.7Cu Solder with Lab-Scale X-Ray Computed Micro-Tomography

NASA Astrophysics Data System (ADS)

Mertens, James Charles Edwin

For decades, microelectronics manufacturing has been concerned with failures related to electromigration phenomena in conductors experiencing high current densities. The influence of interconnect microstructure on device failures related to electromigration in BGA and flip chip solder interconnects has become a significant interest with reduced individual solder interconnect volumes. A survey indicates that x-ray computed micro-tomography (muXCT) is an emerging, novel means for characterizing the microstructures' role in governing electromigration failures. This work details the design and construction of a lab-scale muXCT system to characterize electromigration in the Sn-0.7Cu lead-free solder system by leveraging in situ imaging. In order to enhance the attenuation contrast observed in multi-phase material systems, a modeling approach has been developed to predict settings for the controllable imaging parameters which yield relatively high detection rates over the range of x-ray energies for which maximum attenuation contrast is expected in the polychromatic x-ray imaging system. In order to develop this predictive tool, a model has been constructed for the Bremsstrahlung spectrum of an x-ray tube, and calculations for the detector's efficiency over the relevant range of x-ray energies have been made, and the product of emitted and detected spectra has been used to calculate the effective x-ray imaging spectrum. An approach has also been established for filtering 'zinger' noise in x-ray radiographs, which has proven problematic at high x-ray energies used for solder imaging. The performance of this filter has been compared with a known existing method and the results indicate a significant increase in the accuracy of zinger filtered radiographs. The obtained results indicate the conception of a powerful means for the study of failure causing processes in solder systems used as interconnects in microelectronic packaging devices. These results include the volumetric quantification of parameters which are indicative of both electromigration tolerance of solders and the dominant mechanisms for atomic migration in response to current stressing. This work is aimed to further the community's understanding of failure-causing electromigration processes in industrially relevant material systems for microelectronic interconnect applications and to advance the capability of available characterization techniques for their interrogation.

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Model-free uncertainty estimation in stochastical optical fluctuation imaging (SOFI) leads to a doubled temporal resolution

PubMed Central

Vandenberg, Wim; Duwé, Sam; Leutenegger, Marcel; Moeyaert, Benjamien; Krajnik, Bartosz; Lasser, Theo; Dedecker, Peter

2016-01-01

Stochastic optical fluctuation imaging (SOFI) is a super-resolution fluorescence imaging technique that makes use of stochastic fluctuations in the emission of the fluorophores. During a SOFI measurement multiple fluorescence images are acquired from the sample, followed by the calculation of the spatiotemporal cumulants of the intensities observed at each position. Compared to other techniques, SOFI works well under conditions of low signal-to-noise, high background, or high emitter densities. However, it can be difficult to unambiguously determine the reliability of images produced by any superresolution imaging technique. In this work we present a strategy that enables the estimation of the variance or uncertainty associated with each pixel in the SOFI image. In addition to estimating the image quality or reliability, we show that this can be used to optimize the signal-to-noise ratio (SNR) of SOFI images by including multiple pixel combinations in the cumulant calculation. We present an algorithm to perform this optimization, which automatically takes all relevant instrumental, sample, and probe parameters into account. Depending on the optical magnification of the system, this strategy can be used to improve the SNR of a SOFI image by 40% to 90%. This gain in information is entirely free, in the sense that it does not require additional efforts or complications. Alternatively our approach can be applied to reduce the number of fluorescence images to meet a particular quality level by about 30% to 50%, strongly improving the temporal resolution of SOFI imaging. PMID:26977356

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

Cruz, Jeffrey A.; Savage, Linda J.; Zegarac, Robert; ...

2016-06-22

Understanding and improving the productivity and robustness of plant photosynthesis requires high-throughput phenotyping under environmental conditions that are relevant to the field. Here we demonstrate the dynamic environmental photosynthesis imager (DEPI), an experimental platform for integrated, continuous, and high-throughput measurements of photosynthetic parameters during plant growth under reproducible yet dynamic environmental conditions. Using parallel imagers obviates the need to move plants or sensors, reducing artifacts and allowing simultaneous measurement on large numbers of plants. As a result, DEPI can reveal phenotypes that are not evident under standard laboratory conditions but emerge under progressively more dynamic illumination. We show examples inmore » mutants of Arabidopsis of such “emergent phenotypes” that are highly transient and heterogeneous, appearing in different leaves under different conditions and depending in complex ways on both environmental conditions and plant developmental age. Finally, these emergent phenotypes appear to be caused by a range of phenomena, suggesting that such previously unseen processes are critical for plant responses to dynamic environments.« less

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking

NASA Astrophysics Data System (ADS)

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Multimodal Deep Autoencoder for Human Pose Recovery.

PubMed

Hong, Chaoqun; Yu, Jun; Wan, Jian; Tao, Dacheng; Wang, Meng

2015-12-01

Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their relationships are inherently non-linear, which limits recovery performance of these methods. In this paper, we propose a novel pose recovery method using non-linear mapping with multi-layered deep neural network. It is based on feature extraction with multimodal fusion and back-propagation deep learning. In multimodal fusion, we construct hypergraph Laplacian with low-rank representation. In this way, we obtain a unified feature description by standard eigen-decomposition of the hypergraph Laplacian matrix. In back-propagation deep learning, we learn a non-linear mapping from 2D images to 3D poses with parameter fine-tuning. The experimental results on three data sets show that the recovery error has been reduced by 20%-25%, which demonstrates the effectiveness of the proposed method.

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking.

PubMed

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J; Jian, Yifan; Sarunic, Marinko V

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Assessment of Renal Hemodynamics and Oxygenation by Simultaneous Magnetic Resonance Imaging (MRI) and Quantitative Invasive Physiological Measurements.

PubMed

Cantow, Kathleen; Arakelyan, Karen; Seeliger, Erdmann; Niendorf, Thoralf; Pohlmann, Andreas

2016-01-01

In vivo assessment of renal perfusion and oxygenation under (patho)physiological conditions by means of noninvasive diagnostic imaging is conceptually appealing. Blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) and quantitative parametric mapping of the magnetic resonance (MR) relaxation times T 2* and T 2 are thought to provide surrogates of renal tissue oxygenation. The validity and efficacy of this technique for quantitative characterization of local tissue oxygenation and its changes under different functional conditions have not been systematically examined yet and remain to be established. For this purpose, the development of an integrative multimodality approaches is essential. Here we describe an integrated hybrid approach (MR-PHYSIOL) that combines established quantitative physiological measurements with T 2* (T 2) mapping and MR-based kidney size measurements. Standardized reversible (patho)physiologically relevant interventions, such as brief periods of aortic occlusion, hypoxia, and hyperoxia, are used for detailing the relation between the MR-PHYSIOL parameters, in particular between renal T 2* and tissue oxygenation.

Imaging brain microstructure with diffusion MRI: practicality and applications.

PubMed

Alexander, Daniel C; Dyrby, Tim B; Nilsson, Markus; Zhang, Hui

2017-11-29

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term. Copyright © 2017 John Wiley & Sons, Ltd.

A review of consensus test methods for established medical imaging modalities and their implications for optical coherence tomography

NASA Astrophysics Data System (ADS)

Pfefer, Joshua; Agrawal, Anant

2012-03-01

In recent years there has been increasing interest in development of consensus, tissue-phantom-based approaches for assessment of biophotonic imaging systems, with the primary goal of facilitating clinical translation of novel optical technologies. Well-characterized test methods based on tissue phantoms can provide useful tools for performance assessment, thus enabling standardization and device inter-comparison during preclinical development as well as quality assurance and re-calibration in the clinical setting. In this review, we study the role of phantom-based test methods as described in consensus documents such as international standards for established imaging modalities including X-ray CT, MRI and ultrasound. Specifically, we focus on three image quality characteristics - spatial resolution, spatial measurement accuracy and image uniformity - and summarize the terminology, metrics, phantom design/construction approaches and measurement/analysis procedures used to assess these characteristics. Phantom approaches described are those in routine clinical use and tend to have simplified morphology and biologically-relevant physical parameters. Finally, we discuss the potential for applying knowledge gained from existing consensus documents in the development of standardized, phantom-based test methods for optical coherence tomography.

Determining the relative importance of figures in journal articles to find representative images

NASA Astrophysics Data System (ADS)

Müller, Henning; Foncubierta-Rodríguez, Antonio; Lin, Chang; Eggel, Ivan

2013-03-01

When physicians are searching for articles in the medical literature, images of the articles can help determining relevance of the article content for a specific information need. The visual image representation can be an advantage in effectiveness (quality of found articles) and also in efficiency (speed of determining relevance or irrelevance) as many articles can likely be excluded much quicker by looking at a few representative images. In domains such as medical information retrieval, allowing to determine relevance quickly and accurately is an important criterion. This becomes even more important when small interfaces are used as it is frequently the case on mobile phones and tablets to access scientific data whenever information needs arise. In scientific articles many figures are used and particularly in the biomedical literature only a subset may be relevant for determining the relevance of a specific article to an information need. In many cases clinical images can be seen as more important for visual appearance than graphs or histograms that require looking at the context for interpretation. To get a clearer idea of image relevance in articles, a user test with a physician was performed who classified images of biomedical research articles into categories of importance that can subsequently be used to evaluate algorithms that automatically select images as representative examples. The manual sorting of images of 50 journal articles of BioMedCentral with each containing more than 8 figures by importance also allows to derive several rules that determine how to choose images and how to develop algorithms for choosing the most representative images of specific texts. This article describes the user tests and can be a first important step to evaluate automatic tools to select representative images for representing articles and potentially also images in other contexts, for example when representing patient records or other medical concepts when selecting images to represent RadLex terms in tutorials or interactive interfaces for example. This can help to make the image retrieval process more efficient and effective for physicians.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

Visual analytics for semantic queries of TerraSAR-X image content

NASA Astrophysics Data System (ADS)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain the image content using semantic terms and the relations between them answering questions such as what is the percentage of urban area in a region? or what is the distribution of water bodies in a city?

Collagen analysis by second-harmonic generation microscopy predicts outcome of luminal breast cancer.

PubMed

Natal, Rodrigo A; Vassallo, José; Paiva, Geisilene R; Pelegati, Vitor B; Barbosa, Guilherme O; Mendonça, Guilherme R; Bondarik, Caroline; Derchain, Sophie F; Carvalho, Hernandes F; Lima, Carmen S; Cesar, Carlos L; Sarian, Luís Otávio

2018-04-01

Second-harmonic generation microscopy represents an important tool to evaluate extracellular matrix collagen structure, which undergoes changes during cancer progression. Thus, it is potentially relevant to assess breast cancer development. We propose the use of second-harmonic generation images of tumor stroma selected on hematoxylin and eosin-stained slides to evaluate the prognostic value of collagen fibers analyses in peri and intratumoral areas in patients diagnosed with invasive ductal breast carcinoma. Quantitative analyses of collagen parameters were performed using ImageJ software. These parameters presented significantly higher values in peri than in intratumoral areas. Higher intratumoral collagen uniformity was associated with high pathological stages and with the presence of axillary lymph node metastasis. In patients with immunohistochemistry-based luminal subtype, higher intratumoral collagen uniformity and quantity were independently associated with poorer relapse-free and overall survival, respectively. A multivariate response recursive partitioning model determined 12.857 and 11.894 as the best cut-offs for intratumoral collagen quantity and uniformity, respectively. These values have shown high sensitivity and specificity to differentiate distinct outcomes. Values of intratumoral collagen quantity and uniformity exceeding the cut-offs were strongly associated with poorer relapse-free and overall survival. Our findings support a promising prognostic value of quantitative evaluation of intratumoral collagen by second-harmonic generation imaging mainly in the luminal subtype breast cancer.

Real space channelization for generic DBT system image quality evaluation with channelized Hotelling observer

NASA Astrophysics Data System (ADS)

Petrov, Dimitar; Cockmartin, Lesley; Marshall, Nicholas; Vancoillie, Liesbeth; Young, Kenneth; Bosmans, Hilde

2017-03-01

Digital breast tomosynthesis (DBT) is a relatively new 3D mammography technique that promises better detection of low contrast masses than conventional 2D mammography. The parameter space for DBT is large however and finding an optimal balance between dose and image quality remains challenging. Given the large number of conditions and images required in optimization studies, the use of human observers (HO) is time consuming and certainly not feasible for the tuning of all degrees of freedom. Our goal was to develop a model observer (MO) that could predict human detectability for clinically relevant details embedded within a newly developed structured phantom for DBT applications. DBT series were acquired on GE SenoClaire 3D, Giotto Class, Fujifilm AMULET Innovality and Philips MicroDose systems at different dose levels, Siemens Inspiration DBT acquisitions were reconstructed with different algorithms, while a larger set of DBT series was acquired on Hologic Dimensions system for first reproducibility testing. A channelized Hotelling observer (CHO) with Gabor channels was developed The parameters of the Gabor channels were tuned on all systems at standard scanning conditions and the candidate that produced the best fit for all systems was chosen. After tuning, the MO was applied to all systems and conditions. Linear regression lines between MO and HO scores were calculated, giving correlation coefficients between 0.87 and 0.99 for all tested conditions.

Image Search Reranking With Hierarchical Topic Awareness.

PubMed

Tian, Xinmei; Yang, Linjun; Lu, Yijuan; Tian, Qi; Tao, Dacheng

2015-10-01

With much attention from both academia and industrial communities, visual search reranking has recently been proposed to refine image search results obtained from text-based image search engines. Most of the traditional reranking methods cannot capture both relevance and diversity of the search results at the same time. Or they ignore the hierarchical topic structure of search result. Each topic is treated equally and independently. However, in real applications, images returned for certain queries are naturally in hierarchical organization, rather than simple parallel relation. In this paper, a new reranking method "topic-aware reranking (TARerank)" is proposed. TARerank describes the hierarchical topic structure of search results in one model, and seamlessly captures both relevance and diversity of the image search results simultaneously. Through a structured learning framework, relevance and diversity are modeled in TARerank by a set of carefully designed features, and then the model is learned from human-labeled training samples. The learned model is expected to predict reranking results with high relevance and diversity for testing queries. To verify the effectiveness of the proposed method, we collect an image search dataset and conduct comparison experiments on it. The experimental results demonstrate that the proposed TARerank outperforms the existing relevance-based and diversified reranking methods.

[Digital breast tomosynthesis : technical principles, current clinical relevance and future perspectives].

PubMed

Hellerhoff, K

2010-11-01

In recent years digital full field mammography has increasingly replaced conventional film mammography. High quality imaging is guaranteed by high quantum efficiency and very good contrast resolution with optimized dosing even for women with dense glandular tissue. However, digital mammography remains a projection procedure by which overlapping tissue limits the detectability of subtle alterations. Tomosynthesis is a procedure developed from digital mammography for slice examination of breasts which eliminates the effects of overlapping tissue and allows 3D imaging of breasts. A curved movement of the X-ray tube during scanning allows the acquisition of many 2D images from different angles. Subseqently, reconstruction algorithms employing a shift and add method improve the recognition of details at a defined level and at the same time eliminate smear artefacts due to overlapping structures. The total dose corresponds to that of conventional mammography imaging. The technical procedure, including the number of levels, suitable anodes/filter combinations, angle regions of images and selection of reconstruction algorithms, is presently undergoing optimization. Previous studies on the clinical value of tomosynthesis have examined screening parameters, such as recall rate and detection rate as well as information on tumor extent for histologically proven breast tumors. More advanced techniques, such as contrast medium-enhanced tomosynthesis, are presently under development and dual-energy imaging is of particular importance.

Multilayer thin-film phantoms for axial contrast transfer function measurement in optical coherence tomography.

PubMed

Agrawal, Anant; Chen, Chao-Wei; Baxi, Jigesh; Chen, Yu; Pfefer, T Joshua

2013-07-01

In optical coherence tomography (OCT), axial resolution is one of the most critical parameters impacting image quality. It is commonly measured by determining the point spread function (PSF) based on a specular surface reflection. The contrast transfer function (CTF) provides more insights into an imaging system's resolving characteristics and can be readily generated in a system-independent manner, without consideration for image pixel size. In this study, we developed a test method for determination of CTF based on multi-layer, thin-film phantoms, evaluated using spectral- and time-domain OCT platforms with different axial resolution values. Phantoms representing six spatial frequencies were fabricated and imaged. The fabrication process involved spin coating silicone films with precise thicknesses in the 8-40 μm range. Alternating layers were doped with a specified concentration of scattering particles. Validation of layer optical properties and thicknesses were achieved with spectrophotometry and stylus profilometry, respectively. OCT B-scans were used to calculate CTFs and results were compared with convetional PSF measurements based on specular reflections. Testing of these phantoms indicated that our approach can provide direct access to axial resolution characteristics highly relevant to image quality. Furthermore, tissue phantoms based on our thin-film fabrication approach may have a wide range of additional applications in optical imaging and spectroscopy.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

PubMed

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

Pulsatility Index as a Diagnostic Parameter of Reciprocating Wall Shear Stress Parameters in Physiological Pulsating Waveforms

PubMed Central

Avrahami, Idit; Kersh, Dikla

2016-01-01

Arterial wall shear stress (WSS) parameters are widely used for prediction of the initiation and development of atherosclerosis and arterial pathologies. Traditional clinical evaluation of arterial condition relies on correlations of WSS parameters with average flow rate (Q) and heart rate (HR) measurements. We show that for pulsating flow waveforms in a straight tube with flow reversals that lead to significant reciprocating WSS, the measurements of HR and Q are not sufficient for prediction of WSS parameters. Therefore, we suggest adding a third quantity—known as the pulsatility index (PI)—which is defined as the peak-to-peak flow rate amplitude normalized by Q. We examine several pulsating flow waveforms with and without flow reversals using a simulation of a Womersley model in a straight rigid tube and validate the simulations through experimental study using particle image velocimetry (PIV). The results indicate that clinically relevant WSS parameters such as the percentage of negative WSS (P[%]), oscillating shear index (OSI) and the ratio of minimum to maximum shear stress rates (min/max), are better predicted when the PI is used in conjunction with HR and Q. Therefore, we propose to use PI as an additional and essential diagnostic quantity for improved predictability of the reciprocating WSS. PMID:27893801

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

NASA Astrophysics Data System (ADS)

Ewerlöf, Maria; Larsson, Marcus; Salerud, E. Göran

2017-02-01

Hyperspectral imaging (HSI) can estimate the spatial distribution of skin blood oxygenation, using visible to near-infrared light. HSI oximeters often use a liquid-crystal tunable filter, an acousto-optic tunable filter or mechanically adjustable filter wheels, which has too long response/switching times to monitor tissue hemodynamics. This work aims to evaluate a multispectral snapshot imaging system to estimate skin blood volume and oxygen saturation with high temporal and spatial resolution. We use a snapshot imager, the xiSpec camera (MQ022HG-IM-SM4X4-VIS, XIMEA), having 16 wavelength-specific Fabry-Perot filters overlaid on the custom CMOS-chip. The spectral distribution of the bands is however substantially overlapping, which needs to be taken into account for an accurate analysis. An inverse Monte Carlo analysis is performed using a two-layered skin tissue model, defined by epidermal thickness, haemoglobin concentration and oxygen saturation, melanin concentration and spectrally dependent reduced-scattering coefficient, all parameters relevant for human skin. The analysis takes into account the spectral detector response of the xiSpec camera. At each spatial location in the field-of-view, we compare the simulated output to the detected diffusively backscattered spectra to find the best fit. The imager is evaluated for spatial and temporal variations during arterial and venous occlusion protocols applied to the forearm. Estimated blood volume changes and oxygenation maps at 512x272 pixels show values that are comparable to reference measurements performed in contact with the skin tissue. We conclude that the snapshot xiSpec camera, paired with an inverse Monte Carlo algorithm, permits us to use this sensor for spatial and temporal measurement of varying physiological parameters, such as skin tissue blood volume and oxygenation.

Quantitative in vivo imaging of tissue factor expression in glioma using dynamic contrast-enhanced MRI derived parameters.

PubMed

Chen, Xiao; Xie, Tian; Fang, Jingqin; Xue, Wei; Tong, Haipeng; Kang, Houyi; Wang, Sumei; Yang, Yizeng; Xu, Minhui; Zhang, Weiguo

2017-08-01

Tissue Factor (TF) has been well established in angiogenesis, invasion, metastasis, and prognosis in glioma. A noninvasive assessment of TF expression status in glioma is therefore of obvious clinical relevance. Dynamic contrast-enhanced (DCE) MRI parameters have been used to evaluate microvascular characteristics and predict molecular expression status in tumors. Our aim is to investigate whether quantitative DCE-MRI parameters could assess TF expression in glioma. Thirty-two patients with histopathologically diagnosed supratentorial glioma who underwent DCE-MRI were retrospectively recruited. Extended Tofts linear model was used for DCE-MRI post-processing. Hot-spot, whole tumor cross-sectional approaches, and histogram were used for analysis of model based parameters. Four serial paraffin sections of each case were stained with TF, CD105, CD34 and α-Sooth Muscle Actin, respectively for evaluating the association of TF and microvascular properties. Pearson correlation was performed between percentage of TF expression area and DCE-MRI parameters, multiple microvascular indexes. Volume transfer constant (K trans ) hot-spot value best correlated with TF (r=0.886, p<0.001), followed by 90th percentile K trans value (r=0.801, p<0.001). Moreover, histogram analysis of K trans value demonstrated that weak TF expression was associated with less heterogeneous and positively skewed distribution. Finally, pathology analysis revealed TF was associated with glioma grade and significantly correlated with these two dynamic angiogenic indexes which could be used to explain the strong correlation between K trans and TF expression. Our results indicate that K trans may serve as a potential clinical imaging biomarker to predict TF expression status preoperatively in gliomas. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling of Soft Poroelastic Tissue in Time-Harmonic MR Elastography

PubMed Central

Perriñez, Phillip R.; Kennedy, Francis E.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.

2010-01-01

Elastography is an emerging imaging technique that focuses on assessing the resistance to deformation of soft biological tissues in vivo. Magnetic resonance elastography (MRE) uses measured displacement fields resulting from low-amplitude, low-frequency (10 Hz–1 kHz) time-harmonic vibration to recover images of the elastic property distribution of tissues including breast, liver, muscle, prostate, and brain. While many soft tissues display complex time-dependent behavior not described by linear elasticity, the models most commonly employed in MRE parameter reconstructions are based on elastic assumptions. Further, elasticity models fail to include the interstitial fluid phase present in vivo. Alternative continuum models, such as consolidation theory, are able to represent tissue and other materials comprising two distinct phases, generally consisting of a porous elastic solid and penetrating fluid. MRE reconstructions of simulated elastic and poroelastic phantoms were performed to investigate the limitations of current-elasticity-based methods in producing accurate elastic parameter estimates in poroelastic media. The results indicate that linearly elastic reconstructions of fluid-saturated porous media at amplitudes and frequencies relevant to steady-state MRE can yield misleading effective property distributions resulting from the complex interaction between their solid and fluid phases. PMID:19272864

Intrinsic speckle noise in in-line particle holography due to polydisperse and continuous particle sizes

NASA Astrophysics Data System (ADS)

Edwards, Philip J.; Hobson, Peter R.; Rodgers, G. J.

2000-08-01

In-line particle holography is subject to image deterioration due to intrinsic speckle noise. The resulting reduction in the signal to noise ratio (SNR) of the replayed image can become critical for applications such as holographic particle velocimetry (HPV) and 3D visualisation of marine plankton. Work has been done to extend the mono-disperse model relevant to HPV to include poly-disperse particle fields appropriate for the visualisation of marine plankton. Continuous and discrete particle fields are both considered. It is found that random walk statistics still apply for the poly-disperse case. The speckle field is simply the summation of the individual speckle patters due to each scatter size. Therefor the characteristic speckle parameter (which encompasses particle diameter, concentration and sample depth) is alos just the summation of the individual speckle parameters. This reduces the SNR calculation to the same form as for the mono-disperse case. For the continuous situation three distributions, power, exponential and Gaussian are discussed with the resulting SNR calcuated. The work presented here was performed as part of the Holomar project to produce a working underwater holographic camera for recording plankton.

Contrast-enhanced T1-weighted fluid-attenuated inversion-recovery BLADE magnetic resonance imaging of the brain: an alternative to spin-echo technique for detection of brain lesions in the unsedated pediatric patient?

PubMed

Alibek, Sedat; Adamietz, Boris; Cavallaro, Alexander; Stemmer, Alto; Anders, Katharina; Kramer, Manuel; Bautz, Werner; Staatz, Gundula

2008-08-01

We compared contrast-enhanced T1-weighted magnetic resonance (MR) imaging of the brain using different types of data acquisition techniques: periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER, BLADE) imaging versus standard k-space sampling (conventional spin-echo pulse sequence) in the unsedated pediatric patient with focus on artifact reduction, overall image quality, and lesion detectability. Forty-eight pediatric patients (aged 3 months to 18 years) were scanned with a clinical 1.5-T whole body MR scanner. Cross-sectional contrast-enhanced T1-weighted spin-echo sequence was compared to a T1-weighted dark-fluid fluid-attenuated inversion-recovery (FLAIR) BLADE sequence for qualitative and quantitative criteria (image artifacts, image quality, lesion detectability) by two experienced radiologists. Imaging protocols were matched for imaging parameters. Reader agreement was assessed using the exact Bowker test. BLADE images showed significantly less pulsation and motion artifacts than the standard T1-weighted spin-echo sequence scan. BLADE images showed statistically significant lower signal-to-noise ratio but higher contrast-to-noise ratios with superior gray-white matter contrast. All lesions were demonstrated on FLAIR BLADE imaging, and one false-positive lesion was visible in spin-echo sequence images. BLADE MR imaging at 1.5 T is applicable for central nervous system imaging of the unsedated pediatric patient, reduces motion and pulsation artifacts, and minimizes the need for sedation or general anesthesia without loss of relevant diagnostic information.

Active browsing using similarity pyramids

NASA Astrophysics Data System (ADS)

Chen, Jau-Yuen; Bouman, Charles A.; Dalton, John C.

1998-12-01

In this paper, we describe a new approach to managing large image databases, which we call active browsing. Active browsing integrates relevance feedback into the browsing environment, so that users can modify the database's organization to suit the desired task. Our method is based on a similarity pyramid data structure, which hierarchically organizes the database, so that it can be efficiently browsed. At coarse levels, the similarity pyramid allows users to view the database as large clusters of similar images. Alternatively, users can 'zoom into' finer levels to view individual images. We discuss relevance feedback for the browsing process, and argue that it is fundamentally different from relevance feedback for more traditional search-by-query tasks. We propose two fundamental operations for active browsing: pruning and reorganization. Both of these operations depend on a user-defined relevance set, which represents the image or set of images desired by the user. We present statistical methods for accurately pruning the database, and we propose a new 'worm hole' distance metric for reorganizing the database, so that members of the relevance set are grouped together.

Visual Image Sensor Organ Replacement: Implementation

NASA Technical Reports Server (NTRS)

Maluf, A. David (Inventor)

2011-01-01

Method and system for enhancing or extending visual representation of a selected region of a visual image, where visual representation is interfered with or distorted, by supplementing a visual signal with at least one audio signal having one or more audio signal parameters that represent one or more visual image parameters, such as vertical and/or horizontal location of the region; region brightness; dominant wavelength range of the region; change in a parameter value that characterizes the visual image, with respect to a reference parameter value; and time rate of change in a parameter value that characterizes the visual image. Region dimensions can be changed to emphasize change with time of a visual image parameter.

Tomographic inversion techniques incorporating physical constraints for line integrated spectroscopy in stellarators and tokamaks

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

Pablant, N. A.; Bell, R. E.; Bitter, M.

2014-11-15

Accurate tomographic inversion is important for diagnostic systems on stellarators and tokamaks which rely on measurements of line integrated emission spectra. A tomographic inversion technique based on spline optimization with enforcement of constraints is described that can produce unique and physically relevant inversions even in situations with noisy or incomplete input data. This inversion technique is routinely used in the analysis of data from the x-ray imaging crystal spectrometer (XICS) installed at the Large Helical Device. The XICS diagnostic records a 1D image of line integrated emission spectra from impurities in the plasma. Through the use of Doppler spectroscopy andmore » tomographic inversion, XICS can provide profile measurements of the local emissivity, temperature, and plasma flow. Tomographic inversion requires the assumption that these measured quantities are flux surface functions, and that a known plasma equilibrium reconstruction is available. In the case of low signal levels or partial spatial coverage of the plasma cross-section, standard inversion techniques utilizing matrix inversion and linear-regularization often cannot produce unique and physically relevant solutions. The addition of physical constraints, such as parameter ranges, derivative directions, and boundary conditions, allow for unique solutions to be reliably found. The constrained inversion technique described here utilizes a modified Levenberg-Marquardt optimization scheme, which introduces a condition avoidance mechanism by selective reduction of search directions. The constrained inversion technique also allows for the addition of more complicated parameter dependencies, for example, geometrical dependence of the emissivity due to asymmetries in the plasma density arising from fast rotation. The accuracy of this constrained inversion technique is discussed, with an emphasis on its applicability to systems with limited plasma coverage.« less

Tomographic inversion techniques incorporating physical constraints for line integrated spectroscopy in stellarators and tokamaksa)

DOE PAGES

Pablant, N. A.; Bell, R. E.; Bitter, M.; ...

2014-08-08

Accurate tomographic inversion is important for diagnostic systems on stellarators and tokamaks which rely on measurements of line integrated emission spectra. A tomographic inversion technique based on spline optimization with enforcement of constraints is described that can produce unique and physically relevant inversions even in situations with noisy or incomplete input data. This inversion technique is routinely used in the analysis of data from the x-ray imaging crystal spectrometer (XICS) installed at LHD. The XICS diagnostic records a 1D image of line integrated emission spectra from impurities in the plasma. Through the use of Doppler spectroscopy and tomographic inversion, XICSmore » can provide pro file measurements of the local emissivity, temperature and plasma flow. Tomographic inversion requires the assumption that these measured quantities are flux surface functions, and that a known plasma equilibrium reconstruction is available. In the case of low signal levels or partial spatial coverage of the plasma cross-section, standard inversion techniques utilizing matrix inversion and linear-regularization often cannot produce unique and physically relevant solutions. The addition of physical constraints, such as parameter ranges, derivative directions, and boundary conditions, allow for unique solutions to be reliably found. The constrained inversion technique described here utilizes a modifi ed Levenberg-Marquardt optimization scheme, which introduces a condition avoidance mechanism by selective reduction of search directions. The constrained inversion technique also allows for the addition of more complicated parameter dependencies, for example geometrical dependence of the emissivity due to asymmetries in the plasma density arising from fast rotation. The accuracy of this constrained inversion technique is discussed, with an emphasis on its applicability to systems with limited plasma coverage.« less

Respiratory motion compensated overlay of surface models from cardiac MR on interventional x-ray fluoroscopy for guidance of cardiac resynchronization therapy procedures

NASA Astrophysics Data System (ADS)

Manzke, R.; Bornstedt, A.; Lutz, A.; Schenderlein, M.; Hombach, V.; Binner, L.; Rasche, V.

2010-02-01

Various multi-center trials have shown that cardiac resynchronization therapy (CRT) is an effective procedure for patients with end-stage drug invariable heart failure (HF). Despite the encouraging results of CRT, at least 30% of patients do not respond to the treatment. Detailed knowledge of the cardiac anatomy (coronary venous tree, left ventricle), functional parameters (i.e. ventricular synchronicity) is supposed to improve CRT patient selection and interventional lead placement for reduction of the number of non-responders. As a pre-interventional imaging modality, cardiac magnetic resonance (CMR) imaging has the potential to provide all relevant information. With functional information from CMR optimal implantation target sites may be better identified. Pre-operative CMR could also help to determine whether useful vein target segments are available for lead placement. Fused with X-ray, the mainstay interventional modality, improved interventional guidance for lead-placement could further help to increase procedure outcome. In this contribution, we present novel and practicable methods for a) pre-operative functional and anatomical imaging of relevant cardiac structures to CRT using CMR, b) 2D-3D registration of CMR anatomy and functional meshes with X-ray vein angiograms and c) real-time capable breathing motion compensation for improved fluoroscopy mesh overlay during the intervention based on right ventricular pacer lead tracking. With these methods, enhanced interventional guidance for left ventricular lead placement is provided.

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Image informative maps for component-wise estimating parameters of signal-dependent noise

NASA Astrophysics Data System (ADS)

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem

2013-01-01

We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.

Optimization of intra-voxel incoherent motion imaging at 3.0 Tesla for fast liver examination.

PubMed

Leporq, Benjamin; Saint-Jalmes, Hervé; Rabrait, Cecile; Pilleul, Frank; Guillaud, Olivier; Dumortier, Jérôme; Scoazec, Jean-Yves; Beuf, Olivier

2015-05-01

Optimization of multi b-values MR protocol for fast intra-voxel incoherent motion imaging of the liver at 3.0 Tesla. A comparison of four different acquisition protocols were carried out based on estimated IVIM (DSlow , DFast , and f) and ADC-parameters in 25 healthy volunteers. The effects of respiratory gating compared with free breathing acquisition then diffusion gradient scheme (simultaneous or sequential) and finally use of weighted averaging for different b-values were assessed. An optimization study based on Cramer-Rao lower bound theory was then performed to minimize the number of b-values required for a suitable quantification. The duration-optimized protocol was evaluated on 12 patients with chronic liver diseases No significant differences of IVIM parameters were observed between the assessed protocols. Only four b-values (0, 12, 82, and 1310 s.mm(-2) ) were found mandatory to perform a suitable quantification of IVIM parameters. DSlow and DFast significantly decreased between nonadvanced and advanced fibrosis (P < 0.05 and P < 0.01) whereas perfusion fraction and ADC variations were not found to be significant. Results showed that IVIM could be performed in free breathing, with a weighted-averaging procedure, a simultaneous diffusion gradient scheme and only four optimized b-values (0, 10, 80, and 800) reducing scan duration by a factor of nine compared with a nonoptimized protocol. Preliminary results have shown that parameters such as DSlow and DFast based on optimized IVIM protocol can be relevant biomarkers to distinguish between nonadvanced and advanced fibrosis. © 2014 Wiley Periodicals, Inc.

Local Variability of Parameters for Characterization of the Corneal Subbasal Nerve Plexus.

PubMed

Winter, Karsten; Scheibe, Patrick; Köhler, Bernd; Allgeier, Stephan; Guthoff, Rudolf F; Stachs, Oliver

2016-01-01

The corneal subbasal nerve plexus (SNP) offers high potential for early diagnosis of diabetic peripheral neuropathy. Changes in subbasal nerve fibers can be assessed in vivo by confocal laser scanning microscopy (CLSM) and quantified using specific parameters. While current study results agree regarding parameter tendency, there are considerable differences in terms of absolute values. The present study set out to identify factors that might account for this high parameter variability. In three healthy subjects, we used a novel method of software-based large-scale reconstruction that provided SNP images of the central cornea, decomposed the image areas into all possible image sections corresponding to the size of a single conventional CLSM image (0.16 mm2), and calculated a set of parameters for each image section. In order to carry out a large number of virtual examinations within the reconstructed image areas, an extensive simulation procedure (10,000 runs per image) was implemented. The three analyzed images ranged in size from 3.75 mm2 to 4.27 mm2. The spatial configuration of the subbasal nerve fiber networks varied greatly across the cornea and thus caused heavily location-dependent results as well as wide value ranges for the parameters assessed. Distributions of SNP parameter values varied greatly between the three images and showed significant differences between all images for every parameter calculated (p < 0.001 in each case). The relatively small size of the conventionally evaluated SNP area is a contributory factor in high SNP parameter variability. Averaging of parameter values based on multiple CLSM frames does not necessarily result in good approximations of the respective reference values of the whole image area. This illustrates the potential for examiner bias when selecting SNP images in the central corneal area.

General equations for optimal selection of diagnostic image acquisition parameters in clinical X-ray imaging.

PubMed

Zheng, Xiaoming

2017-12-01

The purpose of this work was to examine the effects of relationship functions between diagnostic image quality and radiation dose on the governing equations for image acquisition parameter variations in X-ray imaging. Various equations were derived for the optimal selection of peak kilovoltage (kVp) and exposure parameter (milliAmpere second, mAs) in computed tomography (CT), computed radiography (CR), and direct digital radiography. Logistic, logarithmic, and linear functions were employed to establish the relationship between radiation dose and diagnostic image quality. The radiation dose to the patient, as a function of image acquisition parameters (kVp, mAs) and patient size (d), was used in radiation dose and image quality optimization. Both logistic and logarithmic functions resulted in the same governing equation for optimal selection of image acquisition parameters using a dose efficiency index. For image quality as a linear function of radiation dose, the same governing equation was derived from the linear relationship. The general equations should be used in guiding clinical X-ray imaging through optimal selection of image acquisition parameters. The radiation dose to the patient could be reduced from current levels in medical X-ray imaging.

Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

PubMed

Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

2018-04-01

Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd. All rights reserved.

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

A sparse representation of the pathologist's interaction with whole slide images to improve the assigned relevance of regions of interest

NASA Astrophysics Data System (ADS)

Santiago, Daniel; Corredor, Germán.; Romero, Eduardo

2017-11-01

During a diagnosis task, a Pathologist looks over a Whole Slide Image (WSI), aiming to find out relevant pathological patterns. Nonetheless, a virtual microscope captures these structures, but also other cellular patterns with different or none diagnostic meaning. Annotation of these images depends on manual delineation, which in practice becomes a hard task. This article contributes a new method for detecting relevant regions in WSI using the routine navigations in a virtual microscope. This method constructs a sparse representation or dictionary of each navigation path and determines the hidden relevance by maximizing the incoherence between several paths. The resulting dictionaries are then projected onto each other and relevant information is set to the dictionary atoms whose similarity is higher than a custom threshold. Evaluation was performed with 6 pathological images segmented from a skin biopsy already diagnosed with basal cell carcinoma (BCC). Results show that our proposal outperforms the baseline by more than 20%.

Reconstruction of quadratic curves in 3D using two or more perspective views: simulation studies

NASA Astrophysics Data System (ADS)

Kumar, Sanjeev; Sukavanam, N.; Balasubramanian, R.

2006-01-01

The shapes of many natural and man-made objects have planar and curvilinear surfaces. The images of such curves usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. In this paper, we describe a method of reconstruction of a quadratic curve in 3-D space as an intersection of two cones containing the respective projected curve images. The correspondence between this pair of projections of the curve is assumed to be established in this work. Using least-square curve fitting, the parameters of a curve in 2-D space are found. From this we are reconstructing the 3-D quadratic curve. Relevant mathematical formulations and analytical solutions for obtaining the equation of reconstructed curve are given. The result of the described reconstruction methodology are studied by simulation studies. This reconstruction methodology is applicable to LBW decision in cricket, path of the missile, Robotic Vision, path lanning etc.

Image analysis supported moss cell disruption in photo-bioreactors.

PubMed

Lucumi, A; Posten, C; Pons, M-N

2005-05-01

Diverse methods for the disruption of cell entanglements and pellets of the moss Physcomitrella patens were tested in order to improve the homogeneity of suspension cultures. The morphological characterization of the moss was carried out by means of image analysis. Selected morphological parameters were defined and compared to the reduction of the carbon dioxide fixation, and the released pigments after cell disruption. The size control of the moss entanglements based on the rotor stator principle allowed a focused shear stress, avoiding a severe reduction in the photosynthesis. Batch cultures of P. patens in a 30.0-l pilot tubular photo-bioreactor with cell disruption showed no significant variation in growth rate and a delayed cell differentiation, when compared to undisrupted cultures. A highly controlled photoautotrophic culture of P. patens in a scalable photo-bioreactor was established, contributing to the development required for the future use of mosses as producers of relevant heterologous proteins.

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

PubMed Central

del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J.; Raboso, Mariano

2015-01-01

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements. PMID:26091392

A model for acoustic vaporization dynamics of a bubble/droplet system encapsulated within a hyperelastic shell.

PubMed

Lacour, Thomas; Guédra, Matthieu; Valier-Brasier, Tony; Coulouvrat, François

2018-01-01

Nanodroplets have great, promising medical applications such as contrast imaging, embolotherapy, or targeted drug delivery. Their functions can be mechanically activated by means of focused ultrasound inducing a phase change of the inner liquid known as the acoustic droplet vaporization (ADV) process. In this context, a four-phases (vapor + liquid + shell + surrounding environment) model of ADV is proposed. Attention is especially devoted to the mechanical properties of the encapsulating shell, incorporating the well-known strain-softening behavior of Mooney-Rivlin material adapted to very large deformations of soft, nearly incompressible materials. Various responses to ultrasound excitation are illustrated, depending on linear and nonlinear mechanical shell properties and acoustical excitation parameters. Different classes of ADV outcomes are exhibited, and a relevant threshold ensuring complete vaporization of the inner liquid layer is defined. The dependence of this threshold with acoustical, geometrical, and mechanical parameters is also provided.

Compositional and textural information from the dual inversion of visible, near and thermal infrared remotely sensed data

NASA Technical Reports Server (NTRS)

Brackett, Robert A.; Arvidson, Raymond E.

1993-01-01

A technique is presented that allows extraction of compositional and textural information from visible, near and thermal infrared remotely sensed data. Using a library of both emissivity and reflectance spectra, endmember abundances and endmember thermal inertias are extracted from AVIRIS (Airborne Visible and Infrared Imaging Spectrometer) and TIMS (Thermal Infrared Mapping Spectrometer) data over Lunar Crater Volcanic Field, Nevada, using a dual inversion. The inversion technique is motivated by upcoming Mars Observer data and the need for separation of composition and texture parameters from sub pixel mixtures of bedrock and dust. The model employed offers the opportunity to extract compositional and textural information for a variety of endmembers within a given pixel. Geologic inferences concerning grain size, abundance, and source of endmembers can be made directly from the inverted data. These parameters are of direct relevance to Mars exploration, both for Mars Observer and for follow-on missions.

A Simple fMRI Compatible Robotic Stimulator to Study the Neural Mechanisms of Touch and Pain.

PubMed

Riillo, F; Bagnato, C; Allievi, A G; Takagi, A; Fabrizi, L; Saggio, G; Arichi, T; Burdet, E

2016-08-01

This paper presents a simple device for the investigation of the human somatosensory system with functional magnetic imaging (fMRI). PC-controlled pneumatic actuation is employed to produce innocuous or noxious mechanical stimulation of the skin. Stimulation patterns are synchronized with fMRI and other relevant physiological measurements like electroencephalographic activity and vital physiological parameters. The system allows adjustable regulation of stimulation parameters and provides consistent patterns of stimulation. A validation experiment demonstrates that the system safely and reliably identifies clusters of functional activity in brain regions involved in the processing of pain. This new device is inexpensive, portable, easy-to-assemble and customizable to suit different experimental requirements. It provides robust and consistent somatosensory stimulation, which is of crucial importance to investigating the mechanisms of pain and its strong connection with the sense of touch.

Inferring subunit stoichiometry from single molecule photobleaching

PubMed Central

2013-01-01

Single molecule photobleaching is a powerful tool for determining the stoichiometry of protein complexes. By attaching fluorophores to proteins of interest, the number of associated subunits in a complex can be deduced by imaging single molecules and counting fluorophore photobleaching steps. Because some bleaching steps might be unobserved, the ensemble of steps will be binomially distributed. In this work, it is shown that inferring the true composition of a complex from such data is nontrivial because binomially distributed observations present an ill-posed inference problem. That is, a unique and optimal estimate of the relevant parameters cannot be extracted from the observations. Because of this, a method has not been firmly established to quantify confidence when using this technique. This paper presents a general inference model for interpreting such data and provides methods for accurately estimating parameter confidence. The formalization and methods presented here provide a rigorous analytical basis for this pervasive experimental tool. PMID:23712552

Does the choice of display system influence perception and visibility of clinically relevant features in digital pathology images?

NASA Astrophysics Data System (ADS)

Kimpe, Tom; Rostang, Johan; Avanaki, Ali; Espig, Kathryn; Xthona, Albert; Cocuranu, Ioan; Parwani, Anil V.; Pantanowitz, Liron

2014-03-01

Digital pathology systems typically consist of a slide scanner, processing software, visualization software, and finally a workstation with display for visualization of the digital slide images. This paper studies whether digital pathology images can look different when presenting them on different display systems, and whether these visual differences can result in different perceived contrast of clinically relevant features. By analyzing a set of four digital pathology images of different subspecialties on three different display systems, it was concluded that pathology images look different when visualized on different display systems. The importance of these visual differences is elucidated when they are located in areas of the digital slide that contain clinically relevant features. Based on a calculation of dE2000 differences between background and clinically relevant features, it was clear that perceived contrast of clinically relevant features is influenced by the choice of display system. Furthermore, it seems that the specific calibration target chosen for the display system has an important effect on the perceived contrast of clinically relevant features. Preliminary results suggest that calibrating to DICOM GSDF calibration performed slightly worse than sRGB, while a new experimental calibration target CSDF performed better than both DICOM GSDF and sRGB. This result is promising as it suggests that further research work could lead to better definition of an optimized calibration target for digital pathology images resulting in a positive effect on clinical performance.

A theoretical framework to model DSC-MRI data acquired in the presence of contrast agent extravasation

NASA Astrophysics Data System (ADS)

Quarles, C. C.; Gochberg, D. F.; Gore, J. C.; Yankeelov, T. E.

2009-10-01

Dynamic susceptibility contrast (DSC) MRI methods rely on compartmentalization of the contrast agent such that a susceptibility gradient can be induced between the contrast-containing compartment and adjacent spaces, such as between intravascular and extravascular spaces. When there is a disruption of the blood-brain barrier, as is frequently the case with brain tumors, a contrast agent leaks out of the vasculature, resulting in additional T1, T2 and T*2 relaxation effects in the extravascular space, thereby affecting the signal intensity time course and reducing the reliability of the computed hemodynamic parameters. In this study, a theoretical model describing these dynamic intra- and extravascular T1, T2 and T*2 relaxation interactions is proposed. The applicability of using the proposed model to investigate the influence of relevant MRI pulse sequences (e.g. echo time, flip angle), and physical (e.g. susceptibility calibration factors, pre-contrast relaxation rates) and physiological parameters (e.g. permeability, blood flow, compartmental volume fractions) on DSC-MRI signal time curves is demonstrated. Such a model could yield important insights into the biophysical basis of contrast-agent-extravasastion-induced effects on measured DSC-MRI signals and provide a means to investigate pulse sequence optimization and appropriate data analysis methods for the extraction of physiologically relevant imaging metrics.

GREAT: a gradient-based color-sampling scheme for Retinex.

PubMed

Lecca, Michela; Rizzi, Alessandro; Serapioni, Raul Paolo

2017-04-01

Modeling the local color spatial distribution is a crucial step for the algorithms of the Milano Retinex family. Here we present GREAT, a novel, noise-free Milano Retinex implementation based on an image-aware spatial color sampling. For each channel of a color input image, GREAT computes a 2D set of edges whose magnitude exceeds a pre-defined threshold. Then GREAT re-scales the channel intensity of each image pixel, called target, by the average of the intensities of the selected edges weighted by a function of their positions, gradient magnitudes, and intensities relative to the target. In this way, GREAT enhances the input image, adjusting its brightness, contrast and dynamic range. The use of the edges as pixels relevant to color filtering is justified by the importance that edges play in human color sensation. The name GREAT comes from the expression "Gradient RElevAnce for ReTinex," which refers to the threshold-based definition of a gradient relevance map for edge selection and thus for image color filtering.

Combined Clinical Parameters and Multiparametric Magnetic Resonance Imaging for Advanced Risk Modeling of Prostate Cancer-Patient-tailored Risk Stratification Can Reduce Unnecessary Biopsies.

PubMed

Radtke, Jan Philipp; Wiesenfarth, Manuel; Kesch, Claudia; Freitag, Martin T; Alt, Celine D; Celik, Kamil; Distler, Florian; Roth, Wilfried; Wieczorek, Kathrin; Stock, Christian; Duensing, Stefan; Roethke, Matthias C; Teber, Dogu; Schlemmer, Heinz-Peter; Hohenfellner, Markus; Bonekamp, David; Hadaschik, Boris A

2017-12-01

Multiparametric magnetic resonance imaging (mpMRI) is gaining widespread acceptance in prostate cancer (PC) diagnosis and improves significant PC (sPC; Gleason score≥3+4) detection. Decision making based on European Randomised Study of Screening for PC (ERSPC) risk-calculator (RC) parameters may overcome prostate-specific antigen (PSA) limitations. We added pre-biopsy mpMRI to ERSPC-RC parameters and developed risk models (RMs) to predict individual sPC risk for biopsy-naïve men and men after previous biopsy. We retrospectively analyzed clinical parameters of 1159 men who underwent mpMRI prior to MRI/transrectal ultrasound fusion biopsy between 2012 and 2015. Multivariate regression analyses were used to determine significant sPC predictors for RM development. The prediction performance was compared with ERSPC-RCs, RCs refitted on our cohort, Prostate Imaging Reporting and Data System (PI-RADS) v1.0, and ERSPC-RC plus PI-RADSv1.0 using receiver-operating characteristics (ROCs). Discrimination and calibration of the RM, as well as net decision and reduction curve analyses were evaluated based on resampling methods. PSA, prostate volume, digital-rectal examination, and PI-RADS were significant sPC predictors and included in the RMs together with age. The ROC area under the curve of the RM for biopsy-naïve men was comparable with ERSPC-RC3 plus PI-RADSv1.0 (0.83 vs 0.84) but larger compared with ERSPC-RC3 (0.81), refitted RC3 (0.80), and PI-RADS (0.76). For postbiopsy men, the novel RM's discrimination (0.81) was higher, compared with PI-RADS (0.78), ERSPC-RC4 (0.66), refitted RC4 (0.76), and ERSPC-RC4 plus PI-RADSv1.0 (0.78). Both RM benefits exceeded those of ERSPC-RCs and PI-RADS in the decision regarding which patient to receive biopsy and enabled the highest reduction rate of unnecessary biopsies. Limitations include a monocentric design and a lack of PI-RADSv2.0. The novel RMs, incorporating clinical parameters and PI-RADS, performed significantly better compared with RMs without PI-RADS and provided measurable benefit in making the decision to biopsy men at a suspicion of PC. For biopsy-naïve patients, both our RM and ERSPC-RC3 plus PI-RADSv1.0 exceeded the prediction performance compared with clinical parameters alone. Combined risk models including clinical and imaging parameters predict clinically relevant prostate cancer significantly better than clinical risk calculators and multiparametric magnetic resonance imaging alone. The risk models demonstrate a benefit in making a decision about which patient needs a biopsy and concurrently help avoid unnecessary biopsies. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Rapid Solidification in Bulk Ti-Nb Alloys by Single-Track Laser Melting

NASA Astrophysics Data System (ADS)

Roehling, John D.; Perron, Aurélien; Fattebert, Jean-Luc; Haxhimali, Tomorr; Guss, Gabe; Li, Tian T.; Bober, David; Stokes, Adam W.; Clarke, Amy J.; Turchi, Patrice E. A.; Matthews, Manyalibo J.; McKeown, Joseph T.

2018-05-01

Single-track laser melting experiments were performed on bulk Ti-Nb alloys to explore process parameters and the resultant macroscopic structure and microstructure. The microstructures in Ti-20Nb and Ti-50Nb (at.%) alloys exhibited cellular growth during rapid solidification, with average cell size of approximately 0.5 µm. Solidification velocities during cellular growth were calculated from images of melt tracks. Measurements of the composition in the cellular and intercellular regions revealed nonequilibrium partitioning and its dependence on velocity during rapid solidification. Experimental results were used to benchmark a phase-field model to describe rapid solidification under conditions relevant to additive manufacturing.

Fitting PMT Responses with an Artificial Neural Network

NASA Astrophysics Data System (ADS)

Kemmerer, William; Niculescu, Gabriel

2017-09-01

Correctly modeling the low light responce of photodetectors such as photomultiplier tubes (PMT) is crucial for the operation of particle detection relying on the Cherenkov effect. The Gas Ring Imaging Cherenkov (GRINCH) in the SuperBigBite Spectrometer (SBS) at Jefferson Lab will rely on an array of 510 29 mm 9125B PMTs. To select the tubes for this array, more than 900 were tested and their low-light response function was fitted. An Artificial Neural Network was defined and trained to extract the relevant PMT parameters without carrying out a detailed fir of the ADC spectrum. These results will be discussed here. NSF.

On the dynamical basis of the classification of normal galaxies

PubMed Central

Haass, J.; Bertin, G.; Lin, C. C.

1982-01-01

Some realistic galaxy models have been found to support discrete unstable spiral modes. Here, through the study of the relevant physical mechanisms and an extensive numerical investigation of the properties of the dominant modes in a wide class of galactic equilibria, we show how spiral structures are excited with different morphological features, depending on the properties of the equilibrium model. We identify the basic dynamical parameters and mechanisms and compare the resulting morphology of spiral modes with the actual classification of galaxies. The present study suggests a dynamical basis for the transition among various types and subclasses of normal and barred spiral galaxies. Images PMID:16593200

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Automated detection using natural language processing of radiologists recommendations for additional imaging of incidental findings.

PubMed

Dutta, Sayon; Long, William J; Brown, David F M; Reisner, Andrew T

2013-08-01

As use of radiology studies increases, there is a concurrent increase in incidental findings (eg, lung nodules) for which the radiologist issues recommendations for additional imaging for follow-up. Busy emergency physicians may be challenged to carefully communicate recommendations for additional imaging not relevant to the patient's primary evaluation. The emergence of electronic health records and natural language processing algorithms may help address this quality gap. We seek to describe recommendations for additional imaging from our institution and develop and validate an automated natural language processing algorithm to reliably identify recommendations for additional imaging. We developed a natural language processing algorithm to detect recommendations for additional imaging, using 3 iterative cycles of training and validation. The third cycle used 3,235 radiology reports (1,600 for algorithm training and 1,635 for validation) of discharged emergency department (ED) patients from which we determined the incidence of discharge-relevant recommendations for additional imaging and the frequency of appropriate discharge documentation. The test characteristics of the 3 natural language processing algorithm iterations were compared, using blinded chart review as the criterion standard. Discharge-relevant recommendations for additional imaging were found in 4.5% (95% confidence interval [CI] 3.5% to 5.5%) of ED radiology reports, but 51% (95% CI 43% to 59%) of discharge instructions failed to note those findings. The final natural language processing algorithm had 89% (95% CI 82% to 94%) sensitivity and 98% (95% CI 97% to 98%) specificity for detecting recommendations for additional imaging. For discharge-relevant recommendations for additional imaging, sensitivity improved to 97% (95% CI 89% to 100%). Recommendations for additional imaging are common, and failure to document relevant recommendations for additional imaging in ED discharge instructions occurs frequently. The natural language processing algorithm's performance improved with each iteration and offers a promising error-prevention tool. Copyright © 2013 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Improved identification of cranial nerves using paired-agent imaging: topical staining protocol optimization through experimentation and simulation

NASA Astrophysics Data System (ADS)

Torres, Veronica C.; Wilson, Todd; Staneviciute, Austeja; Byrne, Richard W.; Tichauer, Kenneth M.

2018-03-01

Skull base tumors are particularly difficult to visualize and access for surgeons because of the crowded environment and close proximity of vital structures, such as cranial nerves. As a result, accidental nerve damage is a significant concern and the likelihood of tumor recurrence is increased because of more conservative resections that attempt to avoid injuring these structures. In this study, a paired-agent imaging method with direct administration of fluorophores is applied to enhance cranial nerve identification. Here, a control imaging agent (ICG) accounts for non-specific uptake of the nerve-targeting agent (Oxazine 4), and ratiometric data analysis is employed to approximate binding potential (BP, a surrogate of targeted biomolecule concentration). For clinical relevance, animal experiments and simulations were conducted to identify parameters for an optimized stain and rinse protocol using the developed paired-agent method. Numerical methods were used to model the diffusive and kinetic behavior of the imaging agents in tissue, and simulation results revealed that there are various combinations of stain time and rinse number that provide improved contrast of cranial nerves, as suggested by optimal measures of BP and contrast-to-noise ratio.

Diffusion tensor imaging and myelin composition analysis reveal abnormal myelination in corpus callosum of canine mucopolysaccharidosis I

PubMed Central

Provenzale, James M.; Nestrasil, Igor; Chen, Steven; Kan, Shih-hsin; Le, Steven Q.; Jens, Jacqueline K.; Snella, Elizabeth M.; Vondrak, Kristen N.; Yee, Jennifer K.; Vite, Charles H.; Elashoff, David; Duan, Lewei; Wang, Raymond Y.; Ellinwood, N. Matthew; Guzman, Miguel A.; Shapiro, Elsa G.; Dickson, Patricia I.

2015-01-01

Children with mucopolysaccharidosis I (MPS I) develop hyperintense white matter foci on T2-weighted brain magnetic resonance (MR) imaging that are associated clinically with cognitive impairment. We report here a diffusion tensor imaging (DTI) and tissue evaluation of white matter in a canine model of MPS I. We found that two DTI parameters, fractional anisotropy (a measure of white matter integrity) and radial diffusivity (which reflects degree of myelination) were abnormal in the corpus callosum of MPS I dogs compared to carrier controls. Tissue studies of the corpus callosum showed reduced expression of myelin-related genes and an abnormal composition of myelin in MPS I dogs. We treated MPS I dogs with recombinant alpha-l-iduronidase, which is the enzyme that is deficient in MPS I disease. The recombinant alpha-l-iduronidase was administered by intrathecal injection into the cisterna magna. Treated dogs showed partial correction of corpus callosum myelination. Our findings suggest that abnormal myelination occurs in the canine MPS I brain, that it may underlie clinically-relevant brain imaging findings in human MPS I patients, and that it may respond to treatment. PMID:26222335

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Multimodal nanoparticle imaging agents: design and applications

NASA Astrophysics Data System (ADS)

Burke, Benjamin P.; Cawthorne, Christopher; Archibald, Stephen J.

2017-10-01

Molecular imaging, where the location of molecules or nanoscale constructs can be tracked in the body to report on disease or biochemical processes, is rapidly expanding to include combined modality or multimodal imaging. No single imaging technique can offer the optimum combination of properties (e.g. resolution, sensitivity, cost, availability). The rapid technological advances in hardware to scan patients, and software to process and fuse images, are pushing the boundaries of novel medical imaging approaches, and hand-in-hand with this is the requirement for advanced and specific multimodal imaging agents. These agents can be detected using a selection from radioisotope, magnetic resonance and optical imaging, among others. Nanoparticles offer great scope in this area as they lend themselves, via facile modification procedures, to act as multifunctional constructs. They have relevance as therapeutics and drug delivery agents that can be tracked by molecular imaging techniques with the particular development of applications in optically guided surgery and as radiosensitizers. There has been a huge amount of research work to produce nanoconstructs for imaging, and the parameters for successful clinical translation and validation of therapeutic applications are now becoming much better understood. It is an exciting time of progress for these agents as their potential is closer to being realized with translation into the clinic. The coming 5-10 years will be critical, as we will see if the predicted improvement in clinical outcomes becomes a reality. Some of the latest advances in combination modality agents are selected and the progression pathway to clinical trials analysed. This article is part of the themed issue 'Challenges for chemistry in molecular imaging'.

Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

PubMed

Knoll, Florian; Hammernik, Kerstin; Kobler, Erich; Pock, Thomas; Recht, Michael P; Sodickson, Daniel K

2018-05-17

Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to assess the influence of image contrast, SNR, and image content on the generalization of learned image reconstruction, and to demonstrate the potential for transfer learning. Reconstructions were trained from undersampled data using data sets with varying SNR, sampling pattern, image contrast, and synthetic data generated from a public image database. The performance of the trained reconstructions was evaluated on 10 in vivo patient knee MRI acquisitions from 2 different pulse sequences that were not used during training. Transfer learning was evaluated by fine-tuning baseline trainings from synthetic data with a small subset of in vivo MR training data. Deviations in SNR between training and testing led to substantial decreases in reconstruction image quality, whereas image contrast was less relevant. Trainings from heterogeneous training data generalized well toward the test data with a range of acquisition parameters. Trainings from synthetic, non-MR image data showed residual aliasing artifacts, which could be removed by transfer learning-inspired fine-tuning. This study presents insights into the generalization ability of learned image reconstruction with respect to deviations in the acquisition settings between training and testing. It also provides an outlook for the potential of transfer learning to fine-tune trainings to a particular target application using only a small number of training cases. © 2018 International Society for Magnetic Resonance in Medicine.

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.

Medical smart textiles based on fiber optic technology: an overview.

PubMed

Massaroni, Carlo; Saccomandi, Paola; Schena, Emiliano

2015-04-13

The growing interest in the development of smart textiles for medical applications is driven by the aim to increase the mobility of patients who need a continuous monitoring of such physiological parameters. At the same time, the use of fiber optic sensors (FOSs) is gaining large acceptance as an alternative to traditional electrical and mechanical sensors for the monitoring of thermal and mechanical parameters. The potential impact of FOSs is related to their good metrological properties, their small size and their flexibility, as well as to their immunity from electromagnetic field. Their main advantage is the possibility to use textile based on fiber optic in a magnetic resonance imaging environment, where standard electronic sensors cannot be employed. This last feature makes FOSs suitable for monitoring biological parameters (e.g., respiratory and heartbeat monitoring) during magnetic resonance procedures. Research interest in combining FOSs and textiles into a single structure to develop wearable sensors is rapidly growing. In this review we provide an overview of the state-of-the-art of textiles, which use FOSs for monitoring of mechanical parameters of physiological interest. In particular we briefly describe the working principle of FOSs employed in this field and their relevant advantages and disadvantages. Also reviewed are their applications for the monitoring of mechanical parameters of physiological interest.

Medical Smart Textiles Based on Fiber Optic Technology: An Overview

PubMed Central

Massaroni, Carlo; Saccomandi, Paola; Schena, Emiliano

2015-01-01

The growing interest in the development of smart textiles for medical applications is driven by the aim to increase the mobility of patients who need a continuous monitoring of such physiological parameters. At the same time, the use of fiber optic sensors (FOSs) is gaining large acceptance as an alternative to traditional electrical and mechanical sensors for the monitoring of thermal and mechanical parameters. The potential impact of FOSs is related to their good metrological properties, their small size and their flexibility, as well as to their immunity from electromagnetic field. Their main advantage is the possibility to use textile based on fiber optic in a magnetic resonance imaging environment, where standard electronic sensors cannot be employed. This last feature makes FOSs suitable for monitoring biological parameters (e.g., respiratory and heartbeat monitoring) during magnetic resonance procedures. Research interest in combining FOSs and textiles into a single structure to develop wearable sensors is rapidly growing. In this review we provide an overview of the state-of-the-art of textiles, which use FOSs for monitoring of mechanical parameters of physiological interest. In particular we briefly describe the working principle of FOSs employed in this field and their relevant advantages and disadvantages. Also reviewed are their applications for the monitoring of mechanical parameters of physiological interest. PMID:25871010

Diagnosis of response and non-response to dry eye treatment using infrared thermography images

NASA Astrophysics Data System (ADS)

Acharya, U. Rajendra; Tan, Jen Hong; Vidya, S.; Yeo, Sharon; Too, Cheah Loon; Lim, Wei Jie Eugene; Chua, Kuang Chua; Tong, Louis

2014-11-01

The dry eye treatment outcome depends on the assessment of clinical relevance of the treatment effect. The potential approach to assess the clinical relevance of the treatment is to identify the symptoms responders and non-responders to the given treatments using the responder analysis. In our work, we have performed the responder analysis to assess the clinical relevance effect of the dry eye treatments namely, hot towel, EyeGiene®, and Blephasteam® twice daily and 12 min session of Lipiflow®. Thermography is performed at week 0 (baseline), at weeks 4 and 12 after treatment. The clinical parameters such as, change in the clinical irritations scores, tear break up time (TBUT), corneal staining and Schirmer's symptoms tests values are used to obtain the responders and non-responders groups. We have obtained the infrared thermography images of dry eye symptoms responders and non-responders to the three types of warming treatments. The energy, kurtosis, skewness, mean, standard deviation, and various entropies namely Shannon, Renyi and Kapoor are extracted from responders and non-responders thermograms. The extracted features are ranked based on t-values. These ranked features are fed to the various classifiers to get the highest performance using minimum features. We have used decision tree (DT), K nearest neighbour (KNN), Naves Bayesian (NB) and support vector machine (SVM) to classify the features into responder and non-responder classes. We have obtained an average accuracy of 99.88%, sensitivity of 99.7% and specificity of 100% using KNN classifier using ten-fold cross validation.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

PubMed

Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

PubMed Central

Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation.

PubMed

Cong, Rui; Li, Jing; Guo, Song

2017-02-01

To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P<0.05). When applying Qual1=Color pattern 1 for downgrading and Qual1=Color pattern 5 for upgrading the BI-RADS categories, we obtained the highest Az value (0.951), and achieved a significantly higher specificity (86.56%, P=0.002) than that of the US (81.18%) with the same sensitivity (94.96%). The qualitative classification proposed in this study may be representative of SWE parameters and has potential to be relevant assistance in breast mass diagnoses. Copyright © 2016. Published by Elsevier B.V.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

NASA Astrophysics Data System (ADS)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Initial testing of a 3D printed perfusion phantom using digital subtraction angiography

NASA Astrophysics Data System (ADS)

Wood, Rachel P.; Khobragade, Parag; Ying, Leslie; Snyder, Kenneth; Wack, David; Bednarek, Daniel R.; Rudin, Stephen; Ionita, Ciprian N.

2015-03-01

Perfusion imaging is the most applied modality for the assessment of acute stroke. Parameters such as Cerebral Blood Flow (CBF), Cerebral Blood volume (CBV) and Mean Transit Time (MTT) are used to distinguish the tissue infarct core and ischemic penumbra. Due to lack of standardization these parameters vary significantly between vendors and software even when provided with the same data set. There is a critical need to standardize the systems and make them more reliable. We have designed a uniform phantom to test and verify the perfusion systems. We implemented a flow loop with different flow rates (250, 300, 350 ml/min) and injected the same amount of contrast. The images of the phantom were acquired using a Digital Angiographic system. Since this phantom is uniform, projection images obtained using DSA is sufficient for initial validation. To validate the phantom we measured the contrast concentration at three regions of interest (arterial input, venous output, perfused area) and derived time density curves (TDC). We then calculated the maximum slope, area under the TDCs and flow. The maximum slope calculations were linearly increasing with increase in flow rate, the area under the curve decreases with increase in flow rate. There was 25% error between the calculated flow and measured flow. The derived TDCs were clinically relevant and the calculated flow, maximum slope and areas under the curve were sensitive to the measured flow. We have created a systematic way to calibrate existing perfusion systems and assess their reliability.

Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis[W][OPEN

PubMed Central

Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian

2014-01-01

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. PMID:25501589

Drop impact on spherical soft surfaces

NASA Astrophysics Data System (ADS)

Chen, Simeng; Bertola, Volfango

2017-08-01

The impact of water drops on spherical soft surfaces is investigated experimentally through high-speed imaging. The effect of a convex compliant surface on the dynamics of impacting drops is relevant to various applications, such as 3D ink-jet printing, where drops of fresh material impact on partially cured soft substrates with arbitrary shape. Several quantities which characterize the morphology of impacting drops are measured through image-processing, including the maximum and minimum spreading angles, length of the wetted curve, and dynamic contact angle. In particular, the dynamic contact angle is measured using a novel digital image-processing scheme based on a goniometric mask, which does not require edge fitting. It is shown that the surface with a higher curvature enhances the retraction of the spreading drop; this effect may be due to the difference of energy dissipation induced by the curvature of the surface. In addition, the impact parameters (elastic modulus, diameter ratio, and Weber number) are observed to significantly affect the dynamic contact angle during impact. A quantitative estimation of the deformation energy shows that it is significantly smaller than viscous dissipation.

Physiological investigation of automobile driver's activation index using simulated monotonous driving.

PubMed

Yamakoshi, T; Yamakoshi, K; Tanaka, S; Nogawa, M; Kusakabe, M; Kusumi, M; Tanida, K

2004-01-01

Monotonous automobile operation in our daily life may cause the lowering of what might be termed an activation state of the human body, resulting in an increased risk of an accident. We therefore propose to create a more suitable environment in-car so as to allow active operation of the vehicle, hopefully thus avoiding potentially dangerous situations during driving. In order to develop such an activation method as a final goal, we have firstly focused on the acquisition of physiological variables, including cardiovascular parameters, during presentation to the driver of a monotonous screen image, simulating autonomous travel of constant-speed on a motorway. Subsequently, we investigated the derivation of a driver's activation index. During the screen image presentation, a momentary electrical stimulation of about 1 second duration was involuntarily applied to a subject's shoulder to obtain a physiological response. We have successfully monitored various physiological variables during the image presentation, and results suggest that a peculiar pattern in the beat-by-beat change of blood pressure in response to the involuntary stimulus may be an appropriate, and feasible, index relevant to activation state.

An Exploration into Diffusion Tensor Imaging in the Bovine Ocular Lens

PubMed Central

Vaghefi, Ehsan; Donaldson, Paul J.

2013-01-01

We describe our development of the diffusion tensor imaging modality for the bovine ocular lens. Diffusion gradients were added to a spin-echo pulse sequence and the relevant parameters of the sequence were refined to achieve good diffusion weighting in the lens tissue, which demonstrated heterogeneous regions of diffusive signal attenuation. Decay curves for b-value (loosely summarizes the strength of diffusion weighting) and TE (determines the amount of magnetic resonance imaging-obtained signal) were used to estimate apparent diffusion coefficients (ADC) and T2 in different lens regions. The ADCs varied by over an order of magnitude and revealed diffusive anisotropy in the lens. Up to 30 diffusion gradient directions, and 8 signal acquisition averages, were applied to lenses in culture in order to improve maps of diffusion tensor eigenvalues, equivalent to ADC, across the lens. From these maps, fractional anisotropy maps were calculated and compared to known spatial distributions of anisotropic molecular fluxes in the lens. This comparison suggested new hypotheses and experiments to quantitatively assess models of circulation in the avascular lens. PMID:23459990

Effects of intra-operative fluoroscopic 3D-imaging on peri-operative imaging strategy in calcaneal fracture surgery.

PubMed

Beerekamp, M S H; Backes, M; Schep, N W L; Ubbink, D T; Luitse, J S; Schepers, T; Goslings, J C

2017-12-01

Previous studies demonstrated that intra-operative fluoroscopic 3D-imaging (3D-imaging) in calcaneal fracture surgery is promising to prevent revision surgery and save costs. However, these studies limited their focus to corrections performed after 3D-imaging, thereby neglecting corrections after intra-operative fluoroscopic 2D-imaging (2D-imaging). The aim of this study was to assess the effects of additional 3D-imaging on intra-operative corrections, peri-operative imaging used, and patient-relevant outcomes compared to 2D-imaging alone. In this before-after study, data of adult patients who underwent open reduction and internal fixation (ORIF) of a calcaneal fracture between 2000 and 2014 in our level-I Trauma center were collected. 3D-imaging (BV Pulsera with 3D-RX, Philips Healthcare, Best, The Netherlands) was available as of 2007 at the surgeons' discretion. Patient and fracture characteristics, peri-operative imaging, intra-operative corrections and patient-relevant outcomes were collected from the hospital databases. Patients in whom additional 3D-imaging was applied were compared to those undergoing 2D-imaging alone. A total of 231 patients were included of whom 107 (46%) were operated with the use of 3D-imaging. No significant differences were found in baseline characteristics. The median duration of surgery was significantly longer when using 3D-imaging (2:08 vs. 1:54 h; p = 0.002). Corrections after additional 3D-imaging were performed in 53% of the patients. However, significantly fewer corrections were made after 2D-imaging when 3D-imaging was available (Risk difference (RD) -15%; 95% Confidence interval (CI) -29 to -2). Peri-operative imaging, besides intra-operative 3D-imaging, and patient-relevant outcomes were similar between groups. Intra-operative 3D-imaging provides additional information resulting in additional corrections. Moreover, 3D-imaging probably changed the surgeons' attitude to rely more on 3D-imaging, hence a 15%-decrease of corrections performed after 2D-imaging when 3D imaging was available. No substantiation for cost reduction was found through reduction in peri-operative imaging or in terms of improved patient-relevant outcomes.

Quantitative Ultrasound Imaging Using Acoustic Backscatter Coefficients.

NASA Astrophysics Data System (ADS)

Boote, Evan Jeffery

Current clinical ultrasound scanners render images which have brightness levels related to the degree of backscattered energy from the tissue being imaged. These images offer the interpreter a qualitative impression of the scattering characteristics of the tissue being examined, but due to the complex factors which affect the amplitude and character of the echoed acoustic energy, it is difficult to make quantitative assessments of scattering nature of the tissue, and thus, difficult to make precise diagnosis when subtle disease effects are present. In this dissertation, a method of data reduction for determining acoustic backscatter coefficients is adapted for use in forming quantitative ultrasound images of this parameter. In these images, the brightness level of an individual pixel corresponds to the backscatter coefficient determined for the spatial position represented by that pixel. The data reduction method utilized rigorously accounts for extraneous factors which affect the scattered echo waveform and has been demonstrated to accurately determine backscatter coefficients under a wide range of conditions. The algorithms and procedures used to form backscatter coefficient images are described. These were tested using tissue-mimicking phantoms which have regions of varying scattering levels. Another phantom has a fat-mimicking layer for testing these techniques under more clinically relevant conditions. Backscatter coefficient images were also formed of in vitro human liver tissue. A clinical ultrasound scanner has been adapted for use as a backscatter coefficient imaging platform. The digital interface between the scanner and the computer used for data reduction are described. Initial tests, using phantoms are presented. A study of backscatter coefficient imaging of in vivo liver was performed using several normal, healthy human subjects.

Fluorescence Fluctuations and Equivalence Classes of Ca 2+ Imaging Experiments

PubMed Central

Piegari, Estefanía; Lopez, Lucía; Perez Ipiña, Emiliano; Ponce Dawson, Silvina

2014-01-01

release into the cytosol through inositol 1,4,5-trisphosphate receptors (IP3Rs) plays a relevant role in numerous physiological processes. IP3R-mediated signals involve -induced -release (CICR) whereby release through one open IP3R induces the opening of other channels. IP3Rs are apparently organized in clusters. The signals can remain localized (i.e., puffs) if CICR is limited to one cluster or become waves that propagate between clusters. puffs are the building blocks of waves. Thus, there is great interest in determining puff properties, especially in view of the current controversy on the spatial distribution of activatable IP3Rs. puffs have been observed in intact cells with optical techniques proving that they are intrinsically stochastic. Obtaining a correct picture of their dynamics then entails being able to detect the whole range of puff sizes. puffs are observed using visible single-wavelength dyes, slow exogenous buffers (e.g., EGTA) to disrupt inter-cluster CICR and UV-photolyzable caged IP3. Single-wavelength dyes increase their fluorescence upon calcium binding producing images that are strongly dependent on their kinetic, transport and photophysical properties. Determining the artifacts that the imaging setting introduces is particularly relevant when trying to analyze the smallest signals. In this paper we introduce a method to estimate the expected signal-to-noise ratio of imaging experiments that use single-wavelength dyes. The method is based on the Number and Brightness technique. It involves the performance of a series of experiments and their subsequent analysis in terms of a fluorescence fluctuation model with which the model parameters are quantified. Using the model, the expected signal-to-noise ratio is then computed. Equivalence classes between different experimental conditions that produce images with similar signal-to-noise ratios can then be established. The method may also be used to estimate the smallest signals that can reliably be observed with each setting. PMID:24776736

Attenuation-based automatic kilovolt (kV)-selection in computed tomography of the chest: effects on radiation exposure and image quality.

PubMed

Eller, Achim; Wuest, Wolfgang; Scharf, Michael; Brand, Michael; Achenbach, Stephan; Uder, Michael; Lell, Michael M

2013-12-01

To evaluate an automated attenuation-based kV-selection in computed tomography of the chest in respect to radiation dose and image quality, compared to a standard 120 kV protocol. 104 patients were examined using a 128-slice scanner. Fifty examinations (58 ± 15 years, study group) were performed using the automated adaption of tube potential (100-140 kV), based on the attenuation profile of the scout scan, 54 examinations (62 ± 14 years, control group) with fixed 120 kV. Estimated CT dose index (CTDI) of the software-proposed setting was compared with a 120 kV protocol. After the scan CTDI volume (CTDIvol) and dose length product (DLP) were recorded. Image quality was assessed by region of interest (ROI) measurements, subjective image quality by two observers with a 4-point scale (3--excellent, 0--not diagnostic). The algorithm selected 100 kV in 78% and 120 kV in 22%. Overall CTDIvol reduction was 26.6% (34% in 100 kV) overall DLP reduction was 22.8% (32.1% in 100 kV) (all p<0.001). Subjective image quality was excellent in both groups. The attenuation based kV-selection algorithm enables relevant dose reduction (~27%) in chest-CT while keeping image quality parameters at high levels. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Remote Sensing Image Quality Assessment Experiment with Post-Processing

NASA Astrophysics Data System (ADS)

Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.

2018-04-01

This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

NASA Astrophysics Data System (ADS)

Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

2018-02-01

This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

Infrared photothermal imaging of trace explosives on relevant substrates

NASA Astrophysics Data System (ADS)

Kendziora, Christopher A.; Furstenberg, Robert; Papantonakis, Michael; Nguyen, Viet; Borchert, James; Byers, Jeff; McGill, R. Andrew

2013-06-01

We are developing a technique for the stand-off detection of trace explosives on relevant substrate surfaces using photo-thermal infrared (IR) imaging spectroscopy (PT-IRIS). This approach leverages one or more compact IR quantum cascade lasers, tuned to strong absorption bands in the analytes and directed to illuminate an area on a surface of interest. An IR focal plane array is used to image the surface and detect small increases in thermal emission upon laser illumination. The PT-IRIS signal is processed as a hyperspectral image cube comprised of spatial, spectral and temporal dimensions as vectors within a detection algorithm. The ability to detect trace analytes on relevant substrates is critical for stand-off applications, but is complicated by the optical and thermal analyte/substrate interactions. This manuscript describes recent PT-IRIS experimental results and analysis for traces of RDX, TNT, ammonium nitrate (AN) and sucrose on relevant substrates (steel, polyethylene, glass and painted steel panels). We demonstrate that these analytes can be detected on these substrates at relevant surface mass loadings (10 μg/cm2 to 100 μg/cm2) even at the single pixel level.

Proton imaging of stochastic magnetic fields

NASA Astrophysics Data System (ADS)

Bott, A. F. A.; Graziani, C.; Tzeferacos, P.; White, T. G.; Lamb, D. Q.; Gregori, G.; Schekochihin, A. A.

2017-12-01

Recent laser-plasma experiments (Fox et al., Phys. Rev. Lett., vol. 111, 2013, 225002; Huntington et al., Nat. Phys., vol. 11(2), 2015, 173-176 Tzeferacos et al., Phys. Plasmas, vol. 24(4), 2017a, 041404; Tzeferacos et al., 2017b, arXiv:1702.03016 [physics.plasm-ph]) report the existence of dynamically significant magnetic fields, whose statistical characterisation is essential for a complete understanding of the physical processes these experiments are attempting to investigate. In this paper, we show how a proton-imaging diagnostic can be used to determine a range of relevant magnetic-field statistics, including the magnetic-energy spectrum. To achieve this goal, we explore the properties of an analytic relation between a stochastic magnetic field and the image-flux distribution created upon imaging that field. This `Kugland image-flux relation' was previously derived (Kugland et al., Rev. Sci. Instrum. vol. 83(10), 2012, 101301) under simplifying assumptions typically valid in actual proton-imaging set-ups. We conclude that, as with regular electromagnetic fields, features of the beam's final image-flux distribution often display a universal character determined by a single, field-scale dependent parameter - the contrast parameter s/{\\mathcal{M}}lB$ - which quantifies the relative size of the correlation length B$ of the stochastic field, proton displacements s$ due to magnetic deflections and the image magnification . For stochastic magnetic fields, we establish the existence of four contrast regimes, under which proton-flux images relate to their parent fields in a qualitatively distinct manner. These are linear, nonlinear injective, caustic and diffusive. The diffusive regime is newly identified and characterised. The nonlinear injective regime is distinguished from the caustic regime in manifesting nonlinear behaviour, but as in the linear regime, the path-integrated magnetic field experienced by the beam can be extracted uniquely. Thus, in the linear and nonlinear injective regimes we show that the magnetic-energy spectrum can be obtained under a further statistical assumption of isotropy. This is not the case in the caustic or diffusive regimes. We discuss complications to the contrast-regime characterisation arising for inhomogeneous, multi-scale stochastic fields, which can encompass many contrast regimes, as well as limitations currently placed by experimental capabilities on one's ability to extract magnetic-field statistics. The results presented in this paper are of consequence in providing a comprehensive description of proton images of stochastic magnetic fields, with applications for improved analysis of proton-flux images.

Dynamic "inline" images: context-sensitive retrieval and integration of images into Web documents.

PubMed

Kahn, Charles E

2008-09-01

Integrating relevant images into web-based information resources adds value for research and education. This work sought to evaluate the feasibility of using "Web 2.0" technologies to dynamically retrieve and integrate pertinent images into a radiology web site. An online radiology reference of 1,178 textual web documents was selected as the set of target documents. The ARRS GoldMiner image search engine, which incorporated 176,386 images from 228 peer-reviewed journals, retrieved images on demand and integrated them into the documents. At least one image was retrieved in real-time for display as an "inline" image gallery for 87% of the web documents. Each thumbnail image was linked to the full-size image at its original web site. Review of 20 randomly selected Collaborative Hypertext of Radiology documents found that 69 of 72 displayed images (96%) were relevant to the target document. Users could click on the "More" link to search the image collection more comprehensively and, from there, link to the full text of the article. A gallery of relevant radiology images can be inserted easily into web pages on any web server. Indexing by concepts and keywords allows context-aware image retrieval, and searching by document title and subject metadata yields excellent results. These techniques allow web developers to incorporate easily a context-sensitive image gallery into their documents.

Quantitative Assessment of Optical Coherence Tomography Imaging Performance with Phantom-Based Test Methods And Computational Modeling

NASA Astrophysics Data System (ADS)

Agrawal, Anant

Optical coherence tomography (OCT) is a powerful medical imaging modality that uniquely produces high-resolution cross-sectional images of tissue using low energy light. Its clinical applications and technological capabilities have grown substantially since its invention about twenty years ago, but efforts have been limited to develop tools to assess performance of OCT devices with respect to the quality and content of acquired images. Such tools are important to ensure information derived from OCT signals and images is accurate and consistent, in order to support further technology development, promote standardization, and benefit public health. The research in this dissertation investigates new physical and computational models which can provide unique insights into specific performance characteristics of OCT devices. Physical models, known as phantoms, are fabricated and evaluated in the interest of establishing standardized test methods to measure several important quantities relevant to image quality. (1) Spatial resolution is measured with a nanoparticle-embedded phantom and model eye which together yield the point spread function under conditions where OCT is commonly used. (2) A multi-layered phantom is constructed to measure the contrast transfer function along the axis of light propagation, relevant for cross-sectional imaging capabilities. (3) Existing and new methods to determine device sensitivity are examined and compared, to better understand the detection limits of OCT. A novel computational model based on the finite-difference time-domain (FDTD) method, which simulates the physics of light behavior at the sub-microscopic level within complex, heterogeneous media, is developed to probe device and tissue characteristics influencing the information content of an OCT image. This model is first tested in simple geometric configurations to understand its accuracy and limitations, then a highly realistic representation of a biological cell, the retinal cone photoreceptor, is created and its resulting OCT signals studied. The phantoms and their associated test methods have successfully yielded novel types of data on the specific performance parameters of interest, which can feed standardization efforts within the OCT community. The level of signal detail provided by the computational model is unprecedented and gives significant insights into the effects of subcellular structures on OCT signals. Together, the outputs of this research effort serve as new tools in the toolkit to examine the intricate details of how and how well OCT devices produce information-rich images of biological tissue.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

PubMed

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

Real-time gamma imaging of technetium transport through natural and engineered porous materials for radioactive waste disposal.

PubMed

Corkhill, Claire L; Bridge, Jonathan W; Chen, Xiaohui C; Hillel, Phil; Thornton, Steve F; Romero-Gonzalez, Maria E; Banwart, Steven A; Hyatt, Neil C

2013-12-03

We present a novel methodology for determining the transport of technetium-99m, a γ-emitting metastable isomer of (99)Tc, through quartz sand and porous media relevant to the disposal of nuclear waste in a geological disposal facility (GDF). Quartz sand is utilized as a model medium, and the applicability of the methodology to determine radionuclide transport in engineered backfill cement is explored using the UK GDF candidate backfill cement, Nirex Reference Vault Backfill (NRVB), in a model system. Two-dimensional distributions in (99m)Tc activity were collected at millimeter-resolution using decay-corrected gamma camera images. Pulse-inputs of ~20 MBq (99m)Tc were introduced into short (<10 cm) water-saturated columns at a constant flow of 0.33 mL min(-1). Changes in calibrated mass distribution of (99m)Tc at 30 s intervals, over a period of several hours, were quantified by spatial moments analysis. Transport parameters were fitted to the experimental data using a one-dimensional convection-dispersion equation, yielding transport properties for this radionuclide in a model GDF environment. These data demonstrate that (99)Tc in the pertechnetate form (Tc(VII)O4(-)) does not sorb to cement backfill during transport under model conditions, resulting in closely conservative transport behavior. This methodology represents a quantitative development of radiotracer imaging and offers the opportunity to conveniently and rapidly characterize transport of gamma-emitting isotopes in opaque media, relevant to the geological disposal of nuclear waste and potentially to a wide variety of other subsurface environments.

Real-Time Gamma Imaging of Technetium Transport through Natural and Engineered Porous Materials for Radioactive Waste Disposal

PubMed Central

2013-01-01

We present a novel methodology for determining the transport of technetium-99m, a γ-emitting metastable isomer of 99Tc, through quartz sand and porous media relevant to the disposal of nuclear waste in a geological disposal facility (GDF). Quartz sand is utilized as a model medium, and the applicability of the methodology to determine radionuclide transport in engineered backfill cement is explored using the UK GDF candidate backfill cement, Nirex Reference Vault Backfill (NRVB), in a model system. Two-dimensional distributions in 99mTc activity were collected at millimeter-resolution using decay-corrected gamma camera images. Pulse-inputs of ∼20 MBq 99mTc were introduced into short (<10 cm) water-saturated columns at a constant flow of 0.33 mL min–1. Changes in calibrated mass distribution of 99mTc at 30 s intervals, over a period of several hours, were quantified by spatial moments analysis. Transport parameters were fitted to the experimental data using a one-dimensional convection–dispersion equation, yielding transport properties for this radionuclide in a model GDF environment. These data demonstrate that 99Tc in the pertechnetate form (Tc(VII)O4–) does not sorb to cement backfill during transport under model conditions, resulting in closely conservative transport behavior. This methodology represents a quantitative development of radiotracer imaging and offers the opportunity to conveniently and rapidly characterize transport of gamma-emitting isotopes in opaque media, relevant to the geological disposal of nuclear waste and potentially to a wide variety of other subsurface environments. PMID:24147650

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation

PubMed Central

Wilke, Marko; Altaye, Mekibib; Holland, Scott K.

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating “unusual” populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php. PMID:28275348

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation.

PubMed

Wilke, Marko; Altaye, Mekibib; Holland, Scott K

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php.

Reference Values for Cardiac and Aortic Magnetic Resonance Imaging in Healthy, Young Caucasian Adults.

PubMed

Eikendal, Anouk L M; Bots, Michiel L; Haaring, Cees; Saam, Tobias; van der Geest, Rob J; Westenberg, Jos J M; den Ruijter, Hester M; Hoefer, Imo E; Leiner, Tim

2016-01-01

Reference values for morphological and functional parameters of the cardiovascular system in early life are relevant since they may help to identify young adults who fall outside the physiological range of arterial and cardiac ageing. This study provides age and sex specific reference values for aortic wall characteristics, cardiac function parameters and aortic pulse wave velocity (PWV) in a population-based sample of healthy, young adults using magnetic resonance (MR) imaging. In 131 randomly selected healthy, young adults aged between 25 and 35 years (mean age 31.8 years, 63 men) of the general-population based Atherosclerosis-Monitoring-and-Biomarker-measurements-In-The-YOuNg (AMBITYON) study, descending thoracic aortic dimensions and wall thickness, thoracic aortic PWV and cardiac function parameters were measured using a 3.0T MR-system. Age and sex specific reference values were generated using dedicated software. Differences in reference values between two age groups (25-30 and 30-35 years) and both sexes were tested. Aortic diameters and areas were higher in the older age group (all p<0.007). Moreover, aortic dimensions, left ventricular mass, left and right ventricular volumes and cardiac output were lower in women than in men (all p<0.001). For mean and maximum aortic wall thickness, left and right ejection fraction and aortic PWV we did not observe a significant age or sex effect. This study provides age and sex specific reference values for cardiovascular MR parameters in healthy, young Caucasian adults. These may aid in MR guided pre-clinical identification of young adults who fall outside the physiological range of arterial and cardiac ageing.

Characterization of the passive and active material parameters of the pubovisceralis muscle using an inverse numerical method.

PubMed

Silva, M E T; Parente, M P L; Brandão, S; Mascarenhas, T; Natal Jorge, R M

2018-04-11

The mechanical characteristics of the female pelvic floor are relevant to understand pelvic floor dysfunctions (PFD), and how they are related with changes in their biomechanical behavior. Urinary incontinence (UI) and pelvic organ prolapse (POP) are the most common pathologies, which can be associated with changes in the mechanical properties of the supportive structures in the female pelvic cavity. PFD have been studied through different methods, from experimental tensile tests using tissues from fresh female cadavers or tissues collected at the time of a transvaginal hysterectomy procedure, or by applying imaging techniques. In this work, an inverse finite element analysis (FEA) was applied to understand the passive and active behavior of the pubovisceralis muscle (PVM) during Valsalva maneuver and muscle active contraction, respectively. Individual numerical models of women without pathology, with stress UI (SUI) and POP were built based on magnetic resonance images, including the PVM and surrounding structures. The passive and active material parameters obtained for a transversely isotropic hyperelastic constitutive model were estimated for the three groups. The values for the material constants were significantly higher for the women with POP when compared with the other two groups. The PVM of women with POP showed the highest stiffness. Additionally, the influence of these parameters was analyzed by evaluating their stress-strain, and force-displacements responses. The force produced by the PVM in women with POP was 47% and 82% higher when compared to women without pathology and with SUI, respectively. The inverse FEA allowed estimating the material parameters of the PVM using input information acquired non-invasively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI

NASA Astrophysics Data System (ADS)

Chirra, Prathyush; Leo, Patrick; Yim, Michael; Bloch, B. Nicolas; Rastinehad, Ardeshir R.; Purysko, Andrei; Rosen, Mark; Madabhushi, Anant; Viswanath, Satish

2018-02-01

The recent advent of radiomics has enabled the development of prognostic and predictive tools which use routine imaging, but a key question that still remains is how reproducible these features may be across multiple sites and scanners. This is especially relevant in the context of MRI data, where signal intensity values lack tissue specific, quantitative meaning, as well as being dependent on acquisition parameters (magnetic field strength, image resolution, type of receiver coil). In this paper we present the first empirical study of the reproducibility of 5 different radiomic feature families in a multi-site setting; specifically, for characterizing prostate MRI appearance. Our cohort comprised 147 patient T2w MRI datasets from 4 different sites, all of which were first pre-processed to correct acquisition-related for artifacts such as bias field, differing voxel resolutions, as well as intensity drift (non-standardness). 406 3D voxel wise radiomic features were extracted and evaluated in a cross-site setting to determine how reproducible they were within a relatively homogeneous non-tumor tissue region; using 2 different measures of reproducibility: Multivariate Coefficient of Variation and Instability Score. Our results demonstrated that Haralick features were most reproducible between all 4 sites. By comparison, Laws features were among the least reproducible between sites, as well as performing highly variably across their entire parameter space. Similarly, the Gabor feature family demonstrated good cross-site reproducibility, but for certain parameter combinations alone. These trends indicate that despite extensive pre-processing, only a subset of radiomic features and associated parameters may be reproducible enough for use within radiomics-based machine learning classifier schemes.

Noise in NC-AFM measurements with significant tip–sample interaction

PubMed Central

Lübbe, Jannis; Temmen, Matthias

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip–sample interactions. The total noise power spectral density D Δ f(f m) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip–sample interaction, by the coupling between the amplitude and tip–sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f(f m) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip–sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops. PMID:28144538

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective.

PubMed

Wong, Kee H; Panek, Rafal; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L

2017-03-01

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

Reliable vision-guided grasping

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1992-01-01

Automated assembly of truss structures in space requires vision-guided servoing for grasping a strut when its position and orientation are uncertain. This paper presents a methodology for efficient and robust vision-guided robot grasping alignment. The vision-guided grasping problem is related to vision-guided 'docking' problems. It differs from other hand-in-eye visual servoing problems, such as tracking, in that the distance from the target is a relevant servo parameter. The methodology described in this paper is hierarchy of levels in which the vision/robot interface is decreasingly 'intelligent,' and increasingly fast. Speed is achieved primarily by information reduction. This reduction exploits the use of region-of-interest windows in the image plane and feature motion prediction. These reductions invariably require stringent assumptions about the image. Therefore, at a higher level, these assumptions are verified using slower, more reliable methods. This hierarchy provides for robust error recovery in that when a lower-level routine fails, the next-higher routine will be called and so on. A working system is described which visually aligns a robot to grasp a cylindrical strut. The system uses a single camera mounted on the end effector of a robot and requires only crude calibration parameters. The grasping procedure is fast and reliable, with a multi-level error recovery system.

Noise in NC-AFM measurements with significant tip-sample interaction.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Reichling, Michael

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density D Δ f ( f m ) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f ( f m ) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective

PubMed Central

Panek, Rafal; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L

2017-01-01

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy. PMID:28256151

Blood flow quantification using 1D CFD parameter identification

NASA Astrophysics Data System (ADS)

Brosig, Richard; Kowarschik, Markus; Maday, Peter; Katouzian, Amin; Demirci, Stefanie; Navab, Nassir

2014-03-01

Patient-specific measurements of cerebral blood flow provide valuable diagnostic information concerning cerebrovascular diseases rather than visually driven qualitative evaluation. In this paper, we present a quantitative method to estimate blood flow parameters with high temporal resolution from digital subtraction angiography (DSA) image sequences. Using a 3D DSA dataset and a 2D+t DSA sequence, the proposed algorithm employs a 1D Computational Fluid Dynamics (CFD) model for estimation of time-dependent flow values along a cerebral vessel, combined with an additional Advection Diffusion Equation (ADE) for contrast agent propagation. The CFD system, followed by the ADE, is solved with a finite volume approximation, which ensures the conservation of mass. Instead of defining a new imaging protocol to obtain relevant data, our cost function optimizes the bolus arrival time (BAT) of the contrast agent in 2D+t DSA sequences. The visual determination of BAT is common clinical practice and can be easily derived from and be compared to values, generated by a 1D-CFD simulation. Using this strategy, we ensure that our proposed method fits best to clinical practice and does not require any changes to the medical work flow. Synthetic experiments show that the recovered flow estimates match the ground truth values with less than 12% error in the mean flow rates.

Understanding Magnetic Resonance Imaging of Knee Cartilage Repair: A Focus on Clinical Relevance.

PubMed

Hayashi, Daichi; Li, Xinning; Murakami, Akira M; Roemer, Frank W; Trattnig, Siegfried; Guermazi, Ali

2017-06-01

The aims of this review article are (a) to describe the principles of morphologic and compositional magnetic resonance imaging (MRI) techniques relevant for the imaging of knee cartilage repair surgery and their application to longitudinal studies and (b) to illustrate the clinical relevance of pre- and postsurgical MRI with correlation to intraoperative images. First, MRI sequences that can be applied for imaging of cartilage repair tissue in the knee are described, focusing on comparison of 2D and 3D fast spin echo and gradient recalled echo sequences. Imaging features of cartilage repair tissue are then discussed, including conventional (morphologic) MRI and compositional MRI techniques. More specifically, imaging techniques for specific cartilage repair surgery techniques as described above, as well as MRI-based semiquantitative scoring systems for the knee cartilage repair tissue-MR Observation of Cartilage Repair Tissue and Cartilage Repair OA Knee Score-are explained. Then, currently available surgical techniques are reviewed, including marrow stimulation, osteochondral autograft, osteochondral allograft, particulate cartilage allograft, autologous chondrocyte implantation, and others. Finally, ongoing research efforts and future direction of cartilage repair tissue imaging are discussed.

Weak Lensing from Space I: Instrumentation and Survey Strategy

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

Rhodes, Jason; Refregier, Alexandre; Massey, Richard

A wide field space-based imaging telescope is necessary to fully exploit the technique of observing dark matter via weak gravitational lensing. This first paper in a three part series outlines the survey strategies and relevant instrumental parameters for such a mission. As a concrete example of hardware design, we consider the proposed Supernova/Acceleration Probe (SNAP). Using SNAP engineering models, we quantify the major contributions to this telescope's Point Spread Function (PSF). These PSF contributions are relevant to any similar wide field space telescope. We further show that the PSF of SNAP or a similar telescope will be smaller than currentmore » ground-based PSFs, and more isotropic and stable over time than the PSF of the Hubble Space Telescope. We outline survey strategies for two different regimes - a ''wide'' 300 square degree survey and a ''deep'' 15 square degree survey that will accomplish various weak lensing goals including statistical studies and dark matter mapping.« less

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Content dependent selection of image enhancement parameters for mobile displays

NASA Astrophysics Data System (ADS)

Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo

2011-01-01

Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

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

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch; Zaidi, Habib; Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailedmore » investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.« less

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Testing the quality of images for permanent magnet desktop MRI systems using specially designed phantoms.

PubMed

Qiu, Jianfeng; Wang, Guozhu; Min, Jiao; Wang, Xiaoyan; Wang, Pengcheng

2013-12-21

Our aim was to measure the performance of desktop magnetic resonance imaging (MRI) systems using specially designed phantoms, by testing imaging parameters and analysing the imaging quality. We designed multifunction phantoms with diameters of 18 and 60 mm for desktop MRI scanners in accordance with the American Association of Physicists in Medicine (AAPM) report no. 28. We scanned the phantoms with three permanent magnet 0.5 T desktop MRI systems, measured the MRI image parameters, and analysed imaging quality by comparing the data with the AAPM criteria and Chinese national standards. Image parameters included: resonance frequency, high contrast spatial resolution, low contrast object detectability, slice thickness, geometrical distortion, signal-to-noise ratio (SNR), and image uniformity. The image parameters of three desktop MRI machines could be measured using our specially designed phantoms, and most parameters were in line with MRI quality control criterion, including: resonance frequency, high contrast spatial resolution, low contrast object detectability, slice thickness, geometrical distortion, image uniformity and slice position accuracy. However, SNR was significantly lower than in some references. The imaging test and quality control are necessary for desktop MRI systems, and should be performed with the applicable phantom and corresponding standards.

Learning the manifold of quality ultrasound acquisition.

PubMed

El-Zehiry, Noha; Yan, Michelle; Good, Sara; Fang, Tong; Zhou, S Kevin; Grady, Leo

2013-01-01

Ultrasound acquisition is a challenging task that requires simultaneous adjustment of several acquisition parameters (the depth, the focus, the frequency and its operation mode). If the acquisition parameters are not properly chosen, the resulting image will have a poor quality and will degrade the patient diagnosis and treatment workflow. Several hardware-based systems for autotuning the acquisition parameters have been previously proposed, but these solutions were largely abandoned because they failed to properly account for tissue inhomogeneity and other patient-specific characteristics. Consequently, in routine practice the clinician either uses population-based parameter presets or manually adjusts the acquisition parameters for each patient during the scan. In this paper, we revisit the problem of autotuning the acquisition parameters by taking a completely novel approach and producing a solution based on image analytics. Our solution is inspired by the autofocus capability of conventional digital cameras, but is significantly more challenging because the number of acquisition parameters is large and the determination of "good quality" images is more difficult to assess. Surprisingly, we show that the set of acquisition parameters which produce images that are favored by clinicians comprise a 1D manifold, allowing for a real-time optimization to maximize image quality. We demonstrate our method for acquisition parameter autotuning on several live patients, showing that our system can start with a poor initial set of parameters and automatically optimize the parameters to produce high quality images.

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.

Parameter estimation of qubit states with unknown phase parameter

NASA Astrophysics Data System (ADS)

Suzuki, Jun

2015-02-01

We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér-Rao (CR) bound and Hayashi-Gill-Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.

Richardson-Lucy deconvolution as a general tool for combining images with complementary strengths.

PubMed

Ingaramo, Maria; York, Andrew G; Hoogendoorn, Eelco; Postma, Marten; Shroff, Hari; Patterson, George H

2014-03-17

We use Richardson-Lucy (RL) deconvolution to combine multiple images of a simulated object into a single image in the context of modern fluorescence microscopy techniques. RL deconvolution can merge images with very different point-spread functions, such as in multiview light-sheet microscopes,1, 2 while preserving the best resolution information present in each image. We show that RL deconvolution is also easily applied to merge high-resolution, high-noise images with low-resolution, low-noise images, relevant when complementing conventional microscopy with localization microscopy. We also use RL deconvolution to merge images produced by different simulated illumination patterns, relevant to structured illumination microscopy (SIM)3, 4 and image scanning microscopy (ISM). The quality of our ISM reconstructions is at least as good as reconstructions using standard inversion algorithms for ISM data, but our method follows a simpler recipe that requires no mathematical insight. Finally, we apply RL deconvolution to merge a series of ten images with varying signal and resolution levels. This combination is relevant to gated stimulated-emission depletion (STED) microscopy, and shows that merges of high-quality images are possible even in cases for which a non-iterative inversion algorithm is unknown. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Beyond arousal and valence: The importance of the biological versus social relevance of emotional stimuli

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention; memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images’ subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in visual cortex and greater functional connectivity between amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

Magnetic resonance-transcranial ultrasound fusion imaging: A novel tool for brain electrode location.

PubMed

Walter, Uwe; Müller, Jan-Uwe; Rösche, Johannes; Kirsch, Michael; Grossmann, Annette; Benecke, Reiner; Wittstock, Matthias; Wolters, Alexander

2016-03-01

A combination of preoperative magnetic resonance imaging (MRI) with real-time transcranial ultrasound, known as fusion imaging, may improve postoperative control of deep brain stimulation (DBS) electrode location. Fusion imaging, however, employs a weak magnetic field for tracking the position of the ultrasound transducer and the patient's head. Here we assessed its feasibility, safety, and clinical relevance in patients with DBS. Eighteen imaging sessions were conducted in 15 patients (7 women; aged 52.4 ± 14.4 y) with DBS of subthalamic nucleus (n = 6), globus pallidus interna (n = 5), ventro-intermediate (n = 3), or anterior (n = 1) thalamic nucleus and clinically suspected lead displacement. Minimum distance between DBS generator and magnetic field transmitter was kept at 65 cm. The pre-implantation MRI dataset was loaded into the ultrasound system for the fusion imaging examination. The DBS lead position was rated using validated criteria. Generator DBS parameters and neurological state of patients were monitored. Magnetic resonance-ultrasound fusion imaging and volume navigation were feasible in all cases and provided with real-time imaging capabilities of DBS lead and its location within the superimposed magnetic resonance images. Of 35 assessed lead locations, 30 were rated optimal, three suboptimal, and two displaced. In two cases, electrodes were re-implanted after confirming their inappropriate location on computed tomography (CT) scan. No influence of fusion imaging on clinical state of patients, or on DBS implantable pulse generator function, was found. Magnetic resonance-ultrasound real-time fusion imaging of DBS electrodes is safe with distinct precautions and improves assessment of electrode location. It may lower the need for repeated CT or MRI scans in DBS patients. © 2015 International Parkinson and Movement Disorder Society.

Arrhenius parameter determination as a function of heating method and cellular microenvironment based on spatial cell viability analysis.

PubMed

Whitney, Jon; Carswell, William; Rylander, Nichole

2013-06-01

Predictions of injury in response to photothermal therapy in vivo are frequently made using Arrhenius parameters obtained from cell monolayers exposed to laser or water bath heating. However, the impact of different heating methods and cellular microenvironments on Arrhenius predictions has not been thoroughly investigated. This study determined the influence of heating method (water bath and laser irradiation) and cellular microenvironment (cell monolayers and tissue phantoms) on Arrhenius parameters and spatial viability. MDA-MB-231 cells seeded in monolayers and sodium alginate phantoms were heated with a water bath for 3-20 min at 46, 50, and 54 °C or laser irradiated (wavelength of 1064 nm and fluences of 40 W/cm(2) or 3.8 W/cm(2) for 0-4 min) in combination with photoabsorptive carbon nanohorns. Spatial viability was measured using digital image analysis of cells stained with calcein AM and propidium iodide and used to determine Arrhenius parameters. The influence of microenvironment and heating method on Arrhenius parameters and capability of parameters derived from more simplistic experimental conditions (e.g. water bath heating of monolayers) to predict more physiologically relevant systems (e.g. laser heating of phantoms) were assessed. Arrhenius predictions of the treated area (<1% viable) under-predicted the measured areas in photothermally treated phantoms by 23 mm(2) using water bath treated cell monolayer parameters, 26 mm(2) using water bath treated phantom parameters, 27 mm(2) using photothermally treated monolayer parameters, and 0.7 mm(2) using photothermally treated phantom parameters. Heating method and cellular microenvironment influenced Arrhenius parameters, with heating method having the greater impact.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Moralization Through Moral Shock: Exploring Emotional Antecedents to Moral Conviction.

PubMed

Wisneski, Daniel C; Skitka, Linda J

2017-02-01

The current research tested whether exposure to disgusting images increases moral conviction and whether this happens in the presence of incidental disgust cues versus disgust cues relevant to the target of moralization. Across two studies, we exposed participants to one of the four sets of disgusting versus control images to test the moralization of abortion attitudes: pictures of aborted fetuses, animal abuse, non-harm related disgusting images, harm related disgusting images, or neutral pictures, at either sub- or supraliminal levels of awareness. Moral conviction about abortion increased (compared with control) only for participants exposed to abortion-related images at speeds slow enough to allow conscious awareness. Study 2 replicated this finding, and found that the relationship between attitudinally relevant disgust and moral conviction was mediated by disgust, and not anger or harm appraisals. Findings are discussed in terms of their relevance for intuitionist theories of morality and moral theories that emphasize harm.

Comprehensive analysis of line-edge and line-width roughness for EUV lithography

NASA Astrophysics Data System (ADS)

Bonam, Ravi; Liu, Chi-Chun; Breton, Mary; Sieg, Stuart; Seshadri, Indira; Saulnier, Nicole; Shearer, Jeffrey; Muthinti, Raja; Patlolla, Raghuveer; Huang, Huai

2017-03-01

Pattern transfer fidelity is always a major challenge for any lithography process and needs continuous improvement. Lithographic processes in semiconductor industry are primarily driven by optical imaging on photosensitive polymeric material (resists). Quality of pattern transfer can be assessed by quantifying multiple parameters such as, feature size uniformity (CD), placement, roughness, sidewall angles etc. Roughness in features primarily corresponds to variation of line edge or line width and has gained considerable significance, particularly due to shrinking feature sizes and variations of features in the same order. This has caused downstream processes (Etch (RIE), Chemical Mechanical Polish (CMP) etc.) to reconsider respective tolerance levels. A very important aspect of this work is relevance of roughness metrology from pattern formation at resist to subsequent processes, particularly electrical validity. A major drawback of current LER/LWR metric (sigma) is its lack of relevance across multiple downstream processes which effects material selection at various unit processes. In this work we present a comprehensive assessment of Line Edge and Line Width Roughness at multiple lithographic transfer processes. To simulate effect of roughness a pattern was designed with periodic jogs on the edges of lines with varying amplitudes and frequencies. There are numerous methodologies proposed to analyze roughness and in this work we apply them to programmed roughness structures to assess each technique's sensitivity. This work also aims to identify a relevant methodology to quantify roughness with relevance across downstream processes.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

PubMed

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling the low-light response of photomultiplier tubes

NASA Astrophysics Data System (ADS)

Maxwell, Patrick; Niculescu, Ioana

2017-09-01

A number of crucial experiments exploring the intricate tomography of protons and neutrons will be carried out in Hall A at Jefferson Lab using the SuperBigBite Spectrometer (SBS), a large acceptance magnetic spectrometer sporting 0.5% momentum and 0.5 mr angular resolution. As part of the standard SBS detector package the Gas Ring Imaging Cherenkov (GRINCH) detector will help identify particles produced in the experiments. To determine which photomultiplier (PMT) tubes would be used in GRINCH, more than 900 29 mm 9125B PMTs were tested. Two models, were used to fit test data. For the parameters relevant to this study, results from both models were found to be equivalent, and will be discussed here.

Stimulus factors in motion perception and spatial orientation

NASA Technical Reports Server (NTRS)

Post, R. B.; Johnson, C. A.

1984-01-01

The Malcolm horizon utilizes a large projected light stimulus Peripheral Vision Horizon Device (PVHD) as an attitude indicator in order to achieve a more compelling sense of roll than is obtained with smaller devices. The basic principle is that the larger stimulus is more similar to visibility of a real horizon during roll, and does not require fixation and attention to the degree that smaller displays do. Successful implementation of such a device requires adjustment of the parameters of the visual stimulus so that its effects on motion perception and spatial orientation are optimized. With this purpose in mind, the effects of relevant image variables on the perception of object motion, self motion and spatial orientation are reviewed.

Experimental study of subcritical laboratory magnetized collisionless shocks using a laser-driven magnetic piston

NASA Astrophysics Data System (ADS)

Schaeffer, D. B.; Everson, E. T.; Bondarenko, A. S.; Clark, S. E.; Constantin, C. G.; Winske, D.; Gekelman, W.; Niemann, C.

2015-11-01

Recent experiments at the University of California, Los Angeles have successfully generated subcritical magnetized collisionless shocks, allowing new laboratory studies of shock formation relevant to space shocks. The characteristics of these shocks are compared with new data in which no shock or a pre-shock formed. The results are consistent with theory and 2D hybrid simulations and indicate that the observed shock or shock-like structures can be organized into distinct regimes by coupling strength. With additional experiments on the early time parameters of the laser plasma utilizing Thomson scattering, spectroscopy, and fast-gate filtered imaging, these regimes are found to be in good agreement with theoretical shock formation criteria.

A small animal time-resolved optical tomography platform using wide-field excitation

NASA Astrophysics Data System (ADS)

Venugopal, Vivek

Small animal imaging plays a critical role in present day biomedical research by filling an important gap in the translation of research from the bench to the bedside. Optical techniques constitute an emerging imaging modality which have tremendous potential in preclinical applications. Optical imaging methods are capable of non-invasive assessment of the functional and molecular characteristics of biological tissue. The three-dimensional optical imaging technique, referred to as diffuse optical tomography, provides an approach for the whole-body imaging of small animal models and can provide volumetric maps of tissue functional parameters (e.g. blood volume, oxygen saturation etc.) and/or provide 3D localization and quantification of fluorescence-based molecular markers in vivo. However, the complex mathematical reconstruction problem associated with optical tomography and the cumbersome instrumental designs limits its adoption as a high-throughput quantitative whole-body imaging modality in current biomedical research. The development of new optical imaging paradigms is thus necessary for a wide-acceptance of this new technology. In this thesis, the design, development, characterization and optimization of a small animal optical tomography system is discussed. Specifically, the platform combines a highly sensitive time-resolved imaging paradigm with multi-spectral excitation capability and CCD-based detection to provide a system capable of generating spatially, spectrally and temporally dense measurement datasets. The acquisition of such data sets however can take long and translate to often unrealistic acquisition times when using the classical point source based excitation scheme. The novel approach in the design of this platform is the adoption of a wide-field excitation scheme which employs extended excitation sources and in the process allows an estimated ten-fold reduction in the acquisition time. The work described herein details the design of the imaging platform employing DLP-based excitation and time-gated intensified CCD detection and the optimal system operation parameters are determined. The feasibility this imaging approach and accuracy of the system in reconstructing functional parameters and fluorescence markers based on lifetime contrast is established through phantom studies. As a part of the system characterization, the effect of noise in time-resolved optical tomography is investigated and propagation of system noise in optical reconstructions is established. Furthermore, data processing and measurement calibration techniques aimed at reducing the effect of noise in reconstructions are defined. The optimization of excitation pattern selection is established through a novel measurement-guided iterative pattern correction scheme. This technique referred to as Adaptive Full-Field Optical Tomography was shown to improve reconstruction performances in murine models by reducing the dynamic range in photon flux measurements on the surface. Lastly, the application of the unique attributes of this platform to a biologically relevant imaging application, referred to as Forster Resonance Energy Transfer is described. The tomographic imaging of FRET interaction in vivo on a whole-body scale is achieved using the wide-field imaging approach based on lifetime contrast. This technique represents the first demonstration of tomographic FRET imaging in small animals and has significant potential in the development of optical imaging techniques in varied applications ranging from drug discovery to in vivo study of protein-protein interaction.

Quantitative histogram analysis of images

NASA Astrophysics Data System (ADS)

Holub, Oliver; Ferreira, Sérgio T.

2006-11-01

A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

Nondestructive prediction of pork freshness parameters using multispectral scattering images

NASA Astrophysics Data System (ADS)

Tang, Xiuying; Li, Cuiling; Peng, Yankun; Chao, Kuanglin; Wang, Mingwu

2012-05-01

Optical technology is an important and immerging technology for non-destructive and rapid detection of pork freshness. This paper studied on the possibility of using multispectral imaging technique and scattering characteristics to predict the freshness parameters of pork meat. The pork freshness parameters selected for prediction included total volatile basic nitrogen (TVB-N), color parameters (L *, a *, b *), and pH value. Multispectral scattering images were obtained from pork sample surface by a multispectral imaging system developed by ourselves; they were acquired at the selected narrow wavebands whose center wavelengths were 517,550, 560, 580, 600, 760, 810 and 910nm. In order to extract scattering characteristics from multispectral images at multiple wavelengths, a Lorentzian distribution (LD) function with four parameters (a: scattering asymptotic value; b: scattering peak; c: scattering width; d: scattering slope) was used to fit the scattering curves at the selected wavelengths. The results show that the multispectral imaging technique combined with scattering characteristics is promising for predicting the freshness parameters of pork meat.

SU-G-TeP2-11: Initial Evaluation of a Novel Split-Filter Dual-Energy CT for Use in Radiation Oncology

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

Miller, J; Huang, J; Szczykutowicz, T

2016-06-15

Purpose: To perform an initial evaluation of a novel split-filter dual-energy CT (DECT) system with the goal of understanding the clinical utility and limitations of the system for radiation therapy. Methods: Several phantoms were imaged using the split-filter DECT technique on the Siemens Edge CT scanner using a range of clinically-relevant doses. The optimum-contrast reconstruction, the mixed reconstruction, and the monoenergetic reconstructions (ranging from 40 keV to 190 keV) were evaluated. Each image was analyzed for CT number accuracy, uniformity, noise, low-contrast visibility (LCV), spatial resolution and geometric distortion. For comparison purposes, all parameters were evaluated on 120 kVp single-energymore » CT (SECT) scans used for treatment planning, as well as, a sequential-scan DECT technique for corresponding doses. Results: For all DECT reconstructions no observable geometric distortion was found. Both the optimal-contrast and mixed images demonstrated slight improvements in LCV and noise when compared to the SECT, and slight reductions in CT number accuracy and spatial resolution. The CT numbers trended as expected for the monoenergetic reconstructions, with CT number accuracy within 50 HU for materials of density <2 g/cm3. Spatial resolution increased with energy, and for monoenergetic reconstructions >70 keV the spatial resolution exceeded that of the SECT. The noise in the monoenergetic reconstructions increased with decreasing energy. Thus, the image uniformity, signal-to-noise ratio and LCV were diminished at lower energies (70 keV). Applying iterative reconstruction techniques to the low-energy images reduced noise and improved LCV. The signal-to-noise ratio was stable for energies >100 keV. Conclusion: The initial commissioning of the novel split-filter DECT technology demonstrated favorable results for clinical implementation. The mixed reconstruction showed potential as a replacement for the treatment planning SECT. The image parameters for the monoenergetic reconstructions varied appropriately with energy. This work provides an initial understanding of the limitations and potential applications for monoenergetic imaging.« less

Evanescent field microscopy techniques for studying dynamics at the surface of living cells

NASA Astrophysics Data System (ADS)

Sund, Susan E.

This thesis presents two distinct optical microscopy techniques for applications in cell biophysics: (a)the extension to living cells of an established technique, total internal reflection/fluorescence recovery after photobleaching (TIR/FRAP) for the first time in imaging mode; and (b)the novel development of polarized total internal reflection fluorescence (p- TIRF) to study membrane orientation in living cells. Although reversible chemistry is crucial to dynamical processes in living cells, relatively little is known about the relevant chemical kinetic rates in vivo. TIR/FRAP, an established technique which can measure reversible biomolecular kinetic rates at surfaces, is extended here to measure kinetic parameters of microinjected rhodamine actin at the cytofacial surface of the plasma membrane of living cultured smooth muscle cells. For the first time, spatial imaging (with a CCD camera) is used in conjunction with TIR/FRAP. TIR/FRAP imaging allows production of spatially resolved images of kinetic data, and calculation of correlation distances, cell-wide gradients, and kinetic parameter dependence on initial fluorescence intensity. In living cells, membrane curvature occurs both in easily imaged large scale morphological features, and also in less visualizable submicroscopic regions of activity such as endocytosis, exocytosis, and cell surface ruffling. A fluorescence microscopic method, p-TIRF, is introduced here to visualize such regions. The method is based on fluorescence of the oriented membrane probe diI- C18-(3) (diI) excited by evanescent field light polarized either perpendicular or parallel to the plane of the substrate coverslip. The excitation efficiency from each polarization depends on the membrane orientation, and thus the ratio of the observed fluorescence excited by these two polarizations vividly shows regions of microscopic and submicroscopic curvature of the membrane. A theoretical background of the technique and experimental verifications are presented in samples of protein solutions, model lipid bilayers, and living cells. Sequential digital images of the polarized TIR fluorescence ratios show spatially-resolved time- course maps of membrane orientations on diI labeled macrophages from which low visibility membrane structures can be identified and quantified. The TIR images are sharpened and contrast-enhanced by deconvoluting them with an experimentally-measured point spread function.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

PubMed

Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia

2016-05-31

Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

A Microfluidic Platform to design crosslinked Hyaluronic Acid Nanoparticles (cHANPs) for enhanced MRI

NASA Astrophysics Data System (ADS)

Russo, Maria; Bevilacqua, Paolo; Netti, Paolo Antonio; Torino, Enza

2016-11-01

Recent advancements in imaging diagnostics have focused on the use of nanostructures that entrap Magnetic Resonance Imaging (MRI) Contrast Agents (CAs), without the need to chemically modify the clinically approved compounds. Nevertheless, the exploitation of microfluidic platforms for their controlled and continuous production is still missing. Here, a microfluidic platform is used to synthesize crosslinked Hyaluronic Acid NanoParticles (cHANPs) in which a clinically relevant MRI-CAs, gadolinium diethylenetriamine penta-acetic acid (Gd-DTPA), is entrapped. This microfluidic process facilitates a high degree of control over particle synthesis, enabling the production of monodisperse particles as small as 35 nm. Furthermore, the interference of Gd-DTPA during polymer precipitation is overcome by finely tuning process parameters and leveraging the use of hydrophilic-lipophilic balance (HLB) of surfactants and pH conditions. For both production strategies proposed to design Gd-loaded cHANPs, a boosting of the relaxation rate T1 is observed since a T1 of 1562 is achieved with a 10 μM of Gd-loaded cHANPs while a similar value is reached with 100 μM of the relevant clinical Gd-DTPA in solution. The advanced microfluidic platform to synthesize intravascularly-injectable and completely biocompatible hydrogel nanoparticles entrapping clinically approved CAs enables the implementation of straightforward and scalable strategies in diagnostics and therapy applications.

Estimating the Relevance of World Disturbances to Explain Savings, Interference and Long-Term Motor Adaptation Effects

PubMed Central

Berniker, Max; Kording, Konrad P.

2011-01-01

Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters. PMID:21998574

Measurement of the noise components in the medical x-ray intensity pattern due to overlaying nonrecognizable structures

NASA Astrophysics Data System (ADS)

Tischenko, Oleg; Hoeschen, Christoph; Effenberger, Olaf; Reissberg, Steffen; Buhr, Egbert; Doehring, Wilfried

2003-06-01

There are many aspects that influence and deteriorate the detection of pathologies in X-ray images. Some of those are due to effects taking place in the stage of forming the X-ray intensity pattern in front of the x-ray detector. These can be described as motion blurring, depth blurring, anatomical background, scatter noise and structural noise. Structural noise results from an overlapping of fine irrelevant anatomical structures. A method for measuring the combined effect of structural noise and scatter noise was developed and will be presented in this paper. This method is based on the consideration that within a pair of projections created after rotation of the object with a small angle (which is within the typical uncertainty in positioning the patient) both images would show the same relevant structures whereas the projection of the fine overlapping structures will appear quite differently in the two images. To demonstrate the method two X-ray radiographs of a lung phantom were produced. The second radiograph was achieved after rotating the lung by an angle of about 3. Dyadic wavelet representations of both images were regarded. For each value of the wavelet scale parameter the corresponding pair of approximations was matched using the cross correlation matching technique. The homologous regions of approximations were extracted. The image containing only those structures that appear in both images simultaneously was then reconstructed from the wavelet coefficients corresponding to the homologous regions. The difference between one of the original images and the noise-reduced image contains the structural noise and the scatter noise.

Evaluation of the influence of acquisition parameters of microtomography in image quality applied by carbonate rocks

NASA Astrophysics Data System (ADS)

Santos, T. M. P.; Machado, A. S.; Araújo, O. M. O.; Ferreira, C. G.; Lopes, R. T.

2018-03-01

X-ray computed microtomography is a powerful nondestructive technique for 2D and 3D structure analysis. However, parameters used in acquisition promote directs influence in qualitative and quantitative results in characterization of samples, due image resolution. The aim of this study is value the influence of theses parameters in results through of tests changing these parameters in different situations and system characterization. Results demonstrate those pixel size and detector matrixes are the main parameters that influence in resolution and image quality. Microtomography was considered an excellent technique for characterization using the best image resolution possible.

Reconstruction of biofilm images: combining local and global structural parameters

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

Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk

2014-10-20

Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parametersmore » into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.« less

Comparison of Free-Breathing With Navigator-Triggered Technique in Diffusion Weighted Imaging for Evaluation of Small Hepatocellular Carcinoma: Effect on Image Quality and Intravoxel Incoherent Motion Parameters.

PubMed

Shan, Yan; Zeng, Meng-su; Liu, Kai; Miao, Xi-Yin; Lin, Jiang; Fu, Cai xia; Xu, Peng-ju

2015-01-01

To evaluate the effect on image quality and intravoxel incoherent motion (IVIM) parameters of small hepatocellular carcinoma (HCC) from choice of either free-breathing (FB) or navigator-triggered (NT) diffusion-weighted (DW) imaging. Thirty patients with 37 small HCCs underwent IVIM DW imaging using 12 b values (0-800 s/mm) with 2 sequences: NT, FB. A biexponential analysis with the Bayesian method yielded true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) in small HCCs and liver parenchyma. Apparent diffusion coefficient (ADC) was also calculated. The acquisition time and image quality scores were assessed for 2 sequences. Independent sample t test was used to compare image quality, signal intensity ratio, IVIM parameters, and ADC values between the 2 sequences; reproducibility of IVIM parameters, and ADC values between 2 sequences was assessed with the Bland-Altman method (BA-LA). Image quality with NT sequence was superior to that with FB acquisition (P = 0.02). The mean acquisition time for FB scheme was shorter than that of NT sequence (6 minutes 14 seconds vs 10 minutes 21 seconds ± 10 seconds P < 0.01). The signal intensity ratio of small HCCs did not vary significantly between the 2 sequences. The ADC and IVIM parameters from the 2 sequences show no significant difference. Reproducibility of D*and f parameters in small HCC was poor (BA-LA: 95% confidence interval, -180.8% to 189.2% for D* and -133.8% to 174.9% for f). A moderate reproducibility of D and ADC parameters was observed (BA-LA: 95% confidence interval, -83.5% to 76.8% for D and -74.4% to 88.2% for ADC) between the 2 sequences. The NT DW imaging technique offers no advantage in IVIM parameters measurements of small HCC except better image quality, whereas FB technique offers greater confidence in fitted diffusion parameters for matched acquisition periods.

Content-based image retrieval in medical applications for picture archiving and communication systems

NASA Astrophysics Data System (ADS)

Lehmann, Thomas M.; Guld, Mark O.; Thies, Christian; Fischer, Benedikt; Keysers, Daniel; Kohnen, Michael; Schubert, Henning; Wein, Berthold B.

2003-05-01

Picture archiving and communication systems (PACS) aim to efficiently provide the radiologists with all images in a suitable quality for diagnosis. Modern standards for digital imaging and communication in medicine (DICOM) comprise alphanumerical descriptions of study, patient, and technical parameters. Currently, this is the only information used to select relevant images within PACS. Since textual descriptions insufficiently describe the great variety of details in medical images, content-based image retrieval (CBIR) is expected to have a strong impact when integrated into PACS. However, existing CBIR approaches usually are limited to a distinct modality, organ, or diagnostic study. In this state-of-the-art report, we present first results implementing a general approach to content-based image retrieval in medical applications (IRMA) and discuss its integration into PACS environments. Usually, a PACS consists of a DICOM image server and several DICOM-compliant workstations, which are used by radiologists for reading the images and reporting the findings. Basic IRMA components are the relational database, the scheduler, and the web server, which all may be installed on the DICOM image server, and the IRMA daemons running on distributed machines, e.g., the radiologists" workstations. These workstations can also host the web-based front-ends of IRMA applications. Integrating CBIR and PACS, a special focus is put on (a) location and access transparency for data, methods, and experiments, (b) replication transparency for methods in development, (c) concurrency transparency for job processing and feature extraction, (d) system transparency at method implementation time, and (e) job distribution transparency when issuing a query. Transparent integration will have a certain impact on diagnostic quality supporting both evidence-based medicine and case-based reasoning.

Cardiac CT for myocardial ischaemia detection and characterization--comparative analysis.

PubMed

Bucher, A M; De Cecco, C N; Schoepf, U J; Wang, R; Meinel, F G; Binukrishnan, S R; Spearman, J V; Vogl, T J; Ruzsics, B

2014-11-01

The assessment of patients presenting with symptoms of myocardial ischaemia remains one of the most common and challenging clinical scenarios faced by physicians. Current imaging modalities are capable of three-dimensional, functional and anatomical views of the heart and as such offer a unique contribution to understanding and managing the pathology involved. Evidence has accumulated that visual anatomical coronary evaluation does not adequately predict haemodynamic relevance and should be complemented by physiological evaluation, highlighting the importance of functional assessment. Technical advances in CT technology over the past decade have progressively moved cardiac CT imaging into the clinical workflow. In addition to anatomical evaluation, cardiac CT is capable of providing myocardial perfusion parameters. A variety of CT techniques can be used to assess the myocardial perfusion. The single energy first-pass CT and dual energy first-pass CT allow static assessment of myocardial blood pool. Dynamic cardiac CT imaging allows quantification of myocardial perfusion through time-resolved attenuation data. CT-based myocardial perfusion imaging (MPI) is showing promising diagnostic accuracy compared with the current reference modalities. The aim of this review is to present currently available myocardial perfusion techniques with a focus on CT imaging in light of recent clinical investigations. This article provides a comprehensive overview of currently available CT approaches of static and dynamic MPI and presents the results of corresponding clinical trials.

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Dynamic indocyanine green angiography measurements

NASA Astrophysics Data System (ADS)

Holmes, Timothy; Invernizzi, Alessandro; Larkin, Sean; Staurenghi, Giovanni

2012-11-01

Dynamic indocyanine green imaging uses a scanning laser ophthalmoscope and a fluorescent dye to produce movies of the dye-filling pattern in the retina and choroid of the eye. It is used for evaluating choroidal neovascularization. Movies are examined to identify the anatomy of the pathology for planning treatment and to evaluate progression or response to treatment. The popularity of this approach is affected by the complexity and difficulty in interpreting the movies. Software algorithms were developed to produce images from the movies that are easy to interpret. A mathematical model is formulated of the flow dynamics, and a fitting algorithm is designed that solves for the flow parameters. The images provide information about flow and perfusion, including regions of change between examinations. Imaged measures include the dye fill-time, temporal dispersion, and magnitude of the dye dilution temporal curves associated with image pixels. Cases show how the software can help to identify clinically relevant anatomy such as feeder vessels, drain vessels, capillary networks, and normal choroidal draining vessels. As a potential tool for research into the character of neovascular conditions and treatments, it reveals the flow dynamics and character of the lesion. Future varieties of this methodology may be used for evaluating the success of engineered tissue transplants, surgical flaps, reconstructive surgery, breast surgery, and many other surgical applications where flow, perfusion, and vascularity of tissue are important.

Time-Resolved 3D Quantitative Flow MRI of the Major Intracranial Vessels: Initial Experience and Comparative Evaluation at 1.5T and 3.0T in Combination With Parallel Imaging

PubMed Central

Bammer, Roland; Hope, Thomas A.; Aksoy, Murat; Alley, Marcus T.

2012-01-01

Exact knowledge of blood flow characteristics in the major cerebral vessels is of great relevance for diagnosing cerebrovascular abnormalities. This involves the assessment of hemodynamically critical areas as well as the derivation of biomechanical parameters such as wall shear stress and pressure gradients. A time-resolved, 3D phase-contrast (PC) MRI method using parallel imaging was implemented to measure blood flow in three dimensions at multiple instances over the cardiac cycle. The 4D velocity data obtained from 14 healthy volunteers were used to investigate dynamic blood flow with the use of multiplanar reformatting, 3D streamlines, and 4D particle tracing. In addition, the effects of magnetic field strength, parallel imaging, and temporal resolution on the data were investigated in a comparative evaluation at 1.5T and 3T using three different parallel imaging reduction factors and three different temporal resolutions in eight of the 14 subjects. Studies were consistently performed faster at 3T than at 1.5T because of better parallel imaging performance. A high temporal resolution (65 ms) was required to follow dynamic processes in the intracranial vessels. The 4D flow measurements provided a high degree of vascular conspicuity. Time-resolved streamline analysis provided features that have not been reported previously for the intracranial vasculature. PMID:17195166

Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant.

PubMed

Lender, Anja; Meule, Adrian; Rinck, Mike; Brockmeyer, Timo; Blechert, Jens

2018-06-01

Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them "near" with a joystick that controls a corresponding image zoom. One version of the task couples movement direction with image content-independent features, for example, pulling blue-framed images and pushing green-framed images regardless of content ('irrelevant feature version'). However, participants might selectively attend to this feature and ignore image content and, thus, such a task setup might underestimate existing biases. The present study tested this attention account by comparing two irrelevant feature versions of the task with either a more peripheral (image frame color: green vs. blue) or central (small circle vs. cross overlaid over the image content) image feature as response instruction to a 'relevant feature version', in which participants responded to the image content, thus making it impossible to ignore that content. Images of chocolate-containing foods and of objects were used, and several trait and state measures were acquired to validate the obtained biases. Results revealed a robust approach bias towards food only in the relevant feature condition. Interestingly, a positive correlation with state chocolate craving during the task was found when all three conditions were combined, indicative of criterion validity of all three versions. However, no correlations were found with trait chocolate craving. Results provide a strong case for the relevant feature version of the AAT for bias measurement. They also point to several methodological avenues for future research around selective attention in the irrelevant versions and task validity regarding trait vs. state variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

Towards optimization in digital chest radiography using Monte Carlo modelling

NASA Astrophysics Data System (ADS)

Ullman, Gustaf; Sandborg, Michael; Dance, David R.; Hunt, Roger A.; Alm Carlsson, Gudrun

2006-06-01

A Monte Carlo based computer model of the x-ray imaging system was used to investigate how various image quality parameters of interest in chest PA radiography and the effective dose E vary with tube voltage (90-150 kV), additional copper filtration (0-0.5 mm), anti-scatter method (grid ratios 8-16 and air gap lengths 20-40 cm) and patient thickness (20-28 cm) in a computed radiography (CR) system. Calculated quantities were normalized to a fixed value of air kerma (5.0 µGy) at the automatic exposure control chambers. Soft-tissue nodules were positioned at different locations in the anatomy and calcifications in the apical region. The signal-to-noise ratio, SNR, of the nodules and the nodule contrast relative to the contrast of bone (C/CB) as well as relative to the dynamic range in the image (Crel) were used as image quality measures. In all anatomical regions, except in the densest regions in the thickest patients, the air gap technique provides higher SNR and contrast ratios than the grid technique and at a lower effective dose E. Choice of tube voltage depends on whether quantum noise (SNR) or the contrast ratios are most relevant for the diagnostic task. SNR increases with decreasing tube voltage while C/CB increases with increasing tube voltage.

Linear least-squares method for global luminescent oil film skin friction field analysis

NASA Astrophysics Data System (ADS)

Lee, Taekjin; Nonomura, Taku; Asai, Keisuke; Liu, Tianshu

2018-06-01

A data analysis method based on the linear least-squares (LLS) method was developed for the extraction of high-resolution skin friction fields from global luminescent oil film (GLOF) visualization images of a surface in an aerodynamic flow. In this method, the oil film thickness distribution and its spatiotemporal development are measured by detecting the luminescence intensity of the thin oil film. From the resulting set of GLOF images, the thin oil film equation is solved to obtain an ensemble-averaged (steady) skin friction field as an inverse problem. In this paper, the formulation of a discrete linear system of equations for the LLS method is described, and an error analysis is given to identify the main error sources and the relevant parameters. Simulations were conducted to evaluate the accuracy of the LLS method and the effects of the image patterns, image noise, and sample numbers on the results in comparison with the previous snapshot-solution-averaging (SSA) method. An experimental case is shown to enable the comparison of the results obtained using conventional oil flow visualization and those obtained using both the LLS and SSA methods. The overall results show that the LLS method is more reliable than the SSA method and the LLS method can yield a more detailed skin friction topology in an objective way.

Why the impact of mechanical stimuli on stem cells remains a challenge.

PubMed

Goetzke, Roman; Sechi, Antonio; De Laporte, Laura; Neuss, Sabine; Wagner, Wolfgang

2018-05-04

Mechanical stimulation affects growth and differentiation of stem cells. This may be used to guide lineage-specific cell fate decisions and therefore opens fascinating opportunities for stem cell biology and regenerative medicine. Several studies demonstrated functional and molecular effects of mechanical stimulation but on first sight these results often appear to be inconsistent. Comparison of such studies is hampered by a multitude of relevant parameters that act in concert. There are notorious differences between species, cell types, and culture conditions. Furthermore, the utilized culture substrates have complex features, such as surface chemistry, elasticity, and topography. Cell culture substrates can vary from simple, flat materials to complex 3D scaffolds. Last but not least, mechanical forces can be applied with different frequency, amplitude, and strength. It is therefore a prerequisite to take all these parameters into consideration when ascribing their specific functional relevance-and to only modulate one parameter at the time if the relevance of this parameter is addressed. Such research questions can only be investigated by interdisciplinary cooperation. In this review, we focus particularly on mesenchymal stem cells and pluripotent stem cells to discuss relevant parameters that contribute to the kaleidoscope of mechanical stimulation of stem cells.

Parameter-based estimation of CT dose index and image quality using an in-house android™-based software

NASA Astrophysics Data System (ADS)

Mubarok, S.; Lubis, L. E.; Pawiro, S. A.

2016-03-01

Compromise between radiation dose and image quality is essential in the use of CT imaging. CT dose index (CTDI) is currently the primary dosimetric formalisms in CT scan, while the low and high contrast resolutions are aspects indicating the image quality. This study was aimed to estimate CTDIvol and image quality measures through a range of exposure parameters variation. CTDI measurements were performed using PMMA (polymethyl methacrylate) phantom of 16 cm diameter, while the image quality test was conducted by using catphan ® 600. CTDI measurements were carried out according to IAEA TRS 457 protocol using axial scan mode, under varied parameters of tube voltage, collimation or slice thickness, and tube current. Image quality test was conducted accordingly under the same exposure parameters with CTDI measurements. An Android™ based software was also result of this study. The software was designed to estimate the value of CTDIvol with maximum difference compared to actual CTDIvol measurement of 8.97%. Image quality can also be estimated through CNR parameter with maximum difference to actual CNR measurement of 21.65%.

Piloted studies of Enhanced or Synthetic Vision display parameters

NASA Technical Reports Server (NTRS)

Harris, Randall L., Sr.; Parrish, Russell V.

1992-01-01

This paper summarizes the results of several studies conducted at Langley Research Center over the past few years. The purposes of these studies were to investigate parameters of pictorial displays and imaging sensors that affect pilot approach and landing performance. Pictorial displays have demonstrated exceptional tracking performance and improved the pilots' spatial awareness. Stereopsis cueing improved pilot flight performance and reduced pilot stress. Sensor image parameters such as increased field-of-view. faster image update rate, and aiding symbology improved flare initiation. Finer image resolution and magnification improved attitude control performance parameters.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Characterization of macropore structure of Malan loess in NW China based on 3D pipe models constructed by using computed tomography technology

NASA Astrophysics Data System (ADS)

Li, Yanrong; He, Shengdi; Deng, Xiaohong; Xu, Yongxin

2018-04-01

Malan loess is a grayish yellow or brownish yellow, clastic, highly porous and brittle late Quaternary sediment formed by the accumulation of windblown dust. The present-day pore structure of Malan loess is crucial for understanding the loessification process in history, loess strengths and mechanical behavior. This study employed a modern computed tomography (CT) device to scan Malan loess samples, which were obtained from the east part of the Loess Plateau of China. A sophisticated and efficient workflow for processing the CT images and constructing 3D pore models was established by selecting and programming relevant mathematical algorithms in MATLAB, such as the maximum entropy method, medial axis method, and node recognition algorithm. Individual pipes within the Malan loess were identified and constructed by partitioning and recombining links in the 3D pore model. The macropore structure of Malan loess was then depicted using quantitative parameters. The parameters derived from 2D images of CT scanning included equivalent radius, length and aspect ratio of pores, porosity, and pore distribution entropy, whereas those derived from the constructed 3D structure models included porosity, coordination number, node density, pipe radius, length, length density, dip angle, and dip direction. The analysis of these parameters revealed that Malan loess is a strongly anisotropic geomaterial with a dense and complex network of pores and pipes. The pores discovered on horizontal images, perpendicular to the vertical direction, were round and relatively uniform in shape and size and evenly distributed, whereas the pores discovered on vertical images varied in shape and size and were distributed in clusters. The pores showed good connectivity in vertical direction and formed vertically aligned pipes but displayed weak connectivity in horizontal directions. The pipes in vertical direction were thick, long, and straight compared with those in horizontal directions. These results were in good agreement with both numerical simulation and laboratory permeability tests, which indicate that Malan loess is more permeable in the vertical direction than in the horizontal directions.

3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation.

PubMed

Wörz, Stefan; Schenk, Jens-Peter; Alrajab, Abdulsattar; von Tengg-Kobligk, Hendrik; Rohr, Karl; Arnold, Raoul

2016-10-17

Coarctation of the aorta is one of the most common congenital heart diseases. Despite different treatment opportunities, long-term outcome after surgical or interventional therapy is diverse. Serial morphologic follow-up of vessel growth is necessary, because vessel growth cannot be predicted by primer morphology or a therapeutic option. For the analysis of the long-term outcome after therapy of congenital diseases such as aortic coarctation, accurate 3D geometric analysis of the aorta from follow-up 3D medical image data such as magnetic resonance angiography (MRA) is important. However, for an objective, fast, and accurate 3D geometric analysis, an automatic approach for 3D segmentation and quantification of the aorta from pediatric images is required. We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model that requires only relatively few model parameters. Moreover, we include a novel adaptive background-masking scheme used for least-squares model fitting, we use a spatial normalization scheme to align the segmentation results from follow-up examinations, and we determine relevant 3D geometric parameters of the aortic arch. We have evaluated our proposed approach using different 3D synthetic images. Moreover, we have successfully applied the approach to follow-up pediatric 3D MRA image data, we have normalized the 3D segmentation results of follow-up images of individual patients, and we have combined the results of all patients. We also present a quantitative evaluation of our approach for four follow-up 3D MRA images of a patient, which confirms that our approach yields accurate 3D segmentation results. An experimental comparison with two previous approaches demonstrates that our approach yields superior results. From the results, we found that our approach is well suited for the quantification of the 3D geometry of the aortic arch from follow-up pediatric 3D MRA image data. In future work, this will enable to investigate the long-term outcome of different surgical and interventional therapies for aortic coarctation.

Image quality assessment for CT used on small animals

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

Cisneros, Isabela Paredes, E-mail: iparedesc@unal.edu.co; Agulles-Pedrós, Luis, E-mail: lagullesp@unal.edu.co

Image acquisition on a CT scanner is nowadays necessary in almost any kind of medical study. Its purpose, to produce anatomical images with the best achievable quality, implies the highest diagnostic radiation exposure to patients. Image quality can be measured quantitatively based on parameters such as noise, uniformity and resolution. This measure allows the determination of optimal parameters of operation for the scanner in order to get the best diagnostic image. A human Phillips CT scanner is the first one minded for veterinary-use exclusively in Colombia. The aim of this study was to measure the CT image quality parameters usingmore » an acrylic phantom and then, using the computational tool MATLAB, determine these parameters as a function of current value and window of visualization, in order to reduce dose delivery by keeping the appropriate image quality.« less

Image quality assessment for CT used on small animals

NASA Astrophysics Data System (ADS)

Cisneros, Isabela Paredes; Agulles-Pedrós, Luis

2016-07-01

Image acquisition on a CT scanner is nowadays necessary in almost any kind of medical study. Its purpose, to produce anatomical images with the best achievable quality, implies the highest diagnostic radiation exposure to patients. Image quality can be measured quantitatively based on parameters such as noise, uniformity and resolution. This measure allows the determination of optimal parameters of operation for the scanner in order to get the best diagnostic image. A human Phillips CT scanner is the first one minded for veterinary-use exclusively in Colombia. The aim of this study was to measure the CT image quality parameters using an acrylic phantom and then, using the computational tool MatLab, determine these parameters as a function of current value and window of visualization, in order to reduce dose delivery by keeping the appropriate image quality.

Quantifying the ultrastructure of carotid arteries using high-resolution micro-diffusion tensor imaging—comparison of intact versus open cut tissue

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Gaul, Robert T.; Kerskens, Christian; Flamini, Vittoria; Lally, Caitríona

2017-12-01

Diffusion magnetic resonance imaging (dMRI) can provide insights into the microstructure of intact arterial tissue. The current study employed high magnetic field MRI to obtain ultra-high resolution dMRI at an isotropic voxel resolution of 117 µm3 in less than 2 h of scan time. A parameter selective single shell (128 directions) diffusion-encoding scheme based on Stejskel-Tanner sequence with echo-planar imaging (EPI) readout was used. EPI segmentation was used to reduce the echo time (TE) and to minimise the susceptibility-induced artefacts. The study utilised the dMRI analysis with diffusion tensor imaging (DTI) framework to investigate structural heterogeneity in intact arterial tissue and to quantify variations in tissue composition when the tissue is cut open and flattened. For intact arterial samples, the region of interest base comparison showed significant differences in fractional anisotropy and mean diffusivity across the media layer (p  <  0.05). For open cut flat samples, DTI based directionally invariant indices did not show significant differences across the media layer. For intact samples, fibre tractography based indices such as calculated helical angle and fibre dispersion showed near circumferential alignment and a high degree of fibre dispersion, respectively. This study demonstrates the feasibility of fast dMRI acquisition with ultra-high spatial and angular resolution at 7 T. Using the optimised sequence parameters, this study shows that DTI based markers are sensitive to local structural changes in intact arterial tissue samples and these markers may have clinical relevance in the diagnosis of atherosclerosis and aneurysm.

New bone post-processing tools in forensic imaging: a multi-reader feasibility study to evaluate detection time and diagnostic accuracy in rib fracture assessment.

PubMed

Glemser, Philip A; Pfleiderer, Michael; Heger, Anna; Tremper, Jan; Krauskopf, Astrid; Schlemmer, Heinz-Peter; Yen, Kathrin; Simons, David

2017-03-01

The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.

Mesoscale, Radiometrically Referenced, Multi-Temporal Hyperspectral Data for Co2 Leak Detection by Locating Spatial Variation of Biophysically Relevant Parameters

NASA Astrophysics Data System (ADS)

McCann, Cooper Patrick

Low-cost flight-based hyperspectral imaging systems have the potential to provide valuable information for ecosystem and environmental studies as well as aide in land management and land health monitoring. This thesis describes (1) a bootstrap method of producing mesoscale, radiometrically-referenced hyperspectral data using the Landsat surface reflectance (LaSRC) data product as a reference target, (2) biophysically relevant basis functions to model the reflectance spectra, (3) an unsupervised classification technique based on natural histogram splitting of these biophysically relevant parameters, and (4) local and multi-temporal anomaly detection. The bootstrap method extends standard processing techniques to remove uneven illumination conditions between flight passes, allowing the creation of radiometrically self-consistent data. Through selective spectral and spatial resampling, LaSRC data is used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from a flight on 06/02/2016 is compared with concurrently collected ground based reflectance spectra as a means of validation achieving an average error of 2.74%. Fitting reflectance spectra using basis functions, based on biophysically relevant spectral features, allows both noise and data reductions while shifting information from spectral bands to biophysical features. Histogram splitting is used to determine a clustering based on natural splittings of these fit parameters. The Indian Pines reference data enabled comparisons of the efficacy of this technique to established techniques. The splitting technique is shown to be an improvement over the ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. This improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA. Three hyperspectral flights over the Kevin Dome area, covering 1843 ha, acquired 06/21/2014, 06/24/2015 and 06/26/2016 are examined with different methods of anomaly detection. Detection of anomalies within a single data set is examined to determine, on a local scale, areas that are significantly different from the surrounding area. Additionally, the detection and identification of persistent anomalies and non-persistent anomalies was investigated across multiple data sets.

Calculation of the confidence intervals for transformation parameters in the registration of medical images

PubMed Central

Bansal, Ravi; Staib, Lawrence H.; Laine, Andrew F.; Xu, Dongrong; Liu, Jun; Posecion, Lainie F.; Peterson, Bradley S.

2010-01-01

Images from different individuals typically cannot be registered precisely because anatomical features within the images differ across the people imaged and because the current methods for image registration have inherent technological limitations that interfere with perfect registration. Quantifying the inevitable error in image registration is therefore of crucial importance in assessing the effects that image misregistration may have on subsequent analyses in an imaging study. We have developed a mathematical framework for quantifying errors in registration by computing the confidence intervals of the estimated parameters (3 translations, 3 rotations, and 1 global scale) for the similarity transformation. The presence of noise in images and the variability in anatomy across individuals ensures that estimated registration parameters are always random variables. We assume a functional relation among intensities across voxels in the images, and we use the theory of nonlinear, least-squares estimation to show that the parameters are multivariate Gaussian distributed. We then use the covariance matrix of this distribution to compute the confidence intervals of the transformation parameters. These confidence intervals provide a quantitative assessment of the registration error across the images. Because transformation parameters are nonlinearly related to the coordinates of landmark points in the brain, we subsequently show that the coordinates of those landmark points are also multivariate Gaussian distributed. Using these distributions, we then compute the confidence intervals of the coordinates for landmark points in the image. Each of these confidence intervals in turn provides a quantitative assessment of the registration error at a particular landmark point. Because our method is computationally intensive, however, its current implementation is limited to assessing the error of the parameters in the similarity transformation across images. We assessed the performance of our method in computing the error in estimated similarity parameters by applying that method to real world dataset. Our results showed that the size of the confidence intervals computed using our method decreased – i.e. our confidence in the registration of images from different individuals increased – for increasing amounts of blur in the images. Moreover, the size of the confidence intervals increased for increasing amounts of noise, misregistration, and differing anatomy. Thus, our method precisely quantified confidence in the registration of images that contain varying amounts of misregistration and varying anatomy across individuals. PMID:19138877

Human pose tracking from monocular video by traversing an image motion mapped body pose manifold

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2010-01-01

Tracking human pose from monocular video sequences is a challenging problem due to the large number of independent parameters affecting image appearance and nonlinear relationships between generating parameters and the resultant images. Unlike the current practice of fitting interpolation functions to point correspondences between underlying pose parameters and image appearance, we exploit the relationship between pose parameters and image motion flow vectors in a physically meaningful way. Change in image appearance due to pose change is realized as navigating a low dimensional submanifold of the infinite dimensional Lie group of diffeomorphisms of the two dimensional sphere S2. For small changes in pose, image motion flow vectors lie on the tangent space of the submanifold. Any observed image motion flow vector field is decomposed into the basis motion vector flow fields on the tangent space and combination weights are used to update corresponding pose changes in the different dimensions of the pose parameter space. Image motion flow vectors are largely invariant to style changes in experiments with synthetic and real data where the subjects exhibit variation in appearance and clothing. The experiments demonstrate the robustness of our method (within +/-4° of ground truth) to style variance.

Cell-accurate optical mapping across the entire developing heart.

PubMed

Weber, Michael; Scherf, Nico; Meyer, Alexander M; Panáková, Daniela; Kohl, Peter; Huisken, Jan

2017-12-29

Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca 2+ -mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs.

Retinal vascular imaging technology to monitor disease severity and complications in type 1 diabetes mellitus: A systematic review.

PubMed

Kee, Ae Ra; Wong, Tien Yin; Li, Ling-Jun

2017-02-01

Type 1 diabetes mellitus (T1DM) is a major disease affecting a large number of young patients. In the recent years, retinal vascular imaging has provided an objective assessment of vascular health in patients with T1DM. Our study aimed to review the current literature on retinal vascular parameters in young patients with T1DM in order to understand the following: (i) How retinal vessels are affected in T1DM (ii) How such vascular changes can be predictive of future diabetic microvascular complications METHODS: We performed a systematic review and extracted relevant data from 17 articles. We found significant correlations between retinal vessel changes and diabetes-related risk factors (eg, hypertension, hyperlipidemia, and obesity), diabetes-related features (eg, diabetes duration and glycemic control), and diabetes-related microvascular complications (eg, diabetic retinopathy, nephropathy, and neuropathy). Our findings suggest that retinal microvasculature is associated with both disease severity and complications in young patients with T1DM. © 2016 John Wiley & Sons Ltd.

Cell-accurate optical mapping across the entire developing heart

PubMed Central

Meyer, Alexander M; Panáková, Daniela; Kohl, Peter

2017-01-01

Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca2+-mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs. PMID:29286002

Comprehensive Analysis of Immunological Synapse Phenotypes Using Supported Lipid Bilayers.

PubMed

Valvo, Salvatore; Mayya, Viveka; Seraia, Elena; Afrose, Jehan; Novak-Kotzer, Hila; Ebner, Daniel; Dustin, Michael L

2017-01-01

Supported lipid bilayers (SLB) formed on glass substrates have been a useful tool for study of immune cell signaling since the early 1980s. The mobility of lipid-anchored proteins in the system, first described for antibodies binding to synthetic phospholipid head groups, allows for the measurement of two-dimensional binding reactions and signaling processes in a single imaging plane over time or for fixed samples. The fragility of SLB and the challenges of building and validating individual substrates limit most experimenters to ~10 samples per day, perhaps increasing this few-fold when examining fixed samples. Successful experiments might then require further days to fully analyze. We present methods for automation of many steps in SLB formation, imaging in 96-well glass bottom plates, and analysis that enables >100-fold increase in throughput for fixed samples and wide-field fluorescence. This increased throughput will allow better coverage of relevant parameters and more comprehensive analysis of aspects of the immunological synapse that are well reconstituted by SLB.

Automated Axon Counting in Rodent Optic Nerve Sections with AxonJ.

PubMed

Zarei, Kasra; Scheetz, Todd E; Christopher, Mark; Miller, Kathy; Hedberg-Buenz, Adam; Tandon, Anamika; Anderson, Michael G; Fingert, John H; Abràmoff, Michael David

2016-05-26

We have developed a publicly available tool, AxonJ, which quantifies the axons in optic nerve sections of rodents stained with paraphenylenediamine (PPD). In this study, we compare AxonJ's performance to human experts on 100x and 40x images of optic nerve sections obtained from multiple strains of mice, including mice with defects relevant to glaucoma. AxonJ produced reliable axon counts with high sensitivity of 0.959 and high precision of 0.907, high repeatability of 0.95 when compared to a gold-standard of manual assessments and high correlation of 0.882 to the glaucoma damage staging of a previously published dataset. AxonJ allows analyses that are quantitative, consistent, fully-automated, parameter-free, and rapid on whole optic nerve sections at 40x. As a freely available ImageJ plugin that requires no highly specialized equipment to utilize, AxonJ represents a powerful new community resource augmenting studies of the optic nerve using mice.

Background and imaging simulations for the hard X-ray camera of the MIRAX mission

NASA Astrophysics Data System (ADS)

Castro, M.; Braga, J.; Penacchioni, A.; D'Amico, F.; Sacahui, R.

2016-07-01

We report the results of detailed Monte Carlo simulations of the performance expected both at balloon altitudes and at the probable satellite orbit of a hard X-ray coded-aperture camera being developed for the Monitor e Imageador de RAios X (MIRAX) mission. Based on a thorough mass model of the instrument and detailed specifications of the spectra and angular dependence of the various relevant radiation fields at both the stratospheric and orbital environments, we have used the well-known package GEANT4 to simulate the instrumental background of the camera. We also show simulated images of source fields to be observed and calculated the detailed sensitivity of the instrument in both situations. The results reported here are especially important to researchers in this field considering that we provide important information, not easily found in the literature, on how to prepare input files and calculate crucial instrumental parameters to perform GEANT4 simulations for high-energy astrophysics space experiments.

Computer enhancement of radiographs

NASA Technical Reports Server (NTRS)

Dekaney, A.; Keane, J.; Desautels, J.

1973-01-01

Examination of three relevant noise processes and the image degradation associated with Marshall Space Flight Center's (MSFC) X-ray/scanning system was conducted for application to computer enhancement of radiographs using MSFC's digital filtering techniques. Graininess of type M, R single coat and R double coat X-ray films was quantified as a function of density level using root-mean-square (RMS) granularity. Quantum mottle (including film grain) was quantified as a function of the above film types, exposure level, specimen material and thickness, and film density using RMS granularity and power spectral density (PSD). For various neutral-density levels the scanning device used in digital conversion of radiographs was examined for noise characteristics which were quantified by RMS granularity and PSD. Image degradation of the entire pre-enhancement system (MG-150 X-ray device; film; and optronics scanner) was measured using edge targets to generate modulation transfer functions (MTF). The four parameters were examined as a function of scanning aperture sizes of approximately 12.5 25 and 50 microns.

In Situ Optical Mapping of Voltage and Calcium in the Heart

PubMed Central

Ewart, Paul; Ashley, Euan A.; Loew, Leslie M.; Kohl, Peter; Bollensdorff, Christian; Woods, Christopher E.

2012-01-01

Electroanatomic mapping the interrelation of intracardiac electrical activation with anatomic locations has become an important tool for clinical assessment of complex arrhythmias. Optical mapping of cardiac electrophysiology combines high spatiotemporal resolution of anatomy and physiological function with fast and simultaneous data acquisition. If applied to the clinical setting, this could improve both diagnostic potential and therapeutic efficacy of clinical arrhythmia interventions. The aim of this study was to explore this utility in vivo using a rat model. To this aim, we present a single-camera imaging and multiple light-emitting-diode illumination system that reduces economic and technical implementation hurdles to cardiac optical mapping. Combined with a red-shifted calcium dye and a new near-infrared voltage-sensitive dye, both suitable for use in blood-perfused tissue, we demonstrate the feasibility of in vivo multi-parametric imaging of the mammalian heart. Our approach combines recording of electrophysiologically-relevant parameters with observation of structural substrates and is adaptable, in principle, to trans-catheter percutaneous approaches. PMID:22876327

Sub-nanosecond signal propagation in anisotropy-engineered nanomagnetic logic chains

DOE PAGES

Gu, Zheng; Nowakowski, Mark E.; Carlton, David B.; ...

2015-03-16

Energy efficient nanomagnetic logic (NML) computing architectures propagate binary information by relying on dipolar field coupling to reorient closely spaced nanoscale magnets. In the past, signal propagation in nanomagnet chains were characterized by static magnetic imaging experiments; however, the mechanisms that determine the final state and their reproducibility over millions of cycles in high-speed operation have yet to be experimentally investigated. Here we present a study of NML operation in a high-speed regime. We perform direct imaging of digital signal propagation in permalloy nanomagnet chains with varying degrees of shape-engineered biaxial anisotropy using full-field magnetic X-ray transmission microscopy and time-resolvedmore » photoemission electron microscopy after applying nanosecond magnetic field pulses. Moreover, an intrinsic switching time of 100 ps per magnet is observed. In conclusion these experiments, and accompanying macrospin and micromagnetic simulations, reveal the underlying physics of NML architectures repetitively operated on nanosecond timescales and identify relevant engineering parameters to optimize performance and reliability.« less

Automated Axon Counting in Rodent Optic Nerve Sections with AxonJ

NASA Astrophysics Data System (ADS)

Zarei, Kasra; Scheetz, Todd E.; Christopher, Mark; Miller, Kathy; Hedberg-Buenz, Adam; Tandon, Anamika; Anderson, Michael G.; Fingert, John H.; Abràmoff, Michael David

2016-05-01

We have developed a publicly available tool, AxonJ, which quantifies the axons in optic nerve sections of rodents stained with paraphenylenediamine (PPD). In this study, we compare AxonJ’s performance to human experts on 100x and 40x images of optic nerve sections obtained from multiple strains of mice, including mice with defects relevant to glaucoma. AxonJ produced reliable axon counts with high sensitivity of 0.959 and high precision of 0.907, high repeatability of 0.95 when compared to a gold-standard of manual assessments and high correlation of 0.882 to the glaucoma damage staging of a previously published dataset. AxonJ allows analyses that are quantitative, consistent, fully-automated, parameter-free, and rapid on whole optic nerve sections at 40x. As a freely available ImageJ plugin that requires no highly specialized equipment to utilize, AxonJ represents a powerful new community resource augmenting studies of the optic nerve using mice.

Body mass index and other anthropometric parameters in patients with diffuse large B-cell lymphoma: physiopathological significance and predictive value in the immunochemotherapy era.

PubMed

Sarkozy, Clémentine; Camus, Vincent; Tilly, Hervé; Salles, Gilles; Jardin, Fabrice

2015-07-01

Diffuse large B-cell lymphoma (DLBCL) is the most common form of aggressive non-Hodgkin lymphoma, accounting for 30-40% of newly diagnosed cases. Obesity is a well-defined risk factor for DLBCL. However, the impact of body mass index (BMI) on DLBCL prognosis is controversial. Recent studies suggest that skeletal muscle wasting (sarcopenia) or loss of fat mass can be detected by computed tomography (CT) images and is useful for predicting the clinical outcome in several types of cancer including DLBCL. Several hypotheses have been proposed to explain the differences in DLBCL outcome according to BMI or weight that include tolerance to treatment, inflammatory background and chemotherapy or rituximab metabolism. In this review, we summarize the available literature, addressing the impact and physiopathological relevance of simple anthropometric tools including BMI and tissue distribution measurements. We also discuss their relationship with other nutritional parameters and their potential role in the management of patients with DLBCL.

Value of C-Arm Cone Beam Computed Tomography Image Fusion in Maximizing the Versatility of Endovascular Robotics.

PubMed

Chinnadurai, Ponraj; Duran, Cassidy; Al-Jabbari, Odeaa; Abu Saleh, Walid K; Lumsden, Alan; Bismuth, Jean

2016-01-01

To report our initial experience and highlight the value of using intraoperative C-arm cone beam computed tomography (CT; DynaCT(®)) image fusion guidance along with steerable robotic endovascular catheter navigation to optimize vessel cannulation. Between May 2013 and January 2015, all patients who underwent endovascular procedures using DynaCT image fusion technique along with Hansen Magellan vascular robotic catheter were included in this study. As a part of preoperative planning, relevant vessel landmarks were electronically marked in contrast-enhanced multi-slice computed tomography images and stored. At the beginning of procedure, an intraoperative noncontrast C-arm cone beam CT (syngo DynaCT(®), Siemens Medical Solutions USA Inc.) was acquired in the hybrid suite. Preoperative images were then coregistered to intraoperative DynaCT images using aortic wall calcifications and bone landmarks. Stored landmarks were then overlaid on 2-dimensional (2D) live fluoroscopic images as virtual markers that are updated in real-time with C-arm, table movements and image zoom. Vascular access and robotic catheter (Magellan(®), Hansen Medical) was setup per standard. Vessel cannulation was performed based on electronic virtual markers on live fluoroscopy using robotic catheter. The impact of 3-dimensional (3D) image fusion guidance on robotic vessel cannulation was evaluated retrospectively, by assessing quantitative parameters like number of angiograms acquired before vessel cannulation and qualitative parameters like accuracy of vessel ostium and centerline markers. All 17 vessels were cannulated successfully in 14 patients' attempted using robotic catheter and image fusion guidance. Median vessel diameter at origin was 5.4 mm (range, 2.3-13 mm), whereas 12 of 17 (70.6%) vessels had either calcified and/or stenosed origin from parent vessel. Nine of 17 vessels (52.9 %) were cannulated without any contrast injection. Median number of angiograms required before cannulation was 0 (range, 0-2). On qualitative assessment, 14 of 15 vessels (93.3%) had grade = 1 accuracy (guidewire inside virtual ostial marker). Fourteen of 14 vessels had grade = 1 accuracy (virtual centerlines that matched with the actual vessel trajectory during cannulation). In this small series, the experience of using DynaCT image fusion guidance together with a steerable endovascular robotic catheter indicates that such image fusion strategies can enhance intraoperative 2D fluoroscopy by bringing preoperative 3D information about vascular stenosis and/or calcification, angulation, and take off from main vessel thereby facilitating ultimate vessel cannulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

PubMed

O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

2017-12-06

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

Relative performance analysis of IR FPA technologies from the perspective of system level performance

NASA Astrophysics Data System (ADS)

Haran, Terence L.; James, J. Christopher; Cincotta, Tomas E.

2017-08-01

The majority of high performance infrared systems today utilize FPAs composed of intrinsic direct bandgap semiconductor photon detectors such as MCT or InSb. Quantum well detector technologies such as QWIPs, QDIPs, and SLS photodetectors are potentially lower cost alternatives to MCT and InSb, but the relative performance of these technologies has not been sufficiently high to allow widespread adoption outside of a handful of applications. While detectors are often evaluated using figures of merit such as NETD or D∗, these metrics, which include many underlying aspects such as spectral quantum efficiency, dark current, well size, MTF, and array response uniformity, may be far removed from the performance metrics used to judge performance of a system in an operationally relevant scenario. True comparisons of performance for various detector technologies from the perspective of end-to-end system performance have rarely been conducted, especially considering the rapid progress of the newer quantum well technologies. System level models such as the US Army's Night Vision Integrated Performance Model (NV-IPM) can calculate image contrast and spatial frequency content using data from the target/background, intervening atmosphere, and system components. This paper includes results from a performance parameter sensitivity analysis using NV-IPM to determine the relative importance of various FPA performance parameters to the overall performance of a long range imaging system. Parameters included are: QE, dark current density, quantum well capacity, downstream readout noise, well fill, image frame rate, frame averaging, and residual fixed pattern noise. The state-of-the art for XBn, QWIP, and SLS detector technologies operating in the MWIR and LWIR bands will be surveyed to assess performance of quantum structures compared to MCT and InSb. The intent is to provide a comprehensive assessment of quantum detector performance and to identify areas where increased research could provide the most benefit to overall system level performance.

Single-sensor system for spatially resolved, continuous, and multiparametric optical mapping of cardiac tissue

PubMed Central

Lee, Peter; Bollensdorff, Christian; Quinn, T. Alexander; Wuskell, Joseph P.; Loew, Leslie M.; Kohl, Peter

2011-01-01

Background Simultaneous optical mapping of multiple electrophysiologically relevant parameters in living myocardium is desirable for integrative exploration of mechanisms underlying heart rhythm generation under normal and pathophysiologic conditions. Current multiparametric methods are technically challenging, usually involving multiple sensors and moving parts, which contributes to high logistic and economic thresholds that prevent easy application of the technique. Objective The purpose of this study was to develop a simple, affordable, and effective method for spatially resolved, continuous, simultaneous, and multiparametric optical mapping of the heart, using a single camera. Methods We present a new method to simultaneously monitor multiple parameters using inexpensive off-the-shelf electronic components and no moving parts. The system comprises a single camera, commercially available optical filters, and light-emitting diodes (LEDs), integrated via microcontroller-based electronics for frame-accurate illumination of the tissue. For proof of principle, we illustrate measurement of four parameters, suitable for ratiometric mapping of membrane potential (di-4-ANBDQPQ) and intracellular free calcium (fura-2), in an isolated Langendorff-perfused rat heart during sinus rhythm and ectopy, induced by local electrical or mechanical stimulation. Results The pilot application demonstrates suitability of this imaging approach for heart rhythm research in the isolated heart. In addition, locally induced excitation, whether stimulated electrically or mechanically, gives rise to similar ventricular propagation patterns. Conclusion Combining an affordable camera with suitable optical filters and microprocessor-controlled LEDs, single-sensor multiparametric optical mapping can be practically implemented in a simple yet powerful configuration and applied to heart rhythm research. The moderate system complexity and component cost is destined to lower the threshold to broader application of functional imaging and to ease implementation of more complex optical mapping approaches, such as multiparametric panoramic imaging. A proof-of-principle application confirmed that although electrically and mechanically induced excitation occur by different mechanisms, their electrophysiologic consequences downstream from the point of activation are not dissimilar. PMID:21459161

Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

PubMed

Bidgood, W D; Bray, B; Brown, N; Mori, A R; Spackman, K A; Golichowski, A; Jones, R H; Korman, L; Dove, B; Hildebrand, L; Berg, M

1999-01-01

To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries.

Performance evaluation of algebraic reconstruction technique (ART) for prototype chest digital tomosynthesis (CDT) system

NASA Astrophysics Data System (ADS)

Lee, Haenghwa; Choi, Sunghoon; Jo, Byungdu; Kim, Hyemi; Lee, Donghoon; Kim, Dohyeon; Choi, Seungyeon; Lee, Youngjin; Kim, Hee-Joung

2017-03-01

Chest digital tomosynthesis (CDT) is a new 3D imaging technique that can be expected to improve the detection of subtle lung disease over conventional chest radiography. Algorithm development for CDT system is challenging in that a limited number of low-dose projections are acquired over a limited angular range. To confirm the feasibility of algebraic reconstruction technique (ART) method under variations in key imaging parameters, quality metrics were conducted using LUNGMAN phantom included grand-glass opacity (GGO) tumor. Reconstructed images were acquired from the total 41 projection images over a total angular range of +/-20°. We evaluated contrast-to-noise ratio (CNR) and artifacts spread function (ASF) to investigate the effect of reconstruction parameters such as number of iterations, relaxation parameter and initial guess on image quality. We found that proper value of ART relaxation parameter could improve image quality from the same projection. In this study, proper value of relaxation parameters for zero-image (ZI) and back-projection (BP) initial guesses were 0.4 and 0.6, respectively. Also, the maximum CNR values and the minimum full width at half maximum (FWHM) of ASF were acquired in the reconstructed images after 20 iterations and 3 iterations, respectively. According to the results, BP initial guess for ART method could provide better image quality than ZI initial guess. In conclusion, ART method with proper reconstruction parameters could improve image quality due to the limited angular range in CDT system.

Infrared thermal imaging figures of merit

NASA Technical Reports Server (NTRS)

Kaplan, Herbert

1989-01-01

Commercially available types of infrared thermal imaging instruments, both viewers (qualitative) and imagers (quantitative) are discussed. The various scanning methods by which thermal images (thermograms) are generated will be reviewed. The performance parameters (figures of merit) that define the quality of performance of infrared radiation thermometers will be introduced. A discussion of how these parameters are extended and adapted to define the performance of thermal imaging instruments will be provided. Finally, the significance of each of the key performance parameters of thermal imaging instruments will be reviewed and procedures currently used for testing to verify performance will be outlined.

Target detection in active polarization images perturbed with additive noise and illumination nonuniformity.

PubMed

Bénière, Arnaud; Goudail, François; Dolfi, Daniel; Alouini, Mehdi

2009-07-01

Active imaging systems that illuminate a scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the orthogonal state contrast (OSC) in the scene. Both contrasts are relevant for target detection. However, in real systems, the illumination is often spatially or temporally nonuniform. This creates artificial intensity contrasts that can lead to false alarms. We derive generalized likelihood ratio test (GLRT) detectors, for which intensity information is taken into account or not and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases considering intensity information in addition to polarimetric information is relevant or not.

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

Distinction of Green Sweet Peppers by Using Various Color Space Models and Computation of 3 Dimensional Location Coordinates of Recognized Green Sweet Peppers Based on Parallel Stereovision System

NASA Astrophysics Data System (ADS)

Bachche, Shivaji; Oka, Koichi

2013-06-01

This paper presents the comparative study of various color space models to determine the suitable color space model for detection of green sweet peppers. The images were captured by using CCD cameras and infrared cameras and processed by using Halcon image processing software. The LED ring around the camera neck was used as an artificial lighting to enhance the feature parameters. For color images, CieLab, YIQ, YUV, HSI and HSV whereas for infrared images, grayscale color space models were selected for image processing. In case of color images, HSV color space model was found more significant with high percentage of green sweet pepper detection followed by HSI color space model as both provides information in terms of hue/lightness/chroma or hue/lightness/saturation which are often more relevant to discriminate the fruit from image at specific threshold value. The overlapped fruits or fruits covered by leaves can be detected in better way by using HSV color space model as the reflection feature from fruits had higher histogram than reflection feature from leaves. The IR 80 optical filter failed to distinguish fruits from images as filter blocks useful information on features. Computation of 3D coordinates of recognized green sweet peppers was also conducted in which Halcon image processing software provides location and orientation of the fruits accurately. The depth accuracy of Z axis was examined in which 500 to 600 mm distance between cameras and fruits was found significant to compute the depth distance precisely when distance between two cameras maintained to 100 mm.

A global sensitivity analysis approach for morphogenesis models.

PubMed

Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

2015-11-21

Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Quantitative magnetic resonance micro-imaging methods for pharmaceutical research.

PubMed

Mantle, M D

2011-09-30

The use of magnetic resonance imaging (MRI) as a tool in pharmaceutical research is now well established and the current literature covers a multitude of different pharmaceutically relevant research areas. This review focuses on the use of quantitative magnetic resonance micro-imaging techniques and how they have been exploited to extract information that is of direct relevance to the pharmaceutical industry. The article is divided into two main areas. The first half outlines the theoretical aspects of magnetic resonance and deals with basic magnetic resonance theory, the effects of nuclear spin-lattice (T(1)), spin-spin (T(2)) relaxation and molecular diffusion upon image quantitation, and discusses the applications of rapid magnetic resonance imaging techniques. In addition to the theory, the review aims to provide some practical guidelines for the pharmaceutical researcher with an interest in MRI as to which MRI pulse sequences/protocols should be used and when. The second half of the article reviews the recent advances and developments that have appeared in the literature concerning the use of quantitative micro-imaging methods to pharmaceutically relevant research. Copyright © 2010 Elsevier B.V. All rights reserved.

Single organelle dynamics linked to 3D structure by correlative live-cell imaging and 3D electron microscopy.

PubMed

Fermie, Job; Liv, Nalan; Ten Brink, Corlinda; van Donselaar, Elly G; Müller, Wally H; Schieber, Nicole L; Schwab, Yannick; Gerritsen, Hans C; Klumperman, Judith

2018-05-01

Live-cell correlative light-electron microscopy (live-cell-CLEM) integrates live movies with the corresponding electron microscopy (EM) image, but a major challenge is to relate the dynamic characteristics of single organelles to their 3-dimensional (3D) ultrastructure. Here, we introduce focused ion beam scanning electron microscopy (FIB-SEM) in a modular live-cell-CLEM pipeline for a single organelle CLEM. We transfected cells with lysosomal-associated membrane protein 1-green fluorescent protein (LAMP-1-GFP), analyzed the dynamics of individual GFP-positive spots, and correlated these to their corresponding fine-architecture and immediate cellular environment. By FIB-SEM we quantitatively assessed morphological characteristics, like number of intraluminal vesicles and contact sites with endoplasmic reticulum and mitochondria. Hence, we present a novel way to integrate multiple parameters of subcellular dynamics and architecture onto a single organelle, which is relevant to address biological questions related to membrane trafficking, organelle biogenesis and positioning. Furthermore, by using CLEM to select regions of interest, our method allows for targeted FIB-SEM, which significantly reduces time required for image acquisition and data processing. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Modelling of Cosmic Molecular Masers: Introduction to a Computation Cookbook

NASA Astrophysics Data System (ADS)

Sobolev, Andrej M.; Gray, Malcolm D.

2012-07-01

Numerical modeling of molecular masers is necessary in order to understand their nature and diagnostic capabilities. Model construction requires elaboration of a basic description which allows computation, that is a definition of the parameter space and basic physical relations. Usually, this requires additional thorough studies that can consist of the following stages/parts: relevant molecular spectroscopy and collisional rate coefficients; conditions in and around the masing region (that part of space where population inversion is realized); geometry and size of the masing region (including the question of whether maser spots are discrete clumps or line-of-sight correlations in a much bigger region) and propagation of maser radiation. Output of the maser computer modeling can have the following forms: exploration of parameter space (where do inversions appear in particular maser transitions and their combinations, which parameter values describe a `typical' source, and so on); modeling of individual sources (line flux ratios, spectra, images and their variability); analysis of the pumping mechanism; predictions (new maser transitions, correlations in variability of different maser transitions, and the like). Described schemes (constituents and hierarchy) of the model input and output are based mainly on the experience of the authors and make no claim to be dogmatic.

Structural properties of templated Ge quantum dot arrays: impact of growth and pre-pattern parameters

NASA Astrophysics Data System (ADS)

Tempeler, J.; Danylyuk, S.; Brose, S.; Loosen, P.; Juschkin, L.

2018-07-01

In this study we analyze the impact of process and growth parameters on the structural properties of germanium (Ge) quantum dot (QD) arrays. The arrays were deposited by molecular-beam epitaxy on pre-patterned silicon (Si) substrates. Periodic arrays of pits with diameters between 120 and 20 nm and pitches ranging from 200 nm down to 40 nm were etched into the substrate prior to growth. The structural perfection of the two-dimensional QD arrays was evaluated based on SEM images. The impact of two processing steps on the directed self-assembly of Ge QD arrays is investigated. First, a thin Si buffer layer grown on a pre-patterned substrate reshapes the pre-pattern pits and determines the nucleation and initial shape of the QDs. Subsequently, the deposition parameters of the Ge define the overall shape and uniformity of the QDs. In particular, the growth temperature and the deposition rate are relevant and need to be optimized according to the design of the pre-pattern. Applying this knowledge, we are able to fabricate regular arrays of pyramid shaped QDs with dot densities up to 7.2 × 1010 cm‑2.

Bridging the gap between measurements and modelling: a cardiovascular functional avatar.

PubMed

Casas, Belén; Lantz, Jonas; Viola, Federica; Cedersund, Gunnar; Bolger, Ann F; Carlhäll, Carl-Johan; Karlsson, Matts; Ebbers, Tino

2017-07-24

Lumped parameter models of the cardiovascular system have the potential to assist researchers and clinicians to better understand cardiovascular function. The value of such models increases when they are subject specific. However, most approaches to personalize lumped parameter models have thus far required invasive measurements or fall short of being subject specific due to a lack of the necessary clinical data. Here, we propose an approach to personalize parameters in a model of the heart and the systemic circulation using exclusively non-invasive measurements. The personalized model is created using flow data from four-dimensional magnetic resonance imaging and cuff pressure measurements in the brachial artery. We term this personalized model the cardiovascular avatar. In our proof-of-concept study, we evaluated the capability of the avatar to reproduce pressures and flows in a group of eight healthy subjects. Both quantitatively and qualitatively, the model-based results agreed well with the pressure and flow measurements obtained in vivo for each subject. This non-invasive and personalized approach can synthesize medical data into clinically relevant indicators of cardiovascular function, and estimate hemodynamic variables that cannot be assessed directly from clinical measurements.

Structural properties of templated Ge quantum dot arrays: impact of growth and pre-pattern parameters.

PubMed

Tempeler, J; Danylyuk, S; Brose, S; Loosen, P; Juschkin, L

2018-07-06

In this study we analyze the impact of process and growth parameters on the structural properties of germanium (Ge) quantum dot (QD) arrays. The arrays were deposited by molecular-beam epitaxy on pre-patterned silicon (Si) substrates. Periodic arrays of pits with diameters between 120 and 20 nm and pitches ranging from 200 nm down to 40 nm were etched into the substrate prior to growth. The structural perfection of the two-dimensional QD arrays was evaluated based on SEM images. The impact of two processing steps on the directed self-assembly of Ge QD arrays is investigated. First, a thin Si buffer layer grown on a pre-patterned substrate reshapes the pre-pattern pits and determines the nucleation and initial shape of the QDs. Subsequently, the deposition parameters of the Ge define the overall shape and uniformity of the QDs. In particular, the growth temperature and the deposition rate are relevant and need to be optimized according to the design of the pre-pattern. Applying this knowledge, we are able to fabricate regular arrays of pyramid shaped QDs with dot densities up to 7.2 × 10 10 cm -2 .

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

PubMed

Mete, Mutlu; Sakoglu, Unal; Spence, Jeffrey S; Devous, Michael D; Harris, Thomas S; Adinoff, Bryon

2016-10-06

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2-4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations. The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance. The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants' SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Control-Relevant Modeling, Analysis, and Design for Scramjet-Powered Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Rodriguez, Armando A.; Dickeson, Jeffrey J.; Sridharan, Srikanth; Benavides, Jose; Soloway, Don; Kelkar, Atul; Vogel, Jerald M.

2009-01-01

Within this paper, control-relevant vehicle design concepts are examined using a widely used 3 DOF (plus flexibility) nonlinear model for the longitudinal dynamics of a generic carrot-shaped scramjet powered hypersonic vehicle. Trade studies associated with vehicle/engine parameters are examined. The impact of parameters on control-relevant static properties (e.g. level-flight trimmable region, trim controls, AOA, thrust margin) and dynamic properties (e.g. instability and right half plane zero associated with flight path angle) are examined. Specific parameters considered include: inlet height, diffuser area ratio, lower forebody compression ramp inclination angle, engine location, center of gravity, and mass. Vehicle optimizations is also examined. Both static and dynamic considerations are addressed. The gap-metric optimized vehicle is obtained to illustrate how this control-centric concept can be used to "reduce" scheduling requirements for the final control system. A classic inner-outer loop control architecture and methodology is used to shed light on how specific vehicle/engine design parameter selections impact control system design. In short, the work represents an important first step toward revealing fundamental tradeoffs and systematically treating control-relevant vehicle design.

Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

NASA Astrophysics Data System (ADS)

Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

2013-02-01

Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

Estimation of internal organ motion-induced variance in radiation dose in non-gated radiotherapy

NASA Astrophysics Data System (ADS)

Zhou, Sumin; Zhu, Xiaofeng; Zhang, Mutian; Zheng, Dandan; Lei, Yu; Li, Sicong; Bennion, Nathan; Verma, Vivek; Zhen, Weining; Enke, Charles

2016-12-01

In the delivery of non-gated radiotherapy (RT), owing to intra-fraction organ motion, a certain degree of RT dose uncertainty is present. Herein, we propose a novel mathematical algorithm to estimate the mean and variance of RT dose that is delivered without gating. These parameters are specific to individual internal organ motion, dependent on individual treatment plans, and relevant to the RT delivery process. This algorithm uses images from a patient’s 4D simulation study to model the actual patient internal organ motion during RT delivery. All necessary dose rate calculations are performed in fixed patient internal organ motion states. The analytical and deterministic formulae of mean and variance in dose from non-gated RT were derived directly via statistical averaging of the calculated dose rate over possible random internal organ motion initial phases, and did not require constructing relevant histograms. All results are expressed in dose rate Fourier transform coefficients for computational efficiency. Exact solutions are provided to simplified, yet still clinically relevant, cases. Results from a volumetric-modulated arc therapy (VMAT) patient case are also presented. The results obtained from our mathematical algorithm can aid clinical decisions by providing information regarding both mean and variance of radiation dose to non-gated patients prior to RT delivery.

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

CLASSIFYING MEDICAL IMAGES USING MORPHOLOGICAL APPEARANCE MANIFOLDS.

PubMed

Varol, Erdem; Gaonkar, Bilwaj; Davatzikos, Christos

2013-12-31

Input features for medical image classification algorithms are extracted from raw images using a series of pre processing steps. One common preprocessing step in computational neuroanatomy and functional brain mapping is the nonlinear registration of raw images to a common template space. Typically, the registration methods used are parametric and their output varies greatly with changes in parameters. Most results reported previously perform registration using a fixed parameter setting and use the results as input to the subsequent classification step. The variation in registration results due to choice of parameters thus translates to variation of performance of the classifiers that depend on the registration step for input. Analogous issues have been investigated in the computer vision literature, where image appearance varies with pose and illumination, thereby making classification vulnerable to these confounding parameters. The proposed methodology addresses this issue by sampling image appearances as registration parameters vary, and shows that better classification accuracies can be obtained this way, compared to the conventional approach.

Principles of Quantitative MR Imaging with Illustrated Review of Applicable Modular Pulse Diagrams.

PubMed

Mills, Andrew F; Sakai, Osamu; Anderson, Stephan W; Jara, Hernan

2017-01-01

Continued improvements in diagnostic accuracy using magnetic resonance (MR) imaging will require development of methods for tissue analysis that complement traditional qualitative MR imaging studies. Quantitative MR imaging is based on measurement and interpretation of tissue-specific parameters independent of experimental design, compared with qualitative MR imaging, which relies on interpretation of tissue contrast that results from experimental pulse sequence parameters. Quantitative MR imaging represents a natural next step in the evolution of MR imaging practice, since quantitative MR imaging data can be acquired using currently available qualitative imaging pulse sequences without modifications to imaging equipment. The article presents a review of the basic physical concepts used in MR imaging and how quantitative MR imaging is distinct from qualitative MR imaging. Subsequently, the article reviews the hierarchical organization of major applicable pulse sequences used in this article, with the sequences organized into conventional, hybrid, and multispectral sequences capable of calculating the main tissue parameters of T1, T2, and proton density. While this new concept offers the potential for improved diagnostic accuracy and workflow, awareness of this extension to qualitative imaging is generally low. This article reviews the basic physical concepts in MR imaging, describes commonly measured tissue parameters in quantitative MR imaging, and presents the major available pulse sequences used for quantitative MR imaging, with a focus on the hierarchical organization of these sequences. © RSNA, 2017.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots

PubMed Central

Lelong, Camille C. D.; Burger, Philippe; Jubelin, Guillaume; Roux, Bruno; Labbé, Sylvain; Baret, Frédéric

2008-01-01

This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships. PMID:27879893

Biologically relevant photoacoustic imaging phantoms with tunable optical and acoustic properties

PubMed Central

Vogt, William C.; Jia, Congxian; Wear, Keith A.; Garra, Brian S.; Joshua Pfefer, T.

2016-01-01

Abstract. Established medical imaging technologies such as magnetic resonance imaging and computed tomography rely on well-validated tissue-simulating phantoms for standardized testing of device image quality. The availability of high-quality phantoms for optical-acoustic diagnostics such as photoacoustic tomography (PAT) will facilitate standardization and clinical translation of these emerging approaches. Materials used in prior PAT phantoms do not provide a suitable combination of long-term stability and realistic acoustic and optical properties. Therefore, we have investigated the use of custom polyvinyl chloride plastisol (PVCP) formulations for imaging phantoms and identified a dual-plasticizer approach that provides biologically relevant ranges of relevant properties. Speed of sound and acoustic attenuation were determined over a frequency range of 4 to 9 MHz and optical absorption and scattering over a wavelength range of 400 to 1100 nm. We present characterization of several PVCP formulations, including one designed to mimic breast tissue. This material is used to construct a phantom comprised of an array of cylindrical, hemoglobin-filled inclusions for evaluation of penetration depth. Measurements with a custom near-infrared PAT imager provide quantitative and qualitative comparisons of phantom and tissue images. Results indicate that our PVCP material is uniquely suitable for PAT system image quality evaluation and may provide a practical tool for device validation and intercomparison. PMID:26886681

Robust image modeling techniques with an image restoration application

NASA Astrophysics Data System (ADS)

Kashyap, Rangasami L.; Eom, Kie-Bum

1988-08-01

A robust parameter-estimation algorithm for a nonsymmetric half-plane (NSHP) autoregressive model, where the driving noise is a mixture of a Gaussian and an outlier process, is presented. The convergence of the estimation algorithm is proved. An algorithm to estimate parameters and original image intensity simultaneously from the impulse-noise-corrupted image, where the model governing the image is not available, is also presented. The robustness of the parameter estimates is demonstrated by simulation. Finally, an algorithm to restore realistic images is presented. The entire image generally does not obey a simple image model, but a small portion (e.g., 8 x 8) of the image is assumed to obey an NSHP model. The original image is divided into windows and the robust estimation algorithm is applied for each window. The restoration algorithm is tested by comparing it to traditional methods on several different images.

Structural, functional and spectroscopic MRI studies of methamphetamine addiction.

PubMed

Salo, Ruth; Fassbender, Catherine

2012-01-01

This chapter reviews selected neuroimaging findings related to long-term amphetamine and methamphetamine (MA) use. An overview of structural and functional (fMRI) MR studies, Diffusion Tensor Imaging (DTI), Magnetic Resonance Spectroscopy (MRS) and Positron Emission Tomography (PET) studies conducted in long-term MA abusers is presented. The focus of this chapter is to present the relevant studies as tools to understand brain changes following drug abstinence and recovery from addiction. The behavioral relevance of these neuroimaging studies is discussed as they relate to clinical symptoms and treatment. Within each imaging section this chapter includes a discussion of the relevant imaging studies as they relate to patterns of drug use (i.e., duration of MA use, cumulative lifetime dose and time MA abstinent) as well as an overview of studies that link the imaging findings to cognitive measures. In our conclusion we discuss some of the future directions of neuroimaging as it relates to the pathophysiology of addiction.

Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods.

PubMed

Ulaczyk, Jan; Morawiec, Krzysztof; Zabierowski, Paweł; Drobiazg, Tomasz; Barreau, Nicolas

2017-09-01

A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Matériaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

3D digital image processing for biofilm quantification from confocal laser scanning microscopy: Multidimensional statistical analysis of biofilm modeling

NASA Astrophysics Data System (ADS)

Zielinski, Jerzy S.

The dramatic increase in number and volume of digital images produced in medical diagnostics, and the escalating demand for rapid access to these relevant medical data, along with the need for interpretation and retrieval has become of paramount importance to a modern healthcare system. Therefore, there is an ever growing need for processed, interpreted and saved images of various types. Due to the high cost and unreliability of human-dependent image analysis, it is necessary to develop an automated method for feature extraction, using sophisticated mathematical algorithms and reasoning. This work is focused on digital image signal processing of biological and biomedical data in one- two- and three-dimensional space. Methods and algorithms presented in this work were used to acquire data from genomic sequences, breast cancer, and biofilm images. One-dimensional analysis was applied to DNA sequences which were presented as a non-stationary sequence and modeled by a time-dependent autoregressive moving average (TD-ARMA) model. Two-dimensional analyses used 2D-ARMA model and applied it to detect breast cancer from x-ray mammograms or ultrasound images. Three-dimensional detection and classification techniques were applied to biofilm images acquired using confocal laser scanning microscopy. Modern medical images are geometrically arranged arrays of data. The broadening scope of imaging as a way to organize our observations of the biophysical world has led to a dramatic increase in our ability to apply new processing techniques and to combine multiple channels of data into sophisticated and complex mathematical models of physiological function and dysfunction. With explosion of the amount of data produced in a field of biomedicine, it is crucial to be able to construct accurate mathematical models of the data at hand. Two main purposes of signal modeling are: data size conservation and parameter extraction. Specifically, in biomedical imaging we have four key problems that were addressed in this work: (i) registration, i.e. automated methods of data acquisition and the ability to align multiple data sets with each other; (ii) visualization and reconstruction, i.e. the environment in which registered data sets can be displayed on a plane or in multidimensional space; (iii) segmentation, i.e. automated and semi-automated methods to create models of relevant anatomy from images; (iv) simulation and prediction, i.e. techniques that can be used to simulate growth end evolution of researched phenomenon. Mathematical models can not only be used to verify experimental findings, but also to make qualitative and quantitative predictions, that might serve as guidelines for the future development of technology and/or treatment.

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

Digital image processing and analysis for activated sludge wastewater treatment.

PubMed

Khan, Muhammad Burhan; Lee, Xue Yong; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Malik, Aamir Saeed

2015-01-01

Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

Magnetic Resonance Imaging-derived Flow Parameters for the Analysis of Cardiovascular Diseases and Drug Development.

PubMed

Michael, Dada O; Bamidele, Awojoyogbe O; Adewale, Adesola O; Karem, Boubaker

2013-01-01

Nuclear magnetic resonance (NMR) allows for fast, accurate and noninvasive measurement of fluid flow in restricted and non-restricted media. The results of such measurements may be possible for a very small B 0 field and can be enhanced through detailed examination of generating functions that may arise from polynomial solutions of NMR flow equations in terms of Legendre polynomials and Boubaker polynomials. The generating functions of these polynomials can present an array of interesting possibilities that may be useful for understanding the basic physics of extracting relevant NMR flow information from which various hemodynamic problems can be carefully studied. Specifically, these results may be used to develop effective drugs for cardiovascular-related diseases.

Magnetic Resonance Imaging-derived Flow Parameters for the Analysis of Cardiovascular Diseases and Drug Development

PubMed Central

Michael, Dada O.; Bamidele, Awojoyogbe O.; Adewale, Adesola O.; Karem, Boubaker

2013-01-01

Nuclear magnetic resonance (NMR) allows for fast, accurate and noninvasive measurement of fluid flow in restricted and non-restricted media. The results of such measurements may be possible for a very small B0 field and can be enhanced through detailed examination of generating functions that may arise from polynomial solutions of NMR flow equations in terms of Legendre polynomials and Boubaker polynomials. The generating functions of these polynomials can present an array of interesting possibilities that may be useful for understanding the basic physics of extracting relevant NMR flow information from which various hemodynamic problems can be carefully studied. Specifically, these results may be used to develop effective drugs for cardiovascular-related diseases. PMID:25114546

Cytometric analysis of retinopathies in retinal trypsin digests

NASA Astrophysics Data System (ADS)

Ghanian, Zahra; Staniszewski, Kevin; Sorenson, Christine M.; Sheibani, Nader; Ranji, Mahsa

2014-03-01

The objective of this work was to design an automated image cytometry tool for determination of various retinal vascular parameters including extraction of features that are relevant to postnatal retinal vascular development, and the progression of diabetic retinopathy. To confirm the utility and accuracy of the software, retinal trypsin digest from TSP1-/- and diabetic Akita/+; TSP1-/- mice were analyzed. TSP1 is a critical inhibitor of development of retinopathies and lack of TSP1 exacerbates progression of early diabetic retinopathies. Loss of vascular cells of and gain more acellular capillaries as two major signs of diabetic retinopathies were used to classify a retina as normal or injured. This software allows quantification and high throughput assessment of retinopathy changes associated with diabetes.

SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

NASA Astrophysics Data System (ADS)

Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

2018-05-01

Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

The influence of contour line size and location on the reproducibility of topographic measurement with the Heidelberg Retina Tomograph.

PubMed

Roff, E J; Hosking, S L; Barnes, D A

2001-05-01

The recommended contour line (CL) location with the Heidelberg Retina Tomograph (HRT) is on the inner edge of Elschnig's scleral ring. This study investigated HRT parameter reproducibility when: (i) the CL size is altered relative to Elschnig's ring; (ii) the CL is either redrawn or imported between images. Using the HRT, seven 10 degrees images were acquired for 10 normal volunteers and 10 primary open angle glaucoma (POAG) subjects. A CL was drawn on one image for each subject using Elschnig's scleral ring for reference and imported into subsequent images. The CL diameter was then (a) increased by 50 microns; (b) increased by 100 microns; and (c) decreased by 50 microns. To investigate the effect of the method of contour line transfer between images a CL was: (1) defined for one image and imported to 6 subsequent images; (2) drawn separately for each image. Parameter variability improved as the size of the CL increased for the normal group relative to Elschnig's ring but was unchanged in the POAG group. The export/import function (method 1) resulted in better parameter reproducibility than the redrawing method for both groups. The exporting and importing function resulted in better parameter variability for both subject groups and should be used for transferring CLs across images for the same subject. Increasing the overall CL size relative to Elschnig's scleral ring improved the reproducibility of the measured parameters in the normal group. No significant difference in parameter variability was observed for the POAG group. This suggests that the reproducibility of HRT images are affected more by the variation in topography between images than change in CL definition.

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

DOEpatents

Tobin, Kenneth W; Karnowski, Thomas P; Chaum, Edward

2013-08-06

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Fourier domain image fusion for differential X-ray phase-contrast breast imaging.

PubMed

Coello, Eduardo; Sperl, Jonathan I; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

2017-04-01

X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Sleep mechanisms: Sleep deprivation and detection of changing levels of consciousness

NASA Technical Reports Server (NTRS)

Dement, W. C.; Barchas, J. D.

1972-01-01

An attempt was made to obtain information relevant to assessing the need to sleep and make up for lost sleep. Physiological and behavioral parameters were used as measuring parameters. Sleep deprivation in a restricted environment, derivation of data relevant to determining sleepiness from EEG, and the development of the Sanford Sleepiness Scale were discussed.

A method to optimize the processing algorithm of a computed radiography system for chest radiography.

PubMed

Moore, C S; Liney, G P; Beavis, A W; Saunderson, J R

2007-09-01

A test methodology using an anthropomorphic-equivalent chest phantom is described for the optimization of the Agfa computed radiography "MUSICA" processing algorithm for chest radiography. The contrast-to-noise ratio (CNR) in the lung, heart and diaphragm regions of the phantom, and the "system modulation transfer function" (sMTF) in the lung region, were measured using test tools embedded in the phantom. Using these parameters the MUSICA processing algorithm was optimized with respect to low-contrast detectability and spatial resolution. Two optimum "MUSICA parameter sets" were derived respectively for maximizing the CNR and sMTF in each region of the phantom. Further work is required to find the relative importance of low-contrast detectability and spatial resolution in chest images, from which the definitive optimum MUSICA parameter set can then be derived. Prior to this further work, a compromised optimum MUSICA parameter set was applied to a range of clinical images. A group of experienced image evaluators scored these images alongside images produced from the same radiographs using the MUSICA parameter set in clinical use at the time. The compromised optimum MUSICA parameter set was shown to produce measurably better images.

Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study.

PubMed

Kruggel, Frithjof; Masaki, Fumitaro; Solodkin, Ana

2017-02-15

The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer's Disease Neuroimaging initiative (ADNI). While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level. Interestingly, the neurobiological relevance of the relevant parameter at the individual level describes specific differences associated with aging. In addition, our approach highlights white matter areas that reliably discriminate between patients with Alzheimer's disease and healthy controls with a predictive power of 0.99 and include the hippocampal alveus, the para-hippocampal white matter, the white matter of the posterior cingulate, and optic tracts. In this context, notably the classifier includes a sub-population of patients with minimal cognitive impairment into the pathological domain. Our classifier offers promising features for an accessible biomarker that predicts the risk of conversion to Alzheimer's disease. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf. Significance statement This study assesses neuro-degenerative processes in the brain's white matter as revealed by diffusion-weighted imaging, in order to discriminate healthy from pathological aging in a large sample of elderly subjects. The analysis of time-series examinations in a linear mixed effects model allowed the discrimination of population-based aging processes from individual determinants. We demonstrate that a simple classifier based on white matter imaging data is able to predict the conversion to Alzheimer's disease with a high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

Noise parameter estimation for poisson corrupted images using variance stabilization transforms.

PubMed

Jin, Xiaodan; Xu, Zhenyu; Hirakawa, Keigo

2014-03-01

Noise is present in all images captured by real-world image sensors. Poisson distribution is said to model the stochastic nature of the photon arrival process and agrees with the distribution of measured pixel values. We propose a method for estimating unknown noise parameters from Poisson corrupted images using properties of variance stabilization. With a significantly lower computational complexity and improved stability, the proposed estimation technique yields noise parameters that are comparable in accuracy to the state-of-art methods.

Post-encoding control of working memory enhances processing of relevant information in rhesus monkeys (Macaca mulatta).

PubMed

Brady, Ryan J; Hampton, Robert R

2018-06-01

Working memory is a system by which a limited amount of information can be kept available for processing after the cessation of sensory input. Because working memory resources are limited, it is adaptive to focus processing on the most relevant information. We used a retro-cue paradigm to determine the extent to which monkey working memory possesses control mechanisms that focus processing on the most relevant representations. Monkeys saw a sample array of images, and shortly after the array disappeared, they were visually cued to a location that had been occupied by one of the sample images. The cue indicated which image should be remembered for the upcoming recognition test. By determining whether the monkeys were more accurate and quicker to respond to cued images compared to un-cued images, we tested the hypothesis that monkey working memory focuses processing on relevant information. We found a memory benefit for the cued image in terms of accuracy and retrieval speed with a memory load of two images. With a memory load of three images, we found a benefit in retrieval speed but only after shortening the onset latency of the retro-cue. Our results demonstrate previously unknown flexibility in the cognitive control of memory in monkeys, suggesting that control mechanisms in working memory likely evolved in a common ancestor of humans and monkeys more than 32 million years ago. Future work should be aimed at understanding the interaction between memory load and the ability to control memory resources, and the role of working memory control in generating differences in cognitive capacity among primates. Copyright © 2018 Elsevier B.V. All rights reserved.

Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis

PubMed Central

Muralidharan, Prasanna; Fishbaugh, James; Kim, Eun Young; Johnson, Hans J.; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas

2016-01-01

The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Bayesian mixed-effects shape model that incorporates simultaneous relationships between longitudinal shape data and multiple predictors or covariates to the model. Moreover, we place an Automatic Relevance Determination (ARD) prior on the parameters, that lets us automatically select which covariates are most relevant to the model based on observed data. We evaluate our proposed model and inference procedure on a longitudinal study of Huntington's disease from PREDICT-HD. We first show the utility of the ARD prior for model selection in a univariate modeling of striatal volume, and next we apply the full high-dimensional longitudinal shape model to putamen shapes. PMID:28090246

Transbulbar B-Mode Sonography in Multiple Sclerosis: Clinical and Biological Relevance.

PubMed

De Masi, Roberto; Orlando, Stefania; Conte, Aldo; Pasca, Sergio; Scarpello, Rocco; Spagnolo, Pantaleo; Muscella, Antonella; De Donno, Antonella

2016-12-01

Optic nerve sheath diameter quantification by transbulbar B-mode sonography is a recently validated technique, but its clinical relevance in relapse-free multiple sclerosis patients remains unexplored. In an open-label, comparative, cross-sectional study, we aimed to assess possible differences between patients and healthy controls in terms of optic nerve sheath diameter and its correlation with clinical/paraclinical parameters in this disease. Sixty unselected relapse-free patients and 35 matched healthy controls underwent transbulbar B-mode sonography. Patients underwent routine neurologic examination, brain magnetic resonance imaging and visual evoked potential tests. The mean optic nerve sheath diameter 3 and 5 mm from the eyeball was 22-25% lower in patients than controls and correlated with the Expanded Disability Status Scale (r = -0.34, p = 0.048, and r = -0.32, p = 0.042, respectively). We suggest that optic nerve sheath diameter quantified by transbulbar B-mode sonography should be included in routine assessment of the disease as an extension of the neurologic examination. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

A study on mastectomy samples to evaluate breast imaging quality and potential clinical relevance of differential phase contrast mammography.

PubMed

Hauser, Nik; Wang, Zhentian; Kubik-Huch, Rahel A; Trippel, Mafalda; Singer, Gad; Hohl, Michael K; Roessl, Ewald; Köhler, Thomas; van Stevendaal, Udo; Wieberneit, Nataly; Stampanoni, Marco

2014-03-01

Differential phase contrast and scattering-based x-ray mammography has the potential to provide additional and complementary clinically relevant information compared with absorption-based mammography. The purpose of our study was to provide a first statistical evaluation of the imaging capabilities of the new technique compared with digital absorption mammography. We investigated non-fixed mastectomy samples of 33 patients with invasive breast cancer, using grating-based differential phase contrast mammography (mammoDPC) with a conventional, low-brilliance x-ray tube. We simultaneously recorded absorption, differential phase contrast, and small-angle scattering signals that were combined into novel high-frequency-enhanced images with a dedicated image fusion algorithm. Six international, expert breast radiologists evaluated clinical digital and experimental mammograms in a 2-part blinded, prospective independent reader study. The results were statistically analyzed in terms of image quality and clinical relevance. The results of the comparison of mammoDPC with clinical digital mammography revealed the general quality of the images to be significantly superior (P < 0.001); sharpness, lesion delineation, as well as the general visibility of calcifications to be significantly more assessable (P < 0.001); and delineation of anatomic components of the specimens (surface structures) to be significantly sharper (P < 0.001). Spiculations were significantly better identified, and the overall clinically relevant information provided by mammoDPC was judged to be superior (P < 0.001). Our results demonstrate that complementary information provided by phase and scattering enhanced mammograms obtained with the mammoDPC approach deliver images of generally superior quality. This technique has the potential to improve radiological breast diagnostics.

Linear modeling of human hand-arm dynamics relevant to right-angle torque tool interaction.

PubMed

Ay, Haluk; Sommerich, Carolyn M; Luscher, Anthony F

2013-10-01

A new protocol was evaluated for identification of stiffness, mass, and damping parameters employing a linear model for human hand-arm dynamics relevant to right-angle torque tool use. Powered torque tools are widely used to tighten fasteners in manufacturing industries. While these tools increase accuracy and efficiency of tightening processes, operators are repetitively exposed to impulsive forces, posing risk of upper extremity musculoskeletal injury. A novel testing apparatus was developed that closely mimics biomechanical exposure in torque tool operation. Forty experienced torque tool operators were tested with the apparatus to determine model parameters and validate the protocol for physical capacity assessment. A second-order hand-arm model with parameters extracted in the time domain met model accuracy criterion of 5% for time-to-peak displacement error in 93% of trials (vs. 75% for frequency domain). Average time-to-peak handle displacement and relative peak handle force errors were 0.69 ms and 0.21%, respectively. Model parameters were significantly affected by gender and working posture. Protocol and numerical calculation procedures provide an alternative method for assessing mechanical parameters relevant to right-angle torque tool use. The protocol more closely resembles tool use, and calculation procedures demonstrate better performance of parameter extraction using time domain system identification methods versus frequency domain. Potential future applications include parameter identification for in situ torque tool operation and equipment development for human hand-arm dynamics simulation under impulsive forces that could be used for assessing torque tools based on factors relevant to operator health (handle dynamics and hand-arm reaction force).

Bayesian parameter estimation in spectral quantitative photoacoustic tomography

NASA Astrophysics Data System (ADS)

Pulkkinen, Aki; Cox, Ben T.; Arridge, Simon R.; Kaipio, Jari P.; Tarvainen, Tanja

2016-03-01

Photoacoustic tomography (PAT) is an imaging technique combining strong contrast of optical imaging to high spatial resolution of ultrasound imaging. These strengths are achieved via photoacoustic effect, where a spatial absorption of light pulse is converted into a measurable propagating ultrasound wave. The method is seen as a potential tool for small animal imaging, pre-clinical investigations, study of blood vessels and vasculature, as well as for cancer imaging. The goal in PAT is to form an image of the absorbed optical energy density field via acoustic inverse problem approaches from the measured ultrasound data. Quantitative PAT (QPAT) proceeds from these images and forms quantitative estimates of the optical properties of the target. This optical inverse problem of QPAT is illposed. To alleviate the issue, spectral QPAT (SQPAT) utilizes PAT data formed at multiple optical wavelengths simultaneously with optical parameter models of tissue to form quantitative estimates of the parameters of interest. In this work, the inverse problem of SQPAT is investigated. Light propagation is modelled using the diffusion equation. Optical absorption is described with chromophore concentration weighted sum of known chromophore absorption spectra. Scattering is described by Mie scattering theory with an exponential power law. In the inverse problem, the spatially varying unknown parameters of interest are the chromophore concentrations, the Mie scattering parameters (power law factor and the exponent), and Gruneisen parameter. The inverse problem is approached with a Bayesian method. It is numerically demonstrated, that estimation of all parameters of interest is possible with the approach.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis.

PubMed

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

PubMed Central

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum. PMID:23766941

Automated Root Tracking with "Root System Analyzer"

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Jin, Meina; Ockert, Charlotte; Bol, Roland; Leitner, Daniel

2015-04-01

Crucial factors for plant development are water and nutrient availability in soils. Thus, root architecture is a main aspect of plant productivity and needs to be accurately considered when describing root processes. Images of root architecture contain a huge amount of information, and image analysis helps to recover parameters describing certain root architectural and morphological traits. The majority of imaging systems for root systems are designed for two-dimensional images, such as RootReader2, GiA Roots, SmartRoot, EZ-Rhizo, and Growscreen, but most of them are semi-automated and involve mouse-clicks in each root by the user. "Root System Analyzer" is a new, fully automated approach for recovering root architectural parameters from two-dimensional images of root systems. Individual roots can still be corrected manually in a user interface if required. The algorithm starts with a sequence of segmented two-dimensional images showing the dynamic development of a root system. For each image, morphological operators are used for skeletonization. Based on this, a graph representation of the root system is created. A dynamic root architecture model helps to determine which edges of the graph belong to an individual root. The algorithm elongates each root at the root tip and simulates growth confined within the already existing graph representation. The increment of root elongation is calculated assuming constant growth. For each root, the algorithm finds all possible paths and elongates the root in the direction of the optimal path. In this way, each edge of the graph is assigned to one or more coherent roots. Image sequences of root systems are handled in such a way that the previous image is used as a starting point for the current image. The algorithm is implemented in a set of Matlab m-files. Output of Root System Analyzer is a data structure that includes for each root an identification number, the branching order, the time of emergence, the parent identification number, the distance between branching point to the parent root base, the root length, the root radius and the nodes that belong to each individual root path. This information is relevant for the analysis of dynamic root system development as well as the parameterisation of root architecture models. Here, we show results of Root System Analyzer applied to analyse the root systems of wheat plants grown in rhizotrons. Different treatments with respect to soil moisture and apatite concentrations were used to test the effects of those conditions on root system development. Photographs of the root systems were taken at high spatial and temporal resolution and root systems are automatically tracked.

Classification of microscopy images of Langerhans islets

NASA Astrophysics Data System (ADS)

Å vihlík, Jan; Kybic, Jan; Habart, David; Berková, Zuzana; Girman, Peter; Kříž, Jan; Zacharovová, Klára

2014-03-01

Evaluation of images of Langerhans islets is a crucial procedure for planning an islet transplantation, which is a promising diabetes treatment. This paper deals with segmentation of microscopy images of Langerhans islets and evaluation of islet parameters such as area, diameter, or volume (IE). For all the available images, the ground truth and the islet parameters were independently evaluated by four medical experts. We use a pixelwise linear classifier (perceptron algorithm) and SVM (support vector machine) for image segmentation. The volume is estimated based on circle or ellipse fitting to individual islets. The segmentations were compared with the corresponding ground truth. Quantitative islet parameters were also evaluated and compared with parameters given by medical experts. We can conclude that accuracy of the presented fully automatic algorithm is fully comparable with medical experts.

Selection of regularization parameter in total variation image restoration.

PubMed

Liao, Haiyong; Li, Fang; Ng, Michael K

2009-11-01

We consider and study total variation (TV) image restoration. In the literature there are several regularization parameter selection methods for Tikhonov regularization problems (e.g., the discrepancy principle and the generalized cross-validation method). However, to our knowledge, these selection methods have not been applied to TV regularization problems. The main aim of this paper is to develop a fast TV image restoration method with an automatic selection of the regularization parameter scheme to restore blurred and noisy images. The method exploits the generalized cross-validation (GCV) technique to determine inexpensively how much regularization to use in each restoration step. By updating the regularization parameter in each iteration, the restored image can be obtained. Our experimental results for testing different kinds of noise show that the visual quality and SNRs of images restored by the proposed method is promising. We also demonstrate that the method is efficient, as it can restore images of size 256 x 256 in approximately 20 s in the MATLAB computing environment.

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

Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases.

PubMed

Booij, Tijmen H; Klop, Maarten J D; Yan, Kuan; Szántai-Kis, Csaba; Szokol, Balint; Orfi, Laszlo; van de Water, Bob; Keri, Gyorgy; Price, Leo S

2016-10-01

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting. © 2016 Society for Laboratory Automation and Screening.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

P-glycoprotein (ABCB1) inhibits the influx and increases the efflux of 11C-metoclopramide across the blood-brain barrier: a PET study on non-human primates.

PubMed

Auvity, Sylvain; Caillé, Fabien; Marie, Solène; Wimberley, Catriona; Bauer, Martin; Langer, Oliver; Buvat, Irène; Goutal, Sébastien; Tournier, Nicolas

2018-05-10

Rationale : PET imaging using radiolabeled high-affinity substrates of P-glycoprotein (ABCB1) has convincingly revealed the role of this major efflux transporter in limiting the influx of its substrates from blood into the brain across the blood-brain barrier (BBB). Many drugs, such as metoclopramide, are weak ABCB1 substrates and distribute into the brain even when ABCB1 is fully functional. In this study, we used kinetic modeling and validated simplified methods to highlight and quantify the impact of ABCB1 on the BBB influx and efflux of 11 C-metoclopramide, as a model weak ABCB1 substrate, in non-human primates. Methods : The regional brain kinetics of a tracer dose of 11 C-metoclopramide (298 ± 44 MBq) were assessed in baboons using PET without (n = 4) or with intravenous co-infusion of the ABCB1 inhibitor tariquidar (4 mg/kg/h, n = 4). Metabolite-corrected arterial input functions were generated to estimate the regional volume of distribution ( V T ) as well as the influx ( K 1 ) and efflux ( k 2 ) rate constants, using a one-tissue compartment model. Modeling outcome parameters were correlated with image-derived parameters, i.e. area under the curve AUC 0-30 min and AUC 30-60 min (SUV.min) as well as the elimination slope (k E ; min -1 ) from 30 to 60 min of the regional time-activity curves. Results : Tariquidar significantly increased the brain distribution of 11 C-metoclopramide ( V T = 4.3 ± 0.5 mL/cm 3 and 8.7 ± 0.5 mL/cm 3 for baseline and ABCB1 inhibition conditions, respectively, P<0.001), with a 1.28-fold increase in K 1 (P < 0.05) and a 1.64-fold decrease in k 2 (P < 0.001). The effect of tariquidar was homogeneous across different brain regions. The most sensitive parameters to ABCB1 inhibition were V T (2.02-fold increase) and AUC 30-60 min (2.02-fold increase). V T was significantly (P < 0.0001) correlated with AUC 30-60 min (r 2 = 0.95), AUC 0-30 min (r 2 = 0.87) and k E (r 2 = 0.62). Conclusion : 11 C-metoclopramide PET imaging revealed the relative importance of both the influx hindrance and efflux enhancement components of ABCB1 in a relevant model of the human BBB. The overall impact of ABCB1 on drug delivery to the brain can be non-invasively estimated from image-derived outcome parameters without the need for an arterial input function. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Non-Cooperative Target Imaging and Parameter Estimation with Narrowband Radar Echoes.

PubMed

Yeh, Chun-mao; Zhou, Wei; Lu, Yao-bing; Yang, Jian

2016-01-20

This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are formed on the velocity-acceleration plane at two neighboring coherent processing intervals (CPIs). Then, the rotating velocity (RV) is proposed to be estimated by utilizing the relationship between the positions of the scattering centers among two images. Finally, the target image is rescaled to the range-cross-range plane with the estimated rotational parameter. The validity of the proposed approach is confirmed using numerical simulations.

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

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

Little, K; Lu, Z; MacMahon, H

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, whichmore » were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.« less

MultiDrizzle: An Integrated Pyraf Script for Registering, Cleaning and Combining Images

NASA Astrophysics Data System (ADS)

Koekemoer, A. M.; Fruchter, A. S.; Hook, R. N.; Hack, W.

We present the new PyRAF-based `MultiDrizzle' script, which is aimed at providing a one-step approach to combining dithered HST images. The purpose of this script is to allow easy interaction with the complex suite of tasks in the IRAF/STSDAS `dither' package, as well as the new `PyDrizzle' task, while at the same time retaining the flexibility of these tasks through a number of parameters. These parameters control the various individual steps, such as sky subtraction, image registration, `drizzling' onto separate output images, creation of a clean median image, transformation of the median with `blot' and creation of cosmic ray masks, as well as the final image combination step using `drizzle'. The default parameters of all the steps are set so that the task will work automatically for a wide variety of different types of images, while at the same time allowing adjustment of individual parameters for special cases. The script currently works for both ACS and WFPC2 data, and is now being tested on STIS and NICMOS images. We describe the operation of the script and the effect of various parameters, particularly in the context of combining images from dithered observations using ACS and WFPC2. Additional information is also available at the `MultiDrizzle' home page: http://www.stsci.edu/~koekemoe/multidrizzle/

SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia

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

Kueng, R; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario; Manser, P

Purpose: The values in a PET image which represent activity concentrations of a radioactive tracer are influenced by a large number of parameters including patient conditions as well as image acquisition and reconstruction. This work investigates noise characteristics in PET images for various image acquisition and image reconstruction parameters. Methods: Different phantoms with homogeneous activity distributions were scanned using several acquisition parameters and reconstructed with numerous sets of reconstruction parameters. Images from six PET scanners from different vendors were analyzed and compared with respect to quantitative noise characteristics. Local noise metrics, which give rise to a threshold value defining themore » metric of hypoxic fraction, as well as global noise measures in terms of noise power spectra (NPS) were computed. In addition to variability due to different reconstruction parameters, spatial variability of activity distribution and its noise metrics were investigated. Patient data from clinical trials were mapped onto phantom scans to explore the impact of the scanner’s intrinsic noise variability on quantitative clinical analysis. Results: Local noise metrics showed substantial variability up to an order of magnitude for different reconstruction parameters. Investigations of corresponding NPS revealed reconstruction dependent structural noise characteristics. For the acquisition parameters, noise metrics were guided by Poisson statistics. Large spatial non-uniformity of the noise was observed in both axial and radial direction of a PET image. In addition, activity concentrations in PET images of homogeneous phantom scans showed intriguing spatial fluctuations for most scanners. The clinical metric of the hypoxic fraction was shown to be considerably influenced by the PET scanner’s spatial noise characteristics. Conclusion: We showed that a hypoxic fraction metric based on noise characteristics requires careful consideration of the various dependencies in order to justify its quantitative validity. This work may result in recommendations for harmonizing QA of PET imaging for multi-institutional clinical trials.« less

Benefits of Red-Edge Spectral Band and Texture Features for the Object-based Classification using RapidEye sSatellite Image data

NASA Astrophysics Data System (ADS)

Kim, H. O.; Yeom, J. M.

2014-12-01

Space-based remote sensing in agriculture is particularly relevant to issues such as global climate change, food security, and precision agriculture. Recent satellite missions have opened up new perspectives by offering high spatial resolution, various spectral properties, and fast revisit rates to the same regions. Here, we examine the utility of broadband red-edge spectral information in multispectral satellite image data for classifying paddy rice crops in South Korea. Additionally, we examine how object-based spectral features affect the classification of paddy rice growth stages. For the analysis, two seasons of RapidEye satellite image data were used. The results showed that the broadband red-edge information slightly improved the classification accuracy of the crop condition in heterogeneous paddy rice crop environments, particularly when single-season image data were used. This positive effect appeared to be offset by the multi-temporal image data. Additional texture information brought only a minor improvement or a slight decline, although it is well known to be advantageous for object-based classification in general. We conclude that broadband red-edge information derived from conventional multispectral satellite data has the potential to improve space-based crop monitoring. Because the positive or negative effects of texture features for object-based crop classification could barely be interpreted, the relationships between the textual properties and paddy rice crop parameters at the field scale should be further examined in depth.

Imaging phased telescope array study

NASA Technical Reports Server (NTRS)

Harvey, James E.

1989-01-01

The problems encountered in obtaining a wide field-of-view with large, space-based direct imaging phased telescope arrays were considered. After defining some of the critical systems issues, previous relevant work in the literature was reviewed and summarized. An extensive list was made of potential error sources and the error sources were categorized in the form of an error budget tree including optical design errors, optical fabrication errors, assembly and alignment errors, and environmental errors. After choosing a top level image quality requirment as a goal, a preliminary tops-down error budget allocation was performed; then, based upon engineering experience, detailed analysis, or data from the literature, a bottoms-up error budget reallocation was performed in an attempt to achieve an equitable distribution of difficulty in satisfying the various allocations. This exercise provided a realistic allocation for residual off-axis optical design errors in the presence of state-of-the-art optical fabrication and alignment errors. Three different computational techniques were developed for computing the image degradation of phased telescope arrays due to aberrations of the individual telescopes. Parametric studies and sensitivity analyses were then performed for a variety of subaperture configurations and telescope design parameters in an attempt to determine how the off-axis performance of a phased telescope array varies as the telescopes are scaled up in size. The Air Force Weapons Laboratory (AFWL) multipurpose telescope testbed (MMTT) configuration was analyzed in detail with regard to image degradation due to field curvature and distortion of the individual telescopes as they are scaled up in size.

Cameras for digital microscopy.

PubMed

Spring, Kenneth R

2013-01-01

This chapter reviews the fundamental characteristics of charge-coupled devices (CCDs) and related detectors, outlines the relevant parameters for their use in microscopy, and considers promising recent developments in the technology of detectors. Electronic imaging with a CCD involves three stages--interaction of a photon with the photosensitive surface, storage of the liberated charge, and readout or measurement of the stored charge. The most demanding applications in fluorescence microscopy may require as much as four orders of greater magnitude sensitivity. The image in the present-day light microscope is usually acquired with a CCD camera. The CCD is composed of a large matrix of photosensitive elements (often referred to as "pixels" shorthand for picture elements, which simultaneously capture an image over the entire detector surface. The light-intensity information for each pixel is stored as electronic charge and is converted to an analog voltage by a readout amplifier. This analog voltage is subsequently converted to a numerical value by a digitizer situated on the CCD chip, or very close to it. Several (three to six) amplifiers are required for each pixel, and to date, uniform images with a homogeneous background have been a problem because of the inherent difficulties of balancing the gain in all of the amplifiers. Complementary metal oxide semiconductor sensors also exhibit relatively high noise associated with the requisite high-speed switching. Both of these deficiencies are being addressed, and sensor performance is nearing that required for scientific imaging. Copyright © 1998 Elsevier Inc. All rights reserved.

Fundamentals of Structural Geology

NASA Astrophysics Data System (ADS)

Pollard, David D.; Fletcher, Raymond C.

2005-09-01

Fundamentals of Structural Geology provides a new framework for the investigation of geological structures by integrating field mapping and mechanical analysis. Assuming a basic knowledge of physical geology, introductory calculus and physics, it emphasizes the observational data, modern mapping technology, principles of continuum mechanics, and the mathematical and computational skills, necessary to quantitatively map, describe, model, and explain deformation in Earth's lithosphere. By starting from the fundamental conservation laws of mass and momentum, the constitutive laws of material behavior, and the kinematic relationships for strain and rate of deformation, the authors demonstrate the relevance of solid and fluid mechanics to structural geology. This book offers a modern quantitative approach to structural geology for advanced students and researchers in structural geology and tectonics. It is supported by a website hosting images from the book, additional colour images, student exercises and MATLAB scripts. Solutions to the exercises are available to instructors. The book integrates field mapping using modern technology with the analysis of structures based on a complete mechanics MATLAB is used to visualize physical fields and analytical results and MATLAB scripts can be downloaded from the website to recreate textbook graphics and enable students to explore their choice of parameters and boundary conditions The supplementary website hosts color images of outcrop photographs used in the text, supplementary color images, and images of textbook figures for classroom presentations The textbook website also includes student exercises designed to instill the fundamental relationships, and to encourage the visualization of the evolution of geological structures; solutions are available to instructors

Dynamic imaging model and parameter optimization for a star tracker.

PubMed

Yan, Jinyun; Jiang, Jie; Zhang, Guangjun

2016-03-21

Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters.

Geostatistical characterisation of geothermal parameters for a thermal aquifer storage site in Germany

NASA Astrophysics Data System (ADS)

Rodrigo-Ilarri, J.; Li, T.; Grathwohl, P.; Blum, P.; Bayer, P.

2009-04-01

The design of geothermal systems such as aquifer thermal energy storage systems (ATES) must account for a comprehensive characterisation of all relevant parameters considered for the numerical design model. Hydraulic and thermal conductivities are the most relevant parameters and its distribution determines not only the technical design but also the economic viability of such systems. Hence, the knowledge of the spatial distribution of these parameters is essential for a successful design and operation of such systems. This work shows the first results obtained when applying geostatistical techniques to the characterisation of the Esseling Site in Germany. In this site a long-term thermal tracer test (> 1 year) was performed. On this open system the spatial temperature distribution inside the aquifer was observed over time in order to obtain as much information as possible that yield to a detailed characterisation both of the hydraulic and thermal relevant parameters. This poster shows the preliminary results obtained for the Esseling Site. It has been observed that the common homogeneous approach is not sufficient to explain the observations obtained from the TRT and that parameter heterogeneity must be taken into account.

Image segmentation with a novel regularized composite shape prior based on surrogate study

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

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulatedmore » in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.« less

[68Ga]Pentixafor-PET/CT for imaging of chemokine receptor CXCR4 expression in multiple myeloma - Comparison to [18F]FDG and laboratory values.

PubMed

Lapa, Constantin; Schreder, Martin; Schirbel, Andreas; Samnick, Samuel; Kortüm, Klaus Martin; Herrmann, Ken; Kropf, Saskia; Einsele, Herrmann; Buck, Andreas K; Wester, Hans-Jürgen; Knop, Stefan; Lückerath, Katharina

2017-01-01

Chemokine (C-X-C motif) receptor 4 (CXCR4) is a key factor for tumor growth and metastasis in several types of human cancer including multiple myeloma (MM). Proof-of-concept of CXCR4-directed radionuclide therapy in MM has recently been reported. This study assessed the diagnostic performance of the CXCR4-directed radiotracer [ 68 Ga]Pentixafor in MM and a potential role for stratifying patients to CXCR4-directed therapies. Thirty-five patients with MM underwent [ 68 Ga]Pentixafor-PET/CT for evaluation of eligibility for endoradiotherapy. In 19/35 cases, [ 18 F]FDG-PET/CT for correlation was available. Scans were compared on a patient and on a lesion basis. Tracer uptake was correlated with standard clinical parameters of disease activity. [ 68 Ga]Pentixafor-PET detected CXCR4-positive disease in 23/35 subjects (66%). CXCR4-positivity at PET was independent from myeloma subtypes, cytogenetics or any serological parameters and turned out as a negative prognostic factor. In the 19 patients in whom a comparison to [ 18 F]FDG was available, [ 68 Ga]Pentixafor-PET detected more lesions in 4/19 (21%) subjects, [ 18 F]FDG proved superior in 7/19 (37%). In the remaining 8/19 (42%) patients, both tracers detected an equal number of lesions. [ 18 F]FDG-PET positivity correlated with [ 68 Ga]Pentixafor-PET positivity (p=0.018). [ 68 Ga]Pentixafor-PET provides further evidence that CXCR4 expression frequently occurs in advanced multiple myeloma, representing a negative prognostic factor and a potential target for myeloma specific treatment. However, selecting patients for CXCR4 directed therapies and prognostic stratification seem to be more relevant clinical applications for this novel imaging modality, rather than diagnostic imaging of myeloma.

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

PubMed

Wang, Zhiwei; Liu, Chaoyue; Cheng, Danpeng; Wang, Liang; Yang, Xin; Cheng, Kwang-Ting

2018-05-01

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individually without considering the error tolerance of other steps. As a result, they could either involve unnecessary computational cost or suffer from errors accumulated over steps. In this paper, we present an automated CS PCa detection system, where all steps are optimized jointly in an end-to-end trainable deep neural network. The proposed neural network consists of concatenated subnets: 1) a novel tissue deformation network (TDN) for automated prostate detection and multimodal registration and 2) a dual-path convolutional neural network (CNN) for CS PCa detection. Three types of loss functions, i.e., classification loss, inconsistency loss, and overlap loss, are employed for optimizing all parameters of the proposed TDN and CNN. In the training phase, the two nets mutually affect each other and effectively guide registration and extraction of representative CS PCa-relevant features to achieve results with sufficient accuracy. The entire network is trained in a weakly supervised manner by providing only image-level annotations (i.e., presence/absence of PCa) without exact priors of lesions' locations. Compared with most existing systems which require supervised labels, e.g., manual delineation of PCa lesions, it is much more convenient for clinical usage. Comprehensive evaluation based on fivefold cross validation using 360 patient data demonstrates that our system achieves a high accuracy for CS PCa detection, i.e., a sensitivity of 0.6374 and 0.8978 at 0.1 and 1 false positives per normal/benign patient.

Monitoring of degradation of porous silicon photonic crystals using digital photography

PubMed Central

2014-01-01

We report the monitoring of porous silicon (pSi) degradation in aqueous solutions using a consumer-grade digital camera. To facilitate optical monitoring, the pSi samples were prepared as one-dimensional photonic crystals (rugate filters) by electrochemical etching of highly doped p-type Si wafers using a periodic etch waveform. Two pSi formulations, representing chemistries relevant for self-reporting drug delivery applications, were tested: freshly etched pSi (fpSi) and fpSi coated with the biodegradable polymer chitosan (pSi-ch). Accelerated degradation of the samples in an ethanol-containing pH 10 aqueous basic buffer was monitored in situ by digital imaging with a consumer-grade digital camera with simultaneous optical reflectance spectrophotometric point measurements. As the nanostructured porous silicon matrix dissolved, a hypsochromic shift in the wavelength of the rugate reflectance peak resulted in visible color changes from red to green. While the H coordinate in the hue, saturation, and value (HSV) color space calculated using the as-acquired photographs was a good monitor of degradation at short times (t < 100 min), it was not a useful monitor of sample degradation at longer times since it was influenced by reflections of the broad spectral output of the lamp as well as from the narrow rugate reflectance band. A monotonic relationship was observed between the wavelength of the rugate reflectance peak and an H parameter value calculated from the average red-green-blue (RGB) values of each image by first independently normalizing each channel (R, G, and B) using their maximum and minimum value over the time course of the degradation process. Spectrophotometric measurements and digital image analysis using this H parameter gave consistent relative stabilities of the samples as fpSi > pSi-ch. PMID:25242902

Investigation of Biophysical Mechanisms in Gold Nanoparticle Mediated Laser Manipulation of Cells Using a Multimodal Holographic and Fluorescence Imaging Setup

PubMed Central

Rakoski, Mirko S.; Heinemann, Dag; Schomaker, Markus; Ripken, Tammo; Meyer, Heiko

2015-01-01

Laser based cell manipulation has proven to be a versatile tool in biomedical applications. In this context, combining weakly focused laser pulses and nanostructures, e.g. gold nanoparticles, promises to be useful for high throughput cell manipulation, such as transfection and photothermal therapy. Interactions between laser pulses and gold nanoparticles are well understood. However, it is still necessary to study cell behavior in gold nanoparticle mediated laser manipulation. While parameters like cell viability or perforation efficiency are commonly addressed, the influence of the manipulation process on other essential cell parameters is not sufficiently investigated yet. Thus, we set out to study four relevant cell properties: cell volume and area, ion exchange and cytoskeleton structure after gold nanoparticle based laser manipulation. For this, we designed a multimodal imaging and manipulation setup. 200 nm gold nanoparticles were attached unspecifically to canine cells and irradiated by weakly focused 850 ps laser pulses. Volume and area change in the first minute post laser manipulation was monitored using digital holography. Calcium imaging and cells expressing a marker for filamentous actin (F-actin) served to analyze the ion exchange and the cytoskeleton, respectively. High radiant exposures led to cells exhibiting a tendency to shrink in volume and area, possibly due to outflow of cytoplasm. An intracellular raise in calcium was observed and accompanied by an intercellular calcium wave. This multimodal approach enabled for the first time a comprehensive analysis of the cell behavior in gold nanoparticle mediated cell manipulation. Additionally, this work can pave the way for a better understanding and the evaluation of new applications in the context of cell transfection or photothermal therapy. PMID:25909631

Non-immunogenic dextran-coated superparamagnetic iron oxide nanoparticles: a biocompatible, size-tunable contrast agent for magnetic resonance imaging.

PubMed

Unterweger, Harald; Janko, Christina; Schwarz, Marc; Dézsi, László; Urbanics, Rudolf; Matuszak, Jasmin; Őrfi, Erik; Fülöp, Tamás; Bäuerle, Tobias; Szebeni, János; Journé, Clément; Boccaccini, Aldo R; Alexiou, Christoph; Lyer, Stefan; Cicha, Iwona

2017-01-01

Iron oxide-based contrast agents have been in clinical use for magnetic resonance imaging (MRI) of lymph nodes, liver, intestines, and the cardiovascular system. Superparamagnetic iron oxide nanoparticles (SPIONs) have high potential as a contrast agent for MRI, but no intravenous iron oxide-containing agents are currently approved for clinical imaging. The aim of our work was to analyze the hemocompatibility and immuno-safety of a new type of dextran-coated SPIONs (SPIONdex) and to characterize these nanoparticles with ultra-high-field MRI. Key parameters related to nanoparticle hemocompatibility and immuno-safety were investigated in vitro and ex vivo. To address concerns associated with hypersensitivity reactions to injectable nanoparticulate agents, we analyzed complement activation-related pseudoallergy (CARPA) upon intravenous administration of SPIONdex in a pig model. Furthermore, the size-tunability of SPIONdex and the effects of size reduction on their biocompatibility were investigated. In vitro, SPIONdex did not induce hemolysis, complement or platelet activation, plasma coagulation, or leukocyte procoagulant activity, and had no relevant effect on endothelial cell viability or endothelial-monocytic cell interactions. Furthermore, SPIONdex did not induce CARPA even upon intravenous administration of 5 mg Fe/kg in pigs. Upon SPIONdex administration in mice, decreased liver signal intensity was observed after 15 minutes and was still detectable 24 h later. In addition, by changing synthesis parameters, a reduction in particle size <30 nm was achieved, without affecting their hemo- and biocompatibility. Our findings suggest that due to their excellent biocompatibility, safety upon intravenous administration and size-tunability, SPIONdex particles may represent a suitable candidate for a new-generation MRI contrast agent.

The effect of peripheral chronic salsolinol administration on fat pad adipocytes morphological parameters.

PubMed

Aleksandrovych, Veronika; Kurnik, Magdalena; Białas, Magdalena; Bugajski, Andrzej; Thor, Piotr; Gil, Krzysztof

Salsolinol (1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline) is thought to regulate dopaminergic neurons and to act as a mediator in the neuroendocrine system. We have previously reported that exogenous salsolinol evokes enteric neuronal cell death, leading to the impairment of myenteric neurons density and abnormal intestinal transit in rats. We also observed significant reduction of body weight, related to the disrupted gastrointestinal homeostasis. e aim of current study was to evaluate the influence of prolonged salsolinol administration body weight, food intake, adipose tissue accumulation and fad pad adipocyte morphological parameters assessed by image analysis. Male Wistar rats were subjected to continuous intraperitoneal low dosing of salsolinol - 200 mg/kg in total with ALZET osmotic mini-pumps (Durtec, USA) for 2 or 4 weeks with either normal or high-fat diet. Appropriate groups served as the controls. Food intake, body weight were measured each morning. Both epididymal fat pads were dissected, weighted and processed for routine hematoxylin and eosin staining. e following parameters: cell area, perimeter, long and short axis, aspect ratio and circularity factor were assessed in stained specimens with the image analysis system (Multiscan, Poland). Salsolinol administration significantly reduced total body mass with no differences in total food intake between the groups. The epididymal fat pad weight over final body mass ratio was lower in salsolinol treated rats on high fat diet in comparison with the control groups. e area, perimeter, short and long axis of the fad pad adipocytes were significantly decreased in salsolinol treated animals in comparison with relevant controls. Salsolinol targets some regulatory mechanisms concerned with the basic rat metabolism. Prolonged peripheral salsolinol administration in rats significantly decreases the adipocyte size, and such effect is related to the weight loss and reduced adipose tissue accumulation.

[Definition of the Diagnosis Osteomyelitis-Osteomyelitis Diagnosis Score (ODS)].

PubMed

Schmidt, H G K; Tiemann, A H; Braunschweig, R; Diefenbeck, M; Bühler, M; Abitzsch, D; Haustedt, N; Walter, G; Schoop, R; Heppert, V; Hofmann, G O; Glombitza, M; Grimme, C; Gerlach, U-J; Flesch, I

2011-08-01

The disease "osteomyelitis" is characterised by different symptoms and parameters. Decisive roles in the development of the disease are played by the causative bacteria, the route of infection and the individual defense mechanisms of the host. The diagnosis is based on different symptoms and findings from the clinical history, clinical symptoms, laboratory results, diagnostic imaging, microbiological and histopathological analyses. While different osteomyelitis classifications have been published, there is to the best of our knowledge no score that gives information how sure the diagnosis "osteomyelitis" is in general. For any scientific study of a disease a valid definition is essential. We have developed a special osteomyelitis diagnosis score for the reliable classification of clinical, laboratory and technical findings. The score is based on five diagnostic procedures: 1) clinical history and risk factors, 2) clinical examination and laboratory results, 3) diagnostic imaging (ultrasound, radiology, CT, MRI, nuclear medicine and hybrid methods), 4) microbiology, and 5) histopathology. Each diagnostic procedure is related to many individual findings, which are weighted by a score system, in order to achieve a relevant value for each assessment. If the sum of the five diagnostic criteria is 18 or more points, the diagnosis of osteomyelitis can be viewed as "safe" (diagnosis class A). Between 8-17 points the diagnosis is "probable" (diagnosis class B). Less than 8 points means that the diagnosis is "possible, but unlikely" (class C diagnosis). Since each parameter can score six points at a maximum, a reliable diagnosis can only be achieved if at least 3 parameters are scored with 6 points. The osteomyelitis diagnosis score should help to avoid the false description of a clinical presentation as "osteomyelitis". A safe diagnosis is essential for the aetiology, treatment and outcome studies of osteomyelitis. © Georg Thieme Verlag KG Stuttgart · New York.

Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.

Safe Corridor to Access Clivus for Endoscopic Trans-Sphenoidal Surgery: A Radiological and Anatomical Study

PubMed Central

Cheng, Ye; Zhang, Siwen; Chen, Yong; Zhao, Gang

2015-01-01

Purpose Penetration of the clivus is required for surgical access of the brain stem. The endoscopic transclivus approach is a difficult procedure with high risk of injury to important neurovascular structures. We undertook a novel anatomical and radiological investigation to understand the structure of the clivus and neurovascular structures relevant to the extended trans-nasal trans-sphenoid procedure and determine a safe corridor for the penetration of the clivus. Method We examined the clivus region in the computed tomographic angiography (CTA) images of 220 adults, magnetic resonance (MR) images of 50 adults, and dry skull specimens of 10 adults. Multiplanar reconstruction (MPR) of the CT images was performed, and the anatomical features of the clivus were studied in the coronal, sagittal, and axial planes. The data from the images were used to determine the anatomical parameters of the clivus and neurovascular structures, such as the internal carotid artery and inferior petrosal sinus. Results The examination of the CTA and MR images of the enrolled subjects revealed that the thickness of the clivus helped determine the depth of the penetration, while the distance from the sagittal midline to the important neurovascular structures determined the width of the penetration. Further, data from the CTA and MR images were consistent with those retrieved from the examination of the cadaveric specimens. Conclusion Our findings provided certain pointers that may be useful in guiding the surgery such that inadvertent injury to vital structures is avoided and also provided supportive information for the choice of the appropriate endoscopic equipment. PMID:26368821

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

PubMed

Nguyen, N; Milanfar, P; Golub, G

2001-01-01

In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

Quality control in cone-beam computed tomography (CBCT) EFOMP-ESTRO-IAEA protocol (summary report).

PubMed

de Las Heras Gala, Hugo; Torresin, Alberto; Dasu, Alexandru; Rampado, Osvaldo; Delis, Harry; Hernández Girón, Irene; Theodorakou, Chrysoula; Andersson, Jonas; Holroyd, John; Nilsson, Mats; Edyvean, Sue; Gershan, Vesna; Hadid-Beurrier, Lama; Hoog, Christopher; Delpon, Gregory; Sancho Kolster, Ismael; Peterlin, Primož; Garayoa Roca, Julia; Caprile, Paola; Zervides, Costas

2017-07-01

The aim of the guideline presented in this article is to unify the test parameters for image quality evaluation and radiation output in all types of cone-beam computed tomography (CBCT) systems. The applications of CBCT spread over dental and interventional radiology, guided surgery and radiotherapy. The chosen tests provide the means to objectively evaluate the performance and monitor the constancy of the imaging chain. Experience from all involved associations has been collected to achieve a consensus that is rigorous and helpful for the practice. The guideline recommends to assess image quality in terms of uniformity, geometrical precision, voxel density values (or Hounsfield units where available), noise, low contrast resolution and spatial resolution measurements. These tests usually require the use of a phantom and evaluation software. Radiation output can be determined with a kerma-area product meter attached to the tube case. Alternatively, a solid state dosimeter attached to the flat panel and a simple geometric relationship can be used to calculate the dose to the isocentre. Summary tables including action levels and recommended frequencies for each test, as well as relevant references, are provided. If the radiation output or image quality deviates from expected values, or exceeds documented action levels for a given system, a more in depth system analysis (using conventional tests) and corrective maintenance work may be required. Copyright © 2017. Published by Elsevier Ltd.

AN IMAGING STUDY OF A COMPLEX SOLAR CORONAL RADIO ERUPTION

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

Feng, S. W.; Chen, Y.; Song, H. Q.

2016-08-10

Solar coronal radio bursts are enhanced radio emission excited by energetic electrons accelerated during solar eruptions. Studying these bursts is important for investigating the origin and physical mechanism of energetic particles and further diagnosing coronal parameters. Earlier studies suffered from a lack of simultaneous high-quality imaging data of the radio burst and the eruptive structure in the inner corona. Here we present a study on a complex solar radio eruption consisting of a type II burst and three reversely drifting type III bursts, using simultaneous EUV and radio imaging data. It is found that the type II burst is closelymore » associated with a propagating and evolving CME-driven EUV shock structure, originated initially at the northern shock flank and later transferred to the top part of the shock. This source transfer is coincident with the presence of shock decay and enhancing signatures observed at the corresponding side of the EUV front. The electron energy accelerated by the shock at the flank is estimated to be ∼0.3 c by examining the imaging data of the fast-drifting herringbone structure of the type II burst. The reverse-drifting type III sources are found to be within the ejecta and correlated with a likely reconnection event therein. The implications for further observational studies and relevant space weather forecasting techniques are discussed.« less

A preclinical Talbot-Lau prototype for x-ray dark-field imaging of human-sized objects.

PubMed

Hauke, C; Bartl, P; Leghissa, M; Ritschl, L; Sutter, S M; Weber, T; Zeidler, J; Freudenberger, J; Mertelmeier, T; Radicke, M; Michel, T; Anton, G; Meinel, F G; Baehr, A; Auweter, S; Bondesson, D; Gaass, T; Dinkel, J; Reiser, M; Hellbach, K

2018-06-01

Talbot-Lau x-ray interferometry provides information about the scattering and refractive properties of an object - in addition to the object's attenuation features. Until recently, this method was ineligible for imaging human-sized objects as it is challenging to adapt Talbot-Lau interferometers (TLIs) to the relevant x-ray energy ranges. In this work, we present a preclinical Talbot-Lau prototype capable of imaging human-sized objects with proper image quality at clinically acceptable dose levels. The TLI is designed to match a setup of clinical relevance as closely as possible. The system provides a scan range of 120 × 30 cm 2 by using a scanning beam geometry. Its ultimate load is 100 kg. High aspect ratios and fine grid periods of the gratings ensure a reasonable setup length and clinically relevant image quality. The system is installed in a university hospital and is, therefore, exposed to the external influences of a clinical environment. To demonstrate the system's capabilities, a full-body scan of a euthanized pig was performed. In addition, freshly excised porcine lungs with an extrinsically provoked pneumothorax were mounted into a human thorax phantom and examined with the prototype. Both examination sequences resulted in clinically relevant image quality - even in the case of a skin entrance air kerma of only 0.3 mGy which is in the range of human thoracic imaging. The presented case of a pneumothorax and a reader study showed that the prototype's dark-field images provide added value for pulmonary diagnosis. We demonstrated that a dedicated design of a Talbot-Lau interferometer can be applied to medical imaging by constructing a preclinical Talbot-Lau prototype. We experienced that the system is feasible for imaging human-sized objects and the phase-stepping approach is suitable for clinical practice. Hence, we conclude that Talbot-Lau x-ray imaging has potential for clinical use and enhances the diagnostic power of medical x-ray imaging. © 2018 American Association of Physicists in Medicine.

Automatic Screening and Grading of Age-Related Macular Degeneration from Texture Analysis of Fundus Images

PubMed Central

Phan, Thanh Vân; Seoud, Lama; Chakor, Hadi; Cheriet, Farida

2016-01-01

Age-related macular degeneration (AMD) is a disease which causes visual deficiency and irreversible blindness to the elderly. In this paper, an automatic classification method for AMD is proposed to perform robust and reproducible assessments in a telemedicine context. First, a study was carried out to highlight the most relevant features for AMD characterization based on texture, color, and visual context in fundus images. A support vector machine and a random forest were used to classify images according to the different AMD stages following the AREDS protocol and to evaluate the features' relevance. Experiments were conducted on a database of 279 fundus images coming from a telemedicine platform. The results demonstrate that local binary patterns in multiresolution are the most relevant for AMD classification, regardless of the classifier used. Depending on the classification task, our method achieves promising performances with areas under the ROC curve between 0.739 and 0.874 for screening and between 0.469 and 0.685 for grading. Moreover, the proposed automatic AMD classification system is robust with respect to image quality. PMID:27190636

Measurement methods and accuracy analysis of Chang'E-5 Panoramic Camera installation parameters

NASA Astrophysics Data System (ADS)

Yan, Wei; Ren, Xin; Liu, Jianjun; Tan, Xu; Wang, Wenrui; Chen, Wangli; Zhang, Xiaoxia; Li, Chunlai

2016-04-01

Chang'E-5 (CE-5) is a lunar probe for the third phase of China Lunar Exploration Project (CLEP), whose main scientific objectives are to implement lunar surface sampling and to return the samples back to the Earth. To achieve these goals, investigation of lunar surface topography and geological structure within sampling area seems to be extremely important. The Panoramic Camera (PCAM) is one of the payloads mounted on CE-5 lander. It consists of two optical systems which installed on a camera rotating platform. Optical images of sampling area can be obtained by PCAM in the form of a two-dimensional image and a stereo images pair can be formed by left and right PCAM images. Then lunar terrain can be reconstructed based on photogrammetry. Installation parameters of PCAM with respect to CE-5 lander are critical for the calculation of exterior orientation elements (EO) of PCAM images, which is used for lunar terrain reconstruction. In this paper, types of PCAM installation parameters and coordinate systems involved are defined. Measurement methods combining camera images and optical coordinate observations are studied for this work. Then research contents such as observation program and specific solution methods of installation parameters are introduced. Parametric solution accuracy is analyzed according to observations obtained by PCAM scientifically validated experiment, which is used to test the authenticity of PCAM detection process, ground data processing methods, product quality and so on. Analysis results show that the accuracy of the installation parameters affects the positional accuracy of corresponding image points of PCAM stereo images within 1 pixel. So the measurement methods and parameter accuracy studied in this paper meet the needs of engineering and scientific applications. Keywords: Chang'E-5 Mission; Panoramic Camera; Installation Parameters; Total Station; Coordinate Conversion

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept

NASA Astrophysics Data System (ADS)

Vallières, Martin; Laberge, Sébastien; Diamant, André; El Naqa, Issam

2017-11-01

Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models. As a proof of concept, we evaluated the possibility of enhancing a model constructed for the early prediction of lung metastases in soft-tissue sarcomas by optimizing PET and MR image acquisition protocols via computerized simulations of image acquisitions with varying parameters. Simulated PET images from 30 STS patients were acquired by varying the extent of axial data combined per slice (‘span’). Simulated T 1-weighted and T 2-weighted MR images were acquired by varying the repetition time and echo time in a spin-echo pulse sequence, respectively. We analyzed the impact of the variations of PET and MR image acquisition parameters on individual textures, and we investigated how these variations could enhance the global response and the predictive properties of a texture-based model. Our results suggest that it is feasible to identify an optimal set of image acquisition parameters to improve prediction performance. The model constructed with textures extracted from simulated images acquired with a standard clinical set of acquisition parameters reached an average AUC of 0.84 +/- 0.01 in bootstrap testing experiments. In comparison, the model performance significantly increased using an optimal set of image acquisition parameters (p = 0.04 ), with an average AUC of 0.89 +/- 0.01 . Ultimately, specific acquisition protocols optimized to generate superior radiomics measurements for a given clinical problem could be developed and standardized via dedicated computer simulations and thereafter validated using clinical scanners.

Breast cancer survivorship program: testing for cross-cultural relevance.

PubMed

Chung, Lynna K; Cimprich, Bernadine; Janz, Nancy K; Mills-Wisneski, Sharon M

2009-01-01

Taking CHARGE, a theory-based self-management program, was developed to assist women with survivorship concerns that arise after breast cancer treatment. Few such programs have been evaluated for cultural relevance with diverse groups. This study determined the utility and cultural relevance of the program for African American (AA) breast cancer survivors. Two focus groups were held with AA women (n = 13), aged 41 to 72 years, who had completed primary treatment. Focus group participants assessed the program content, format, materials, and the self-regulation process. Content analysis of audiotapes was conducted using an open, focused coding process to identify emergent themes regarding program relevance and topics requiring enhancement and/or further emphasis. Although findings indicated that the program's content was relevant to participants' experiences, AA women identified need for cultural enhancements in spirituality, self-preservation, and positive valuations of body image. Content areas requiring more emphasis included persistent fatigue, competing demands, disclosure, anticipatory guidance, and age-specific concerns about body image/sexuality. Suggested improvements to program materials included portable observation logs, additional resources, more photographs of younger AA women, vivid colors, and images depicting strength. These findings provide the basis for program enhancements to increase the utility and cultural relevance of Taking CHARGE for AA survivors and underscore the importance of evaluating interventions for racially/ethnically diverse groups.

Characterizing pulmonary blood flow distribution measured using arterial spin labeling.

PubMed

Henderson, A Cortney; Prisk, G Kim; Levin, David L; Hopkins, Susan R; Buxton, Richard B

2009-12-01

The arterial spin labeling (ASL) method provides images in which, ideally, the signal intensity of each image voxel is proportional to the local perfusion. For studies of pulmonary perfusion, the relative dispersion (RD, standard deviation/mean) of the ASL signal across a lung section is used as a reliable measure of flow heterogeneity. However, the RD of the ASL signals within the lung may systematically differ from the true RD of perfusion because the ASL image also includes signals from larger vessels, which can reflect the blood volume rather than blood flow if the vessels are filled with tagged blood during the imaging time. Theoretical studies suggest that the pulmonary vasculature exhibits a lognormal distribution for blood flow and thus an appropriate measure of heterogeneity is the geometric standard deviation (GSD). To test whether the ASL signal exhibits a lognormal distribution for pulmonary blood flow, determine whether larger vessels play an important role in the distribution, and extract physiologically relevant measures of heterogeneity from the ASL signal, we quantified the ASL signal before and after an intervention (head-down tilt) in six subjects. The distribution of ASL signal was better characterized by a lognormal distribution than a normal distribution, reducing the mean squared error by 72% (p < 0.005). Head-down tilt significantly reduced the lognormal scale parameter (p = 0.01) but not the shape parameter or GSD. The RD increased post-tilt and remained significantly elevated (by 17%, p < 0.05). Test case results and mathematical simulations suggest that RD is more sensitive than the GSD to ASL signal from tagged blood in larger vessels, a probable explanation of the change in RD without a statistically significant change in GSD. This suggests that the GSD is a useful measure of pulmonary blood flow heterogeneity with the advantage of being less affected by the ASL signal from tagged blood in larger vessels.

Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

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

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less

Techniques for recognizing identity of several response functions from the data of visual inspection

NASA Astrophysics Data System (ADS)

Nechval, Nicholas A.

1996-08-01

The purpose of this paper is to present some efficient techniques for recognizing from the observed data whether several response functions are identical to each other. For example, in an industrial setting the problem may be to determine whether the production coefficients established in a small-scale pilot study apply to each of several large- scale production facilities. The techniques proposed here combine sensor information from automated visual inspection of manufactured products which is carried out by means of pixel-by-pixel comparison of the sensed image of the product to be inspected with some reference pattern (or image). Let (a1, . . . , am) be p-dimensional parameters associated with m response models of the same type. This study is concerned with the simultaneous comparison of a1, . . . , am. A generalized maximum likelihood ratio (GMLR) test is derived for testing equality of these parameters, where each of the parameters represents a corresponding vector of regression coefficients. The GMLR test reduces to an equivalent test based on a statistic that has an F distribution. The main advantage of the test lies in its relative simplicity and the ease with which it can be applied. Another interesting test for the same problem is an application of Fisher's method of combining independent test statistics which can be considered as a parallel procedure to the GMLR test. The combination of independent test statistics does not appear to have been used very much in applied statistics. There does, however, seem to be potential data analytic value in techniques for combining distributional assessments in relation to statistically independent samples which are of joint experimental relevance. In addition, a new iterated test for the problem defined above is presented. A rejection of the null hypothesis by this test provides some reason why all the parameters are not equal. A numerical example is discussed in the context of the proposed procedures for hypothesis testing.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-02-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

A scale self-adapting segmentation approach and knowledge transfer for automatically updating land use/cover change databases using high spatial resolution images

NASA Astrophysics Data System (ADS)

Wang, Zhihua; Yang, Xiaomei; Lu, Chen; Yang, Fengshuo

2018-07-01

Automatic updating of land use/cover change (LUCC) databases using high spatial resolution images (HSRI) is important for environmental monitoring and policy making, especially for coastal areas that connect the land and coast and that tend to change frequently. Many object-based change detection methods are proposed, especially those combining historical LUCC with HSRI. However, the scale parameter(s) segmenting the serial temporal images, which directly determines the average object size, is hard to choose without experts' intervention. And the samples transferred from historical LUCC also need experts' intervention to avoid insufficient or wrong samples. With respect to the scale parameter(s) choosing, a Scale Self-Adapting Segmentation (SSAS) approach based on the exponential sampling of a scale parameter and location of the local maximum of a weighted local variance was proposed to determine the scale selection problem when segmenting images constrained by LUCC for detecting changes. With respect to the samples transferring, Knowledge Transfer (KT), a classifier trained on historical images with LUCC and applied in the classification of updated images, was also proposed. Comparison experiments were conducted in a coastal area of Zhujiang, China, using SPOT 5 images acquired in 2005 and 2010. The results reveal that (1) SSAS can segment images more effectively without intervention of experts. (2) KT can also reach the maximum accuracy of samples transfer without experts' intervention. Strategy SSAS + KT would be a good choice if the temporal historical image and LUCC match, and the historical image and updated image are obtained from the same resource.

Prognostic Value of Pretherapeutic Tumor-to-Blood Standardized Uptake Ratio in Patients with Esophageal Carcinoma.

PubMed

Bütof, Rebecca; Hofheinz, Frank; Zöphel, Klaus; Stadelmann, Tobias; Schmollack, Julia; Jentsch, Christina; Löck, Steffen; Kotzerke, Jörg; Baumann, Michael; van den Hoff, Jörg

2015-08-01

Despite ongoing efforts to develop new treatment options, the prognosis for patients with inoperable esophageal carcinoma is still poor and the reliability of individual therapy outcome prediction based on clinical parameters is not convincing. The aim of this work was to investigate whether PET can provide independent prognostic information in such a patient group and whether the tumor-to-blood standardized uptake ratio (SUR) can improve the prognostic value of tracer uptake values. (18)F-FDG PET/CT was performed in 130 consecutive patients (mean age ± SD, 63 ± 11 y; 113 men, 17 women) with newly diagnosed esophageal cancer before definitive radiochemotherapy. In the PET images, the metabolically active tumor volume (MTV) of the primary tumor was delineated with an adaptive threshold method. The blood standardized uptake value (SUV) was determined by manually delineating the aorta in the low-dose CT. SUR values were computed as the ratio of tumor SUV and blood SUV. Uptake values were scan-time-corrected to 60 min after injection. Univariate Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), distant metastases-free survival (DM), and locoregional tumor control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. In multivariate Cox regression with respect to OS, including T stage, N stage, and smoking state, MTV- and SUR-based parameters were significant prognostic factors for OS with similar effect size. Multivariate analysis with respect to DM revealed smoking state, MTV, and all SUR-based parameters as significant prognostic factors. The highest hazard ratios (HRs) were found for scan-time-corrected maximum SUR (HR = 3.9) and mean SUR (HR = 4.4). None of the PET parameters was associated with LRC. Univariate Cox regression with respect to LRC revealed a significant effect only for N stage greater than 0 (P = 0.048). PET provides independent prognostic information for OS and DM but not for LRC in patients with locally advanced esophageal carcinoma treated with definitive radiochemotherapy in addition to clinical parameters. Among the investigated uptake-based parameters, only SUR was an independent prognostic factor for OS and DM. These results suggest that the prognostic value of tracer uptake can be improved when characterized by SUR instead of SUV. Further investigations are required to confirm these preliminary results. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Direct reconstruction of pharmacokinetic parameters in dynamic fluorescence molecular tomography by the augmented Lagrangian method

NASA Astrophysics Data System (ADS)

Zhu, Dianwen; Zhang, Wei; Zhao, Yue; Li, Changqing

2016-03-01

Dynamic fluorescence molecular tomography (FMT) has the potential to quantify physiological or biochemical information, known as pharmacokinetic parameters, which are important for cancer detection, drug development and delivery etc. To image those parameters, there are indirect methods, which are easier to implement but tend to provide images with low signal-to-noise ratio, and direct methods, which model all the measurement noises together and are statistically more efficient. The direct reconstruction methods in dynamic FMT have attracted a lot of attention recently. However, the coupling of tomographic image reconstruction and nonlinearity of kinetic parameter estimation due to the compartment modeling has imposed a huge computational burden to the direct reconstruction of the kinetic parameters. In this paper, we propose to take advantage of both the direct and indirect reconstruction ideas through a variable splitting strategy under the augmented Lagrangian framework. Each iteration of the direct reconstruction is split into two steps: the dynamic FMT image reconstruction and the node-wise nonlinear least squares fitting of the pharmacokinetic parameter images. Through numerical simulation studies, we have found that the proposed algorithm can achieve good reconstruction results within a small amount of time. This will be the first step for a combined dynamic PET and FMT imaging in the future.

Review of 3D image data calibration for heterogeneity correction in proton therapy treatment planning.

PubMed

Zhu, Jiahua; Penfold, Scott N

2016-06-01

Correct modelling of the interaction parameters of patient tissues is of vital importance in proton therapy treatment planning because of the large dose gradients associated with the Bragg peak. Different 3D imaging techniques yield different information regarding these interaction parameters. Given the rapidly expanding interest in proton therapy, this review is written to make readers aware of the current challenges in accounting for tissue heterogeneities and the imaging systems that are proposed to tackle these challenges. A summary of the interaction parameters of interest in proton therapy and the current and developmental 3D imaging techniques used in proton therapy treatment planning is given. The different methods to translate the imaging data to the interaction parameters of interest are reviewed and a summary of the implementations in several commercial treatment planning systems is presented.

RMB identification based on polarization parameters inversion imaging

NASA Astrophysics Data System (ADS)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

Social order is threatened by counterfeit money. Conventional anti-counterfeit technology is much too old to identify its authenticity or not. The intrinsic difference between genuine notes and counterfeit notes is its paper tissue. In this paper a new technology of detecting RMB is introduced, the polarization parameter indirect microscopic imaging technique. A conventional reflection microscopic system is used as the basic optical system, and inserting into it with polarization-modulation mechanics. The near-field structural characteristics can be delivered by optical wave and material coupling. According to coupling and conduction physics, calculate the changes of optical wave parameters, then get the curves of the intensity of the image. By analyzing near-field polarization parameters in nanoscale, finally calculate indirect polarization parameter imaging of the fiber of the paper tissue in order to identify its authenticity.

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

Constrained optimization of image restoration filters

NASA Technical Reports Server (NTRS)

Riemer, T. E.; Mcgillem, C. D.

1973-01-01

A linear shift-invariant preprocessing technique is described which requires no specific knowledge of the image parameters and which is sufficiently general to allow the effective radius of the composite imaging system to be minimized while constraining other system parameters to remain within specified limits.

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.

Full automatic fiducial marker detection on coil arrays for accurate instrumentation placement during MRI guided breast interventions

NASA Astrophysics Data System (ADS)

Filippatos, Konstantinos; Boehler, Tobias; Geisler, Benjamin; Zachmann, Harald; Twellmann, Thorsten

2010-02-01

With its high sensitivity, dynamic contrast-enhanced MR imaging (DCE-MRI) of the breast is today one of the first-line tools for early detection and diagnosis of breast cancer, particularly in the dense breast of young women. However, many relevant findings are very small or occult on targeted ultrasound images or mammography, so that MRI guided biopsy is the only option for a precise histological work-up [1]. State-of-the-art software tools for computer-aided diagnosis of breast cancer in DCE-MRI data offer also means for image-based planning of biopsy interventions. One step in the MRI guided biopsy workflow is the alignment of the patient position with the preoperative MR images. In these images, the location and orientation of the coil localization unit can be inferred from a number of fiducial markers, which for this purpose have to be manually or semi-automatically detected by the user. In this study, we propose a method for precise, full-automatic localization of fiducial markers, on which basis a virtual localization unit can be subsequently placed in the image volume for the purpose of determining the parameters for needle navigation. The method is based on adaptive thresholding for separating breast tissue from background followed by rigid registration of marker templates. In an evaluation of 25 clinical cases comprising 4 different commercial coil array models and 3 different MR imaging protocols, the method yielded a sensitivity of 0.96 at a false positive rate of 0.44 markers per case. The mean distance deviation between detected fiducial centers and ground truth information that was appointed from a radiologist was 0.94mm.

Standardized processing of MALDI imaging raw data for enhancement of weak analyte signals in mouse models of gastric cancer and Alzheimer's disease.

PubMed

Schwartz, Matthias; Meyer, Björn; Wirnitzer, Bernhard; Hopf, Carsten

2015-03-01

Conventional mass spectrometry image preprocessing methods used for denoising, such as the Savitzky-Golay smoothing or discrete wavelet transformation, typically do not only remove noise but also weak signals. Recently, memory-efficient principal component analysis (PCA) in conjunction with random projections (RP) has been proposed for reversible compression and analysis of large mass spectrometry imaging datasets. It considers single-pixel spectra in their local context and consequently offers the prospect of using information from the spectra of adjacent pixels for denoising or signal enhancement. However, little systematic analysis of key RP-PCA parameters has been reported so far, and the utility and validity of this method for context-dependent enhancement of known medically or pharmacologically relevant weak analyte signals in linear-mode matrix-assisted laser desorption/ionization (MALDI) mass spectra has not been explored yet. Here, we investigate MALDI imaging datasets from mouse models of Alzheimer's disease and gastric cancer to systematically assess the importance of selecting the right number of random projections k and of principal components (PCs) L for reconstructing reproducibly denoised images after compression. We provide detailed quantitative data for comparison of RP-PCA-denoising with the Savitzky-Golay and wavelet-based denoising in these mouse models as a resource for the mass spectrometry imaging community. Most importantly, we demonstrate that RP-PCA preprocessing can enhance signals of low-intensity amyloid-β peptide isoforms such as Aβ1-26 even in sparsely distributed Alzheimer's β-amyloid plaques and that it enables enhanced imaging of multiply acetylated histone H4 isoforms in response to pharmacological histone deacetylase inhibition in vivo. We conclude that RP-PCA denoising may be a useful preprocessing step in biomarker discovery workflows.

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

PubMed Central

Choi, Se Y; Ahn, Seung H; Choi, Jae D; Kim, Jung H; Lee, Byoung-Il; Kim, Jeong-In

2016-01-01

Objective: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. Methods: A 5 × 5 × 5 mm3 uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current–time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5–7) and knowledge-based IMR (soft-tissue Levels 1–3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. Results: The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. Conclusion: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. Advances in knowledge: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients. PMID:26577542

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

3D segmentation of lung CT data with graph-cuts: analysis of parameter sensitivities

NASA Astrophysics Data System (ADS)

Cha, Jung won; Dunlap, Neal; Wang, Brian; Amini, Amir

2016-03-01

Lung boundary image segmentation is important for many tasks including for example in development of radiation treatment plans for subjects with thoracic malignancies. In this paper, we describe a method and parameter settings for accurate 3D lung boundary segmentation based on graph-cuts from X-ray CT data1. Even though previously several researchers have used graph-cuts for image segmentation, to date, no systematic studies have been performed regarding the range of parameter that give accurate results. The energy function in the graph-cuts algorithm requires 3 suitable parameter settings: K, a large constant for assigning seed points, c, the similarity coefficient for n-links, and λ, the terminal coefficient for t-links. We analyzed the parameter sensitivity with four lung data sets from subjects with lung cancer using error metrics. Large values of K created artifacts on segmented images, and relatively much larger value of c than the value of λ influenced the balance between the boundary term and the data term in the energy function, leading to unacceptable segmentation results. For a range of parameter settings, we performed 3D image segmentation, and in each case compared the results with the expert-delineated lung boundaries. We used simple 6-neighborhood systems for n-link in 3D. The 3D image segmentation took 10 minutes for a 512x512x118 ~ 512x512x190 lung CT image volume. Our results indicate that the graph-cuts algorithm was more sensitive to the K and λ parameter settings than to the C parameter and furthermore that amongst the range of parameters tested, K=5 and λ=0.5 yielded good results.

Estimation of object motion parameters from noisy images.

PubMed

Broida, T J; Chellappa, R

1986-01-01

An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.

An automatic segmentation method of a parameter-adaptive PCNN for medical images.

PubMed

Lian, Jing; Shi, Bin; Li, Mingcong; Nan, Ziwei; Ma, Yide

2017-09-01

Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision. The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter [Formula: see text] for different kinds of images. Secondly, we acquire the parameter [Formula: see text] according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset [Formula: see text] to improve initial segmentation precision. Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726. The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.

Review on the Celestial Sphere Positioning of FITS Format Image Based on WCS and Research on General Visualization

NASA Astrophysics Data System (ADS)

Song, W. M.; Fan, D. W.; Su, L. Y.; Cui, C. Z.

2017-11-01

Calculating the coordinate parameters recorded in the form of key/value pairs in FITS (Flexible Image Transport System) header is the key to determine FITS images' position in the celestial system. As a result, it has great significance in researching the general process of calculating the coordinate parameters. By combining CCD related parameters of astronomical telescope (such as field, focal length, and celestial coordinates in optical axis, etc.), astronomical images recognition algorithm, and WCS (World Coordinate System) theory, the parameters can be calculated effectively. CCD parameters determine the scope of star catalogue, so that they can be used to build a reference star catalogue by the corresponding celestial region of astronomical images; Star pattern recognition completes the matching between the astronomical image and reference star catalogue, and obtains a table with a certain number of stars between CCD plane coordinates and their celestial coordinates for comparison; According to different projection of the sphere to the plane, WCS can build different transfer functions between these two coordinates, and the astronomical position of image pixels can be determined by the table's data we have worked before. FITS images are used to carry out scientific data transmission and analyze as a kind of mainstream data format, but only to be viewed, edited, and analyzed in the professional astronomy software. It decides the limitation of popular science education in astronomy. The realization of a general image visualization method is significant. FITS is converted to PNG or JPEG images firstly. The coordinate parameters in the FITS header are converted to metadata in the form of AVM (Astronomy Visualization Metadata), and then the metadata is added to the PNG or JPEG header. This method can meet amateur astronomers' general needs of viewing and analyzing astronomical images in the non-astronomical software platform. The overall design flow is realized through the java program and tested by SExtractor, WorldWide Telescope, picture viewer, and other software.

Evaluation of Effective Parameters on Quality of Magnetic Resonance Imaging-computed Tomography Image Fusion in Head and Neck Tumors for Application in Treatment Planning.

PubMed

Shirvani, Atefeh; Jabbari, Keyvan; Amouheidari, Alireza

2017-01-01

In radiation therapy, computed tomography (CT) simulation is used for treatment planning to define the location of tumor. Magnetic resonance imaging (MRI)-CT image fusion leads to more efficient tumor contouring. This work tried to identify the practical issues for the combination of CT and MRI images in real clinical cases. The effect of various factors is evaluated on image fusion quality. In this study, the data of thirty patients with brain tumors were used for image fusion. The effect of several parameters on possibility and quality of image fusion was evaluated. These parameters include angles of the patient's head on the bed, slices thickness, slice gap, and height of the patient's head. According to the results, the first dominating factor on quality of image fusion was the difference slice gap between CT and MRI images (cor = 0.86, P < 0.005) and second factor was the angle between CT and MRI slice in the sagittal plane (cor = 0.75, P < 0.005). In 20% of patients, this angle was more than 28° and image fusion was not efficient. In 17% of patients, difference slice gap in CT and MRI was >4 cm and image fusion quality was <25%. The most important problem in image fusion is that MRI images are taken without regard to their use in treatment planning. In general, parameters related to the patient position during MRI imaging should be chosen to be consistent with CT images of the patient in terms of location and angle.

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.

Evaluation of image quality in terahertz pulsed imaging using test objects.

PubMed

Fitzgerald, A J; Berry, E; Miles, R E; Zinovev, N N; Smith, M A; Chamberlain, J M

2002-11-07

As with other imaging modalities, the performance of terahertz (THz) imaging systems is limited by factors of spatial resolution, contrast and noise. The purpose of this paper is to introduce test objects and image analysis methods to evaluate and compare THz image quality in a quantitative and objective way, so that alternative terahertz imaging system configurations and acquisition techniques can be compared, and the range of image parameters can be assessed. Two test objects were designed and manufactured, one to determine the modulation transfer functions (MTF) and the other to derive image signal to noise ratio (SNR) at a range of contrasts. As expected the higher THz frequencies had larger MTFs, and better spatial resolution as determined by the spatial frequency at which the MTF dropped below the 20% threshold. Image SNR was compared for time domain and frequency domain image parameters and time delay based images consistently demonstrated higher SNR than intensity based parameters such as relative transmittance because the latter are more strongly affected by the sources of noise in the THz system such as laser fluctuations and detector shot noise.

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

An improved method to estimate reflectance parameters for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Li, Shiying; Deguchi, Koichiro; Li, Renfa; Manabe, Yoshitsugu; Chihara, Kunihiro

2008-01-01

Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

SU-F-J-157: Effect of Contouring Uncertainty in Post Implant Dosimetry of Low-Dose-Rate Prostate Permanent Seed Brachytherapy

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

Mashouf, S; Merino, T; Ravi, A

Purpose: There is strong evidence relating post-implant dosimetry for low-dose-rate (LDR) prostate seed brachytherapy to local control rates. The delineation of the prostate on CT images, however, represents a challenge due to the lack of soft tissue contrast in order to identify the prostate borders. This study aims at quantifying the sensitivity of clinically relevant dosimetric parameters to uncertainty in the contouring of prostate. Methods: CT images, post-op plans and contours of a cohort of patients (n=43) (low risk=55.8%, intermediate risk=39.5%, high risk=4.7%), who had received prostate seed brachytherapy, were imported into MIM Symphony treatment planning system. The prostate contoursmore » in post-implant CT images were expanded/contracted uniformly for margins of ±1.00 mm, ±2.00 mm, ±3.00 mm, ±4.00 mm and ±5.00 mm. The values for V100 and D90 were extracted from Dose Volume Histograms for each contour and compared. Results: Significant changes were observed in the values of D90 and V100 as well as the number of suboptimal plans for expansion or contraction margins of only few millimeters. Evaluation of coverage based on D90 was found to be less sensitive to expansion errors compared to V100. D90 led to a lower number of implants incorrectly identified with insufficient coverage for expanded contours which increases the accuracy of post-implant QA using CT images compared to V100. Conclusion: In order to establish a successful post implant QA for LDR prostate seed brachytherapy, it is necessary to identify the low and high thresholds of important dose metrics of the target volume such as D90 and V100. Since these parameters are sensitive to target volume definition, accurate identification of prostate borders would help to improve accuracy and predictive value of the post-implant QA process. In this respect, use of imaging modalities such as MRI where prostate is well delineated should prove useful.« less

Significance of the impact of motion compensation on the variability of PET image features

NASA Astrophysics Data System (ADS)

Carles, M.; Bach, T.; Torres-Espallardo, I.; Baltas, D.; Nestle, U.; Martí-Bonmatí, L.

2018-03-01

In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40% of SUVmax and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40% contours, despite the values not being interchangeable, all image features showed strong linear correlations (r  >  0.91, p\\ll 0.001 ). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the compensation of tumor motion did not have a significant impact on the quantitative PET parameters. The variability of PET parameters due to voxel size in image reconstruction was more significant than variability due to voxel size in image post-resampling. In conclusion, most of the parameters (apart from the contrast of neighborhood matrix) were robust to the motion compensation implied by 4D-PET/CT. The impact on parameter variability due to the voxel size in image reconstruction and in image post-resampling could not be assumed to be equivalent.

A new method for the automatic retrieval of medical cases based on the RadLex ontology.

PubMed

Spanier, A B; Cohen, D; Joskowicz, L

2017-03-01

The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision-making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and textual information on the anatomy and pathology findings. The textual information, when available in standardized terminology, e.g., the RadLex ontology, and used in conjunction with the radiological images, provides a substantial advantage for M-CBIR systems. We present a new method for incorporating textual radiological findings from medical case reports in M-CBIR. The input is a database of medical cases, a query case, and the number of desired relevant cases. The output is an ordered list of the most relevant cases in the database. The method is based on a new case formulation, the Augmented RadLex Graph and an Anatomy-Pathology List. It uses a new case relatedness metric [Formula: see text] that prioritizes more specific medical terms in the RadLex tree over less specific ones and that incorporates the length of the query case. An experimental study on 8 CT queries from the 2015 VISCERAL 3D Case Retrieval Challenge database consisting of 1497 volumetric CT scans shows that our method has accuracy rates of 82 and 70% on the first 10 and 30 most relevant cases, respectively, thereby outperforming six other methods. The increasing amount of medical imaging data acquired in clinical practice constitutes a vast database of untapped diagnostically relevant information. This paper presents a new hybrid approach to retrieving the most relevant medical cases based on textual and image information.

Image parameters for maturity determination of a composted material containing sewage sludge

NASA Astrophysics Data System (ADS)

Kujawa, S.; Nowakowski, K.; Tomczak, R. J.; Boniecki, P.; Dach, J.

2013-07-01

Composting is one of the best methods for management of sewage sludge. In a reasonably conducted composting process it is important to early identify the moment in which a material reaches the young compost stage. The objective of this study was to determine parameters contained in images of composted material's samples that can be used for evaluation of the degree of compost maturity. The study focused on two types of compost: containing sewage sludge with corn straw and sewage sludge with rapeseed straw. The photographing of the samples was carried out on a prepared stand for the image acquisition using VIS, UV-A and mixed (VIS + UV-A) light. In the case of UV-A light, three values of the exposure time were assumed. The values of 46 parameters were estimated for each of the images extracted from the photographs of the composted material's samples. Exemplary averaged values of selected parameters obtained from the images of the composted material in the following sampling days were presented. All of the parameters obtained from the composted material's images are the basis for preparation of training, validation and test data sets necessary in development of neural models for classification of the young compost stage.

SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

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

Morris, R; Lakshmanan, M; Fong, G

Purpose: Coherent scatter based imaging has shown improved contrast and molecular specificity over conventional digital mammography however the biological risks have not been quantified due to a lack of accurate information on absorbed dose. This study intends to characterize the dose distribution and average glandular dose from coded aperture coherent scatter spectral imaging of the breast. The dose deposited in the breast from this new diagnostic imaging modality has not yet been quantitatively evaluated. Here, various digitized anthropomorphic phantoms are tested in a Monte Carlo simulation to evaluate the absorbed dose distribution and average glandular dose using clinically feasible scanmore » protocols. Methods: Geant4 Monte Carlo radiation transport simulation software is used to replicate the coded aperture coherent scatter spectral imaging system. Energy sensitive, photon counting detectors are used to characterize the x-ray beam spectra for various imaging protocols. This input spectra is cross-validated with the results from XSPECT, a commercially available application that yields x-ray tube specific spectra for the operating parameters employed. XSPECT is also used to determine the appropriate number of photons emitted per mAs of tube current at a given kVp tube potential. With the implementation of the XCAT digital anthropomorphic breast phantom library, a variety of breast sizes with differing anatomical structure are evaluated. Simulations were performed with and without compression of the breast for dose comparison. Results: Through the Monte Carlo evaluation of a diverse population of breast types imaged under real-world scan conditions, a clinically relevant average glandular dose for this new imaging modality is extrapolated. Conclusion: With access to the physical coherent scatter imaging system used in the simulation, the results of this Monte Carlo study may be used to directly influence the future development of the modality to keep breast dose to a minimum while still maintaining clinically viable image quality.« less

Regularization of soft-X-ray imaging in the DIII-D tokamak

DOE PAGES

Wingen, A.; Shafer, M. W.; Unterberg, E. A.; ...

2015-03-02

We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\\it L-curve} method to find the optimum regularization parameter is outlined. A representative testmore » image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.« less

The Influence of Social Comparison on Visual Representation of One's Face

PubMed Central

Zell, Ethan; Balcetis, Emily

2012-01-01

Can the effects of social comparison extend beyond explicit evaluation to visual self-representation—a perceptual stimulus that is objectively verifiable, unambiguous, and frequently updated? We morphed images of participants' faces with attractive and unattractive references. With access to a mirror, participants selected the morphed image they perceived as depicting their face. Participants who engaged in upward comparison with relevant attractive targets selected a less attractive morph compared to participants exposed to control images (Study 1). After downward comparison with relevant unattractive targets compared to control images, participants selected a more attractive morph (Study 2). Biased representations were not the products of cognitive accessibility of beauty constructs; comparisons did not influence representations of strangers' faces (Study 3). We discuss implications for vision, social comparison, and body image. PMID:22662124

Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT.

PubMed

Ferrario, Damien; Grychtol, Bartłomiej; Adler, Andy; Solà, Josep; Böhm, Stephan H; Bodenstein, Marc

2012-11-01

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the ability of EIT technology to reconstruct relevant impedance changes at their anatomical locations, provided that information about the thoracic boundary shape (and electrode positions) are used for reconstruction.

Reconnaissance of the β Pictoris system down to 1.75 AU with the L' - b and vector vortex coronagraph on VLT/NACO

NASA Astrophysics Data System (ADS)

Milli, J.; Absil, O.; Mawet, D.; Lagrange, A.-M.

2013-09-01

High contrast imaging has thoroughly combed through the limited parameter space accessible with first-generation ground-based adaptive optics instruments and the HST. Only a few objects were discovered, and many non-detections reported and statistically interpreted. The field is now in need of a technological breakthrough. We aim at opening a new parameter space with first-generation systems such as NACO at the Very Large Telescope, by providing ground-breaking inner working angle (IWA) capabilities in the L' band. This mid-infrared wavelength range is a sweet spot for high contrast coronagraphy since the planets-to-star brightness ratio is favorable, while Strehl ratio is naturally higher. An annular groove phase mask (AGPM) vector vortex coronagraph optimized for the L' band, made out of diamond subwavelength gratings has been manufactured and qualified in the lab. The AGPM enables high contrast imaging at very small IWA (here 0".09), potentially being the key to a new parameter space. Here we present the results of the installation and successful commissioning of an L'- band AGPM on VLT/NACO. During a recent science verification run, we imaged the inner regions of Beta Pictoris down to the previously unexplored projected radius of 1.75 AU with unprecedented point source sensitivity. The disk was also clearly resolved down to its inner truncation . The new NACO mode is an opportunity to introduce a more rigorous framework for deriving detection limits at very small angles, which is also relevant for SPHERE and GPI and every high contrast imaging instrument with small IWA ambitions. Indeed, classical tools assuming Gaussian statistics, perfectly valid at large separations, loose significance close to the center simply because the sample size decreases dramatically (fewer resolution elements at a given radius). Moreover, the probability density function (PDF) of speckle noise and associated confidence level for detection depend on radius. ADI was shown to transform speckles'modified Rician PDF into quasi-Gaussian PDF at large separations, but it is expected that this property of ADI does not hold true at small angles. Finally, the flux attenuation induced by ADI, potentially significant at small angles, does not scale linearly with the companion brightness, which makes its calibration more difficult.

Photoacoustic microscopy imaging for microneedle drug delivery

NASA Astrophysics Data System (ADS)

Moothanchery, Mohesh; Seeni, Razina Z.; Xu, Chenjie; Pramanik, Manojit

2018-02-01

The recent development of novel transdermal drug delivery systems (TDDS) using microneedle technology allows micron-sized conduits to be formed within the outermost skin layers attracting keen interest in skin as an interface for localized and systemic delivery of therapeutics. In light of this, researchers are using microneedles as tools to deliver nanoparticle formulations to targeted sites for effective therapy. However, in such studies the use of traditional histological methods are employed for characterization and do not allow for the in vivo visualization of drug delivery mechanism. Hence, this study presents a novel imaging technology to characterize microneedle based nanoparticle delivery systems using optical resolution-photoacoustic microscopy (OR-PAM). In this study in vivo transdermal delivery of gold nanoparticles using microneedles in mice ear and the spatial distribution of the nanoparticles in the tissue was successfully illustrated. Characterization of parameters that are relevant in drug delivery studies such as penetration depth, efficiency of delivered gold nanoparticles were monitored using the system. Photoacoustic microscopy proves an ideal tool for the characterization studies of microneedle properties and the studies shows microneedles as an ideal tool for precise and controlled drug delivery.

A novel concept for smart trepanation.

PubMed

Follmann, Axel; Korff, Alexander; Fuertjes, Tobias; Kunze, Sandra C; Schmieder, Kirsten; Radermacher, Klaus

2012-01-01

Trepanation of the skull is a common procedure in craniofacial and neurosurgical interventions, allowing access to the innermost cranial structures. Despite a careful advancement, injury of the dura mater represents a frequent complication during these cranial openings. The technology of computer-assisted surgery offers different support systems such as navigated tools and surgical robots. This article presents a novel technical approach toward an image- and sensor-based synergistic control of the cutting depth of a manually guided soft-tissue-preserving saw. Feasibility studies in a laboratory setup modeling relevant skull tissue parameters demonstrate that errors due to computed tomography or magnetic resonance image segmentation and registration, optical tracking, and mechanical tolerances of up to 2.5 mm, imminent to many computer-assisted surgery systems, can be compensated for by the cutting tool characteristics without damaging the dura. In conclusion, the feasibility of a computer-controlled trepanation system providing a safer and efficient trepanation has been demonstrated. Injuries of the dura mater can be avoided, and the bone cutting gap can be reduced to 0.5 mm with potential benefits for the reintegration of the bone flap.

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Imaging Mass Spectrometry (MALDI-TOF IMS) for Premalignant Gastrointestinal Lesions

PubMed Central

Ko, Kwang Hyun; Kwon, Chang Il; Park, So Hye; Han, Na Young; Lee, Hoo Keun; Kim, Eun Hee

2013-01-01

Imaging mass spectrometry (IMS) is currently receiving large attention from the mass spectrometric community, although its use is not yet well known in the clinic. As matrix-assisted laser desorption/ionization time-of-flight (MALDI)-IMS can show the biomolecular changes in cells as well as tissues, it can be an ideal tool for biomedical diagnostics as well as the molecular diagnosis of clinical specimens, especially aimed at the prompt detection of premalignant lesions much earlier before overt mass formation, or for obtaining histologic clues from endoscopic biopsy. Besides its use for pathologic diagnosis, MALDI-IMS is also a powerful tool for the detection and localization of drugs, proteins, and lipids in tissue. Measurement of parameters that define and control the implications, challenges, and opportunities associated with the application of IMS to biomedical tissue studies might be feasible through a deep understanding of mass spectrometry. In this focused review series, new insights into the molecular processes relevant to IMS as well as other field applications are introduced. PMID:24340253

Evaluation of Synthetic Self-Oscillating Models of the Vocal Folds

NASA Astrophysics Data System (ADS)

Hubler, Elizabeth P.; Weiland, Kelley S.; Hancock, Adrienne B.; Plesniak, Michael W.

2013-11-01

Approximately 30% of people will suffer from a voice disorder at some point in their lives. The probability doubles for those who rely heavily on their voice, such as teachers and singers. Synthetic vocal fold (VF) models are fabricated and evaluated experimentally in a vocal tract simulator to replicate physiological conditions. Pressure measurements are acquired along the vocal tract and high-speed images are captured at varying flow rates during VF oscillation to facilitate understanding of the characteristics of healthy and damaged VFs. The images are analyzed using a videokymography line-scan technique that has been used to examine VF motion and mucosal wave dynamics in vivo. Clinically relevant parameters calculated from the volume-velocity output of a circumferentially-vented mask (Rothenberg mask) are compared to patient data. This study integrates speech science with engineering and flow physics to overcome current limitations of synthetic VF models to properly replicate normal phonation in order to advance the understanding of resulting flow features, progression of pathological conditions, and medical techniques. Supported by the GW Institute for Biomedical Engineering (GWIBE) and GW Center for Biomimetics and Bioinspired Engineering (COBRE).

Magnetic Resonance Poroelastography: An Algorithm for Estimating the Mechanical Properties of Fluid-Saturated Soft Tissues

PubMed Central

Perriñez, Phillip R.; Kennedy, Francis E.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.

2010-01-01

Magnetic Resonance Poroelastography (MRPE) is introduced as an alternative to single-phase model-based elastographic reconstruction methods. A three-dimensional (3D) finite element poroelastic inversion algorithm was developed to recover the mechanical properties of fluid-saturated tissues. The performance of this algorithm was assessed through a variety of numerical experiments, using synthetic data to probe its stability and sensitivity to the relevant model parameters. Preliminary results suggest the algorithm is robust in the presence of noise and capable of producing accurate assessments of the underlying mechanical properties in simulated phantoms. Further, a 3D time-harmonic motion field was recorded for a poroelastic phantom containing a single cylindrical inclusion and used to assess the feasibility of MRPE image reconstruction from experimental data. The elastograms obtained from the proposed poroelastic algorithm demonstrate significant improvement over linearly elastic MRE images generated using the same data. In addition, MRPE offers the opportunity to estimate the time-harmonic pressure field resulting from tissue excitation, highlighting the potential for its application in the diagnosis and monitoring of disease processes associated with changes in interstitial pressure. PMID:20199912

Regulatory perspectives and research activities at the FDA on the use of phantoms with in vivo diagnostic devices

NASA Astrophysics Data System (ADS)

Agrawal, Anant; Gavrielides, Marios A.; Weininger, Sandy; Chakrabarti, Kish; Pfefer, Joshua

2008-02-01

For a number of years, phantoms have been used to optimize device parameters and validate performance in the primary medical imaging modalities (CT, MRI, PET/SPECT, ultrasound). Furthermore, the FDA under the Mammography Quality Standards Act (MQSA) requires image quality evaluation of mammography systems using FDA-approved phantoms. The oldest quantitative optical diagnostic technology, pulse oximetry, also benefits from the use of active phantoms known as patient simulators to validate certain performance characteristics under different clinically-relevant conditions. As such, guidance provided by the FDA to its staff and to industry on the contents of pre-market notification and approval submissions includes suggestions on how to incorporate the appropriate phantoms in establishing device effectiveness. Research at the FDA supports regulatory statements on the use of phantoms by investigating how phantoms can be designed, characterized, and utilized to determine critical device performance characteristics. These examples provide a model for how novel techniques in the rapidly growing field of optical diagnostics can use phantoms during pre- and post-market regulatory testing.

Multi-temporal MRI carpal bone volumes analysis by principal axes registration

NASA Astrophysics Data System (ADS)

Ferretti, Roberta; Dellepiane, Silvana

2016-03-01

In this paper, a principal axes registration technique is presented, with the relevant application to segmented volumes. The purpose of the proposed registration is to compare multi-temporal volumes of carpal bones from Magnetic Resonance Imaging (MRI) acquisitions. Starting from the study of the second-order moment matrix, the eigenvectors are calculated to allow the rotation of volumes with respect to reference axes. Then the volumes are spatially translated to become perfectly overlapped. A quantitative evaluation of the results obtained is carried out by computing classical indices from the confusion matrix, which depict similarity measures between the volumes of the same organ as extracted from MRI acquisitions executed at different moments. Within the medical field, the way a registration can be used to compare multi-temporal images is of great interest, since it provides the physician with a tool which allows a visual monitoring of a disease evolution. The segmentation method used herein is based on the graph theory and is a robust, unsupervised and parameters independent method. Patients affected by rheumatic diseases have been considered.

Single-molecule spectroscopic methods.

PubMed

Haustein, Elke; Schwille, Petra

2004-10-01

Being praised for the mere fact of enabling the detection of individual fluorophores a dozen years ago, single-molecule techniques nowadays represent standard methods for the elucidation of the structural rearrangements of biologically relevant macromolecules. Single-molecule-sensitive techniques, such as fluorescence correlation spectroscopy, allow real-time access to a multitude of molecular parameters (e.g. diffusion coefficients, concentration and molecular interactions). As a result of various recent advances, this technique shows promise even for intracellular applications. Fluorescence imaging can reveal the spatial localization of fluorophores on nanometer length scales, whereas fluorescence resonance energy transfer supports a wide range of different applications, including real-time monitoring of conformational rearrangements (as in protein folding). Still in their infancy, single-molecule spectroscopic methods thus provide unprecedented insights into basic molecular mechanisms. Copyright 2004 Elsevier Ltd.

Perspectives on Porous Media MR in Clinical MRI

NASA Astrophysics Data System (ADS)

Sigmund, E. E.

2011-03-01

Many goals and challenges of research in natural or synthetic porous media are mirrored in quantitative medical MRI. This review will describe examples where MR techniques used in porous media (particularly diffusion-weighted imaging (DWI)) are applied to physiological pathologies. Tissue microstructure is one area with great overlap with porous media science. Diffusion-weighting (esp. in neurological tissue) has motivated models with explicit physical dimensions, statistical parameters, empirical descriptors, or hybrids thereof. Another clinically relevant microscopic process is active flow. Renal (kidney) tissue possesses significant active vascular / tubular transport that manifests as "pseudodiffusion." Cancerous lesions involve anomalies in both structure and flow. The tools of magnetic resonance and their interpretation in porous media has had great impact on clinical MRI, and continued cross-fertilization of ideas can only enhance the progress of both fields.

Effect of gradient pulse duration on MRI estimation of the diffusional kurtosis for a two-compartment exchange model

NASA Astrophysics Data System (ADS)

Jensen, Jens H.; Helpern, Joseph A.

2011-06-01

Hardware constraints typically require the use of extended gradient pulse durations for clinical applications of diffusion-weighted magnetic resonance imaging (DW-MRI), which can potentially influence the estimation of diffusion metrics. Prior studies have examined this effect for the apparent diffusion coefficient. This study employs a two-compartment exchange model in order to assess the gradient pulse duration sensitivity of the apparent diffusional kurtosis (ADK), a quantitative index of diffusional non-Gaussianity. An analytic expression is derived and numerically evaluated for parameter ranges relevant to DW-MRI of brain. It is found that the ADK differs from the true diffusional kurtosis by at most a few percent. This suggests that ADK estimates for brain may be robust with respect to changes in pulse gradient duration.

New developments in short-pulse eye safe lasers pay the way for future LADARs and 3D mapping performances

NASA Astrophysics Data System (ADS)

Pasmanik, Guerman; Latone, Kevin; Shilov, Alex; Shklovsky, Eugeni; Spiro, Alex; Tiour, Larissa

2005-06-01

We have demonstrated that direct excitation of 3rd Stokes Raman emission in crystal can produce short (few nanosecond) eye-safe pulses. Produced beam has very high quality and the pulse energy can be as high as tens of millijoules. For pulsed diode pumped solid state lasers the demonstrated repetition rate was 250 Hz but higher repetition rates are certainly achievable. It is important that tested schemes do not have strict requirements on laser pump parameters, namely beam divergence and frequency bandwidth. The obtained results are very relevant to the development of eye-safe lasers, such as the new generation of rangefinders, target designators, and laser tracking and pin-pointing devices, as well as remote 2D and 3D imaging systems.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Efficient robust conditional random fields.

PubMed

Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

2015-10-01

Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

OCT imaging of craniofacial anatomy in xenopus embryos (Conference Presentation)

NASA Astrophysics Data System (ADS)

Deniz, Engin; Jonas, Stephan M.; Griffin, John; Hooper, Michael C.; Choma, Michael A.; Khokha, Mustafa K.

2016-03-01

The etiology of craniofacial defects is incompletely understood. The ability to obtain large amounts of gene sequence data from families affected by craniofacial defects is opening up new ways to understand molecular genetic etiological factors. One important link between gene sequence data and clinical relevance is biological research into candidate genes and molecular pathways. We present our recent research using OCT as a nondestructive phenotyping modality of craniofacial morphology in Xenopus embryos, an important animal model for biological research in gene and pathway discovery. We define 2D and 3D scanning protocols for a standardized approach to craniofacial imaging in Xenopus embryos. We define standard views and planar reconstructions for visualizing normal anatomy and landmarks. We compare these views and reconstructions to traditional histopathology using alcian blue staining. In addition to being 3D, nondestructive, and having much faster throughout, OCT can identify craniofacial features that are lost during traditional histopathological preparation. We also identify quantitative morphometric parameters to define normative craniofacial anatomy. We also note that craniofacial and cardiac defects are not infrequently present in the same patient (e.g velocardiofacial syndrome). Given that OCT excels at certain aspects of cardiac imaging in Xenopus embryos, our work highlights the potential of using OCT and Xenopus to study molecular genetic factors that impact both cardiac and craniofacial development.

Three-dimensional analysis of implanted magnetic-resonance-visible meshes.

PubMed

Sindhwani, Nikhil; Feola, Andrew; De Keyzer, Frederik; Claus, Filip; Callewaert, Geertje; Urbankova, Iva; Ourselin, Sebastien; D'hooge, Jan; Deprest, Jan

2015-10-01

Our primary objective was to develop relevant algorithms for quantification of mesh position and 3D shape in magnetic resonance (MR) images. In this proof-of-principle study, one patient with severe anterior vaginal wall prolapse was implanted with an MR-visible mesh. High-resolution MR images of the pelvis were acquired 6 weeks and 8 months postsurgery. 3D models were created using semiautomatic segmentation techniques. Conformational changes were recorded quantitatively using part-comparison analysis. An ellipticity measure is proposed to record longitudinal conformational changes in the mesh arms. The surface that is the effective reinforcement provided by the mesh is calculated using a novel methodology. The area of this surface is the effective support area (ESA). MR-visible mesh was clearly outlined in the images, which allowed us to longitudinally quantify mesh configuration between 6 weeks and 8 months after implantation. No significant changes were found in mesh position, effective support area, conformation of the mesh's main body, and arm length during the period of observation. Ellipticity profiles show longitudinal conformational changes in posterior arms. This paper proposes novel methodologies for a systematic 3D assessment of the position and morphology of MR-visible meshes. A novel semiautomatic tool was developed to calculate the effective area of support provided by the mesh, a potentially clinically important parameter.

[Recent advances in newborn MRI].

PubMed

Morel, B; Hornoy, P; Husson, B; Bloch, I; Adamsbaum, C

2014-07-01

The accurate morphological exploration of the brain is a major challenge in neonatology that advances in magnetic resonance imaging (MRI) can now provide. MRI is the gold standard if an hypoxic ischemic pathology is suspected in a full term neonate. In prematures, the specific role of MRI remains to be defined, secondary to US in any case. We present a state of the art of hardware and software technical developments in MRI. The increase in magnetic field strength (3 tesla) and the emergence of new MRI sequences provide access to new information. They both have positive and negative consequences on the daily clinical data acquisition use. The semiology of brain imaging in full term newborns and prematures is more extensive and complex and thereby more difficult to interpret. The segmentation of different brain structures in the newborn, even very premature, is now available. It is now possible to dissociate the cortex and basal ganglia from the cerebral white matter, to calculate the volume of anatomical structures, which improves the morphometric quantification and the understanding of the normal and abnormal brain development. MRI is a powerful tool to analyze the neonatal brain. The relevance of the diagnostic contribution requires an adaptation of the parameters of the sequences to acquire and of the image processing methods. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Quantitative photoacoustic imaging in the acoustic regime using SPIM

NASA Astrophysics Data System (ADS)

Beigl, Alexander; Elbau, Peter; Sadiq, Kamran; Scherzer, Otmar

2018-05-01

While in standard photoacoustic imaging the propagation of sound waves is modeled by the standard wave equation, our approach is based on a generalized wave equation with variable sound speed and material density, respectively. In this paper we present an approach for photoacoustic imaging, which in addition to the recovery of the absorption density parameter, the imaging parameter of standard photoacoustics, also allows us to reconstruct the spatially varying sound speed and density, respectively, of the medium. We provide analytical reconstruction formulas for all three parameters based in a linearized model based on single plane illumination microscopy (SPIM) techniques.

Novel image encryption algorithm based on multiple-parameter discrete fractional random transform

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Dong, Taiji; Wu, Jianhua

2010-08-01

A new method of digital image encryption is presented by utilizing a new multiple-parameter discrete fractional random transform. Image encryption and decryption are performed based on the index additivity and multiple parameters of the multiple-parameter fractional random transform. The plaintext and ciphertext are respectively in the spatial domain and in the fractional domain determined by the encryption keys. The proposed algorithm can resist statistic analyses effectively. The computer simulation results show that the proposed encryption algorithm is sensitive to the multiple keys, and that it has considerable robustness, noise immunity and security.

Collection Fusion Using Bayesian Estimation of a Linear Regression Model in Image Databases on the Web.

ERIC Educational Resources Information Center

Kim, Deok-Hwan; Chung, Chin-Wan

2003-01-01

Discusses the collection fusion problem of image databases, concerned with retrieving relevant images by content based retrieval from image databases distributed on the Web. Focuses on a metaserver which selects image databases supporting similarity measures and proposes a new algorithm which exploits a probabilistic technique using Bayesian…

But what about the Empress of Racnoss? The allocation of attention to spiders and Doctor Who in a visual search task is predicted by fear and expertise.

PubMed

Purkis, Helena M; Lester, Kathryn J; Field, Andy P

2011-12-01

If there is a spider in the room, then the spider phobic in your group is most likely to point it out to you. This phenomenon is believed to arise because our attentional systems are hardwired to attend to threat in our environment, and, to a spider phobic, spiders are threatening. However, an alternative explanation is simply that attention is quickly drawn to the stimulus of most personal relevance in the environment. Our research examined whether positive stimuli with no biological or evolutionary relevance could be allocated preferential attention. We compared attention to pictures of spiders with pictures from the TV program Doctor Who, for people who varied in both their love of Doctor Who and their fear of spiders. We found a double dissociation: interference from spider and Doctor-Who-related images in a visual search task was predicted by spider fear and Doctor Who expertise, respectively. As such, allocation of attention reflected the personal relevance of the images rather than their threat content. The attentional system believed to have a causal role in anxiety disorders is therefore likely to be a general system that responds not to threat but to stimulus relevance; hence, nonevolutionary images, such as those from Doctor Who, captured attention as quickly as fear-relevant spider images. Where this leaves the Empress of Racnoss, we are unsure. (c) 2011 APA, all rights reserved.

Three-dimensional biofilm structure quantification.

PubMed

Beyenal, Haluk; Donovan, Conrad; Lewandowski, Zbigniew; Harkin, Gary

2004-12-01

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Calibration of imaging parameters for space-borne airglow photography using city light positions

NASA Astrophysics Data System (ADS)

Hozumi, Yuta; Saito, Akinori; Ejiri, Mitsumu K.

2016-09-01

A new method for calibrating imaging parameters of photographs taken from the International Space Station (ISS) is presented in this report. Airglow in the mesosphere and the F-region ionosphere was captured on the limb of the Earth with a digital single-lens reflex camera from the ISS by astronauts. To utilize the photographs as scientific data, imaging parameters, such as the angle of view, exact position, and orientation of the camera, should be determined because they are not measured at the time of imaging. A new calibration method using city light positions shown in the photographs was developed to determine these imaging parameters with high accuracy suitable for airglow study. Applying the pinhole camera model, the apparent city light positions on the photograph are matched with the actual city light locations on Earth, which are derived from the global nighttime stable light map data obtained by the Defense Meteorological Satellite Program satellite. The correct imaging parameters are determined in an iterative process by matching the apparent positions on the image with the actual city light locations. We applied this calibration method to photographs taken on August 26, 2014, and confirmed that the result is correct. The precision of the calibration was evaluated by comparing the results from six different photographs with the same imaging parameters. The precisions in determining the camera position and orientation are estimated to be ±2.2 km and ±0.08°, respectively. The 0.08° difference in the orientation yields a 2.9-km difference at a tangential point of 90 km in altitude. The airglow structures in the photographs were mapped to geographical points using the calibrated imaging parameters and compared with a simultaneous observation by the Visible and near-Infrared Spectral Imager of the Ionosphere, Mesosphere, Upper Atmosphere, and Plasmasphere mapping mission installed on the ISS. The comparison shows good agreements and supports the validity of the calibration. This calibration technique makes it possible to utilize photographs taken on low-Earth-orbit satellites in the nighttime as a reference for the airglow and aurora structures.[Figure not available: see fulltext.

Novel methods for parameter-based analysis of myocardial tissue in MR images

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Behrens, S.; Kuehnel, C.; Oeltze, S.; Konrad, O.; Peitgen, H.-O.

2007-03-01

The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.

Stress distribution and topography of Tellus Regio, Venus

NASA Technical Reports Server (NTRS)

Williams, David R.; Greeley, Ronald

1989-01-01

The Tellus Regio area of Venus represents a subset of a narrow latitude band where Pioneer Venus Orbiter (PVO) altimetry data, line-of-sight (LOS) gravity data, and Venera 15/16 radar images have all been obtained with good resolution. Tellus Regio also has a wide variety of surface morphologic features, elevations ranging up to 2.5 km, and a relatively low LOS gravity anomaly. This area was therefore chosen in order to examine the theoretical stress distributions resulting from various models of compensation of the observed topography. These surface stress distributions are then compared with the surface morphology revealed in the Venera 15/16 radar images. Conclusions drawn from these comparisons will enable constraints to be put on various tectonic parameters relevant to Tellus Regio. The stress distribution is calculated as a function of the topography, the equipotential anomaly, and the assumed model parameters. The topography data is obtained from the PVO altimetry. The equipotential anomaly is estimated from the PVO LOS gravity data. The PVO LOS gravity represents the spacecraft accelerations due to mass anomalies within the planet. These accelerations are measured at various altitudes and angles to the local vertical and therefore do not lend themselves to a straightforward conversion. A minimum variance estimator of the LOS gravity data is calculated, taking into account the various spacecraft altitudes and LOS angles and using the measured PVO topography as an a priori constraint. This results in an estimated equivalent surface mass distribution, from which the equipotential anomaly is determined.

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine

PubMed Central

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-01-01

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants. PMID:27120600

Changes in the Frontotemporal Cortex and Cognitive Correlates in First-Episode Psychosis

PubMed Central

Gutiérrez-Galve, Leticia; Wheeler-Kingshott, Claudia A.M.; Altmann, Daniel R.; Price, Gary; Chu, Elvina M.; Leeson, Verity C.; Lobo, Antonio; Barker, Gareth J.; Barnes, Thomas R.E.; Joyce, Eileen M.; Ron, María A.

2010-01-01

Background Loss of cortical volume in frontotemporal regions has been reported in patients with schizophrenia and their relatives. Cortical area and thickness are determined by different genetic processes, and measuring these parameters separately may clarify disturbances in corticogenesis relevant to schizophrenia. Our study also explored clinical and cognitive correlates of these parameters. Methods Thirty-seven patients with first-episode psychosis (34 schizophrenia, 3 schizoaffective disorder) and 38 healthy control subjects matched for age and sex took part in the study. Imaging was performed on an magnetic resonance imaging 1.5-T scanner. Area and thickness of the frontotemporal cortex were measured using a surface-based morphometry method (Freesurfer). All subjects underwent neuropsychologic testing that included measures of premorbid and current IQ, working and verbal memory, and executive function. Results Reductions in cortical area, more marked in the temporal cortex, were present in patients. Overall frontotemporal cortical thickness did not differ between groups, although regional thinning of the right superior temporal region was observed in patients. There was a significant association of both premorbid IQ and IQ at disease onset with area, but not thickness, of the frontotemporal cortex, and working memory span was associated with area of the frontal cortex. These associations remained significant when only patients with schizophrenia were considered. Conclusions Our results suggest an early disruption of corticogenesis in schizophrenia, although the effect of subsequent environmental factors cannot be excluded. In addition, cortical abnormalities are subject to regional variations and differ from those present in neurodegenerative diseases. PMID:20452574

TAMEE: data management and analysis for tissue microarrays.

PubMed

Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

2007-03-07

With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from http://genome.tugraz.at/Software/TAMEE.

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine.

PubMed

De Bei, Roberta; Fuentes, Sigfredo; Gilliham, Matthew; Tyerman, Steve; Edwards, Everard; Bianchini, Nicolò; Smith, Jason; Collins, Cassandra

2016-04-23

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.

Magnetic Resonance Imaging of Electrolysis.

PubMed Central

Meir, Arie; Hjouj, Mohammad; Rubinsky, Liel; Rubinsky, Boris

2015-01-01

This study explores the hypothesis that Magnetic Resonance Imaging (MRI) can image the process of electrolysis by detecting pH fronts. The study has relevance to real time control of cell ablation with electrolysis. To investigate the hypothesis we compare the following MR imaging sequences: T1 weighted, T2 weighted and Proton Density (PD), with optical images acquired using pH-sensitive dyes embedded in a physiological saline agar solution phantom treated with electrolysis and discrete measurements with a pH microprobe. We further demonstrate the biological relevance of our work using a bacterial E. Coli model, grown on the phantom. The results demonstrate the ability of MRI to image electrolysis produced pH changes in a physiological saline phantom and show that these changes correlate with cell death in the E. Coli model grown on the phantom. The results are promising and invite further experimental research. PMID:25659942