1. Articles from david l. wilson

    1-25 of 25
    1. Fully automated plaque characterization in intravascular OCT images using hybrid convolutional and lumen morphology features

      Fully automated plaque characterization in intravascular OCT images using hybrid convolutional and lumen morphology features

      For intravascular OCT (IVOCT) images, we developed an automated atherosclerotic plaque characterization method that used a hybrid learning approach, which combined deep-learning convolutional and hand-crafted, lumen morphological features. Processing was done on innate A-line units with labels fibrolipidic (fibrous tissue followed by lipidous tissue), fibrocalcific (fibrous tissue followed by calcification), or other. We trained/tested on an expansive data set (6,556 images), and performed an active learning, relabeling step to improve noisy ground truth labels. Conditional random field was an important post-processing step to reduce classification errors. Sensitivities/specificities were 84.8%/97.8% and 91.4%/95.7 ...

      Read Full Article
    2. Application and Evaluation of Highly Automated Software for Comprehensive Stent Analysis in Intravascular Optical Coherence Tomography

      Application and Evaluation of Highly Automated Software for Comprehensive Stent Analysis in Intravascular Optical Coherence Tomography

      Intravascular optical coherence tomography (IVOCT) is used to assess stent tissue coverage and malapposition in stent evaluation trials. We developed the OCT Image Visualization and Analysis Toolkit for Stent (OCTivat-Stent), for highly automated analysis of IVOCT pullbacks. Algorithms automatically detected the guidewire, lumen boundary, and stent struts; determined the presence of tissue coverage for each strut; and estimated the stent contour for comparison of stent and lumen area. Strut-level tissue thickness, tissue coverage area, and malapposition area were automatically quantified. The software was used to analyze 292 stent pullbacks. The concordance-correlation-coefficients of automatically measured stent and lumen areas and independent ...

      Read Full Article
    3. Optical Coherence Tomography-Based Modeling of Stent Deployment in Heavily Calcified Coronary Lesion

      Optical Coherence Tomography-Based Modeling of Stent Deployment in Heavily Calcified Coronary Lesion

      In this work, a heavily calcified coronary artery model was reconstructed from optical coherence tomography (OCT) images to investigate the impact of calcification characteristics on stenting outcomes. The calcification was quantified at various cross sections in terms of angle, maximum thickness, and area. The stent deployment procedure, including the crimping, expansion, and recoil, was implemented. The influence of calcification characteristics on stent expansion, malapposition, and lesion mechanics was characterized. Results have shown that the minimal lumen area following stenting occurred at the cross section with the greatest calcification angle. The calcification angle constricted the stretchability of the lesion and thus ...

      Read Full Article
    4. Automated plaque characterization using deep learning on coronary intravascular optical coherence tomographic images

      Automated plaque characterization using deep learning on coronary intravascular optical coherence tomographic images

      Accurate identification of coronary plaque is very important for cardiologists when treating patients with advanced atherosclerosis. We developed fully-automated semantic segmentation of plaque in intravascular OCT images. We trained/tested a deep learning model on a folded, large, manually annotated clinical dataset. The sensitivities/specificities were 87.4%/89.5% and 85.1%/94.2% for pixel-wise classification of lipidous and calcified plaque, respectively. Automated clinical lesion metrics, potentially useful for treatment planning and research, compared favorably (<4%) with those derived from ground-truth labels. When we converted the results to A-line classification, they were significantly better (p < 0.05) than ...

      Read Full Article
    5. Automated intravascular plaque classification

      Automated intravascular plaque classification

      Methods and apparatus automatically classify intravascular plaque using features extracted from intravascular optical coherence tomography (IVOCT) imagery. One example apparatus includes an image acquisition circuit that accesses a set of IVOCT images, a pre-processing circuit that generates a blood vessel mask based on the IVOCT images, a feature extraction circuit that defines a three dimensional (3D) volume of interest centered on a location in a member of the set of IVOCT images, a classification circuit that generates a classification based on a probability that a voxel represents a type of plaque, and a visualization circuit that provides a visualization, substantially ...

      Read Full Article
    6. Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets

      Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets

      We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features. We incorporated features developed in previous studies (e.g., optical attenuation and A-line peaks). In addition, we included vascular lumen morphology and three-dimensional (3-D) digital edge and texture features. Classification methods were developed using expansive datasets (∼7000  images), consisting of both clinical in-vivo images and an ex-vivo dataset, which was validated using 3-D cryo-imaging/histology. Conditional random field was used to perform 3-D classification noise cleaning of classification results. We tested various multiclass approaches, classifiers ...

      Read Full Article
    7. Postdoc Opening in Coronary Artery, Intravascular OCT Computational Imaging at Case Western Reserve University

      Postdoc Opening in Coronary Artery, Intravascular OCT Computational Imaging at Case Western Reserve University

      We have a postdoctoral opportunity to advance new solutions in cardiovascular and ophthalmological biomedical imaging using machine and deep learning approaches. Projects include mass screening of disease, diagnosis/staging, treatment evaluation, and image guided therapies. A particular opportunity exists in coronary artery intravascular OCT, where we use biomechanical experiments, deep learning. and finite element modeling with the intention of creating software to help plan interventional treatments. Trainees will have an opportunity to join and learn from the wide ranging biomedical imaging community at Case Western Reserve University, which includes the Center of Computational Imaging and Personalized Diagnostics (CCIPD), the Case ...

      Read Full Article
    8. Automated analysis of intravascular OCT image volumes

      Automated analysis of intravascular OCT image volumes

      This disclosure provides systems and methods to automatically classify stent struts as covered or uncovered and to measure the thickness of tissue coverage. As one example, the method includes storing three-dimensional image data acquired intravascularly via an optical coherence tomography (OCT) apparatus and detecting struts based on analysis of the image data. Image data corresponding to each of the detected struts is further analyzed automatically to compute an indication of tissue coverage for the stent.

      Read Full Article
    9. Analysis of optical tomography (OCT) images

      Analysis of optical tomography (OCT) images

      A method includes storing three-dimensional image data acquired intravascularly via an optical coherence tomography (OCT) apparatus. The image data is analyzed to compute a probability estimate of stent presence at support positions appearing in an A-line. Stent strut locations are located in three-dimensional space based on the computed probability estimate of stent presence.

      Read Full Article
    10. Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

      Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

      Evidence suggests high-resolution, high-contrast, 100    frames / s 100  frames/s intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and three-dimensional (3-D) registration methods to provide validation of IVOCT pullback volumes using microscopic, color, and fluorescent cryo-image volumes with optional registered cryo-histology. A specialized registration method matched IVOCT pullback images acquired in the catheter reference frame to a true 3-D cryo-image volume. Briefly, an 11-parameter registration model including a polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition ...

      Read Full Article
    11. Processing to determine optical parameters of atherosclerotic disease from phantom and clinical intravascular optical coherence tomography three-dimensional pullbacks

      Processing to determine optical parameters of atherosclerotic disease from phantom and clinical intravascular optical coherence tomography three-dimensional pullbacks

      Analysis of intravascular optical coherence tomography (IVOCT) data has potential for real-time in vivo plaque classification. We developed a processing pipeline on a three-dimensional local region of support for estimation of optical properties of atherosclerotic plaques from coronary artery, IVOCT pullbacks. Using realistic coronary artery disease phantoms, we determined insignificant differences in mean and standard deviation estimates between our pullback analyses and more conventional processing of stationary acquisitions with frame averaging. There was no effect of tissue depth or oblique imaging on pullback parameter estimates. The method’s performance was assessed in comparison with observer-defined standards using clinical pullback data ...

      Read Full Article
    12. 3D registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

      3D registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation

      High resolution, 100 frames/sec intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and 3D registration methods, to provide validation of IVOCT pullback volumes using microscopic, brightfield and fluorescent cryoimage volumes, with optional, exactly registered cryo-histology. The innovation was a method to match an IVOCT pullback images, acquired in the catheter reference frame, to a true 3D cryo-image volume. Briefly, an 11-parameter, polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition. Virtual catheter parameters were optimized to ...

      Read Full Article
    13. Classification of calcium in intravascular OCT images for the purpose of intervention planning

      Classification of calcium in intravascular OCT images for the purpose of intervention planning

      The presence of extensive calcification is a primary concern when planning and implementing a vascular percutaneous intervention such as stenting. If the balloon does not expand, the interventionalist must blindly apply high balloon pressure, use an atherectomy device, or abort the procedure. As part of a project to determine the ability of Intravascular Optical Coherence Tomography (IVOCT) to aid intervention planning, we developed a method for automatic classification of calcium in coronary IVOCT images. We developed an approach where plaque texture is modeled by the joint probability distribution of a bank of filter responses where the filter bank was chosen ...

      Read Full Article
    14. 3-D Stent Detection in Intravascular OCT Using a Bayesian Network and Graph Search

      3-D Stent Detection in Intravascular OCT Using a Bayesian Network and Graph Search

      Worldwide, many hundreds of thousands of stents are implanted each year to revascularize occlusions in coronary arteries. Intravascular optical coherence tomography (OCT) is an important emerging imaging technique, which has the resolution and contrast necessary to quantitatively analyze stent deployment and tissue coverage following stent implantation. Automation is needed, as current, it takes up to 16 hours to manually analyze hundreds of images and thousands of stent struts from a single pullback. For automated strut detection, we used image formation physics and machine learning via a Bayesian network, and 3-D knowledge of stent structure via graph search. Graph search was ...

      Read Full Article
    15. Parameter estimation of atherosclerotic tissue optical properties from three-dimensional intravascular optical coherence tomography

      Parameter estimation of atherosclerotic tissue optical properties from three-dimensional intravascular optical coherence tomography

      We developed robust, three-dimensional methods, as opposed to traditional A-line analysis, for estimating the optical properties of calcified, fibrotic, and lipid atherosclerotic plaques from in vivo coronary artery intravascular optical coherence tomography clinical pullbacks. We estimated attenuation μ t and backscattered intensity I 0 from small volumes of interest annotated by experts in 35 pullbacks. Some results were as follows: noise reduction filtering was desirable, parallel line (PL) methods outperformed individual line methods, root mean square error was the best goodness-of-fit, and α -trimmed PL ( α -T-PL) was the best overall method. Estimates of μ t were calcified ( 3.84 ± 0.95     mm − 1 ...

      Read Full Article
    16. Differences determined by optical coherence tomography volumetric analysis in non-culprit lesion morphology and inflammation in ST-segment elevation myocardial infarction and stable angina pectoris patients

      Differences determined by optical coherence tomography volumetric analysis in non-culprit lesion morphology and inflammation in ST-segment elevation myocardial infarction and stable angina pectoris patients

      Background: While the current methodology for determining fibrous cap (FC) thickness of lipid plaques is based on manual measurements of arbitrary points, which could lead to high variability and decreased accuracy, it ignores the three-dimensional (3-D) morphology of coronary artery disease. Objective: To compare, utilizing optical coherence tomography (OCT) assessments, volumetric quantification of FC and macrophage detection using both visual assessment and automated image processing algorithms in non-culprit lesions of STEMI and stable angina pectoris (SAP) patients. Methods: Lipid plaques were selected from 67 consecutive patients (1 artery/patient). FC was manually delineated by a computer-aided method and automatically classified ...

      Read Full Article
    17. Feature Of The Week 1/20/13: CWRU Demonstrates Automatic Stent Detection in Intravascular OCT Images Using Bagged Decision Trees

      Feature Of The Week 1/20/13: CWRU Demonstrates Automatic Stent Detection in Intravascular OCT Images Using Bagged Decision Trees

      Cardiovascular disease is the leading cause of death worldwide. Stent implantation by means of percutaneous coronary intervention is the most common coronary revascularization procedure. Intravascular Optical Coherence Tomography (iOCT) is the only imaging modality with the resolution and contrast necessary to enable accurate measurements of luminal architecture and neointima stent coverage. Manual analysis of intravascular OCT pullbacks is time consuming, limiting the size and number of studies that can be performed. We developed a highly automated method for detecting stent struts and measuring tissue coverage. Candidate struts were first identified using image processing techniques. We trained a bagged decision trees ...

      Read Full Article
    18. Automatic stent detection in intravascular OCT images using bagged decision trees

      Automatic stent detection in intravascular OCT images using bagged decision trees

      Intravascular optical coherence tomography (iOCT) is being used to assess viability of new coronary artery stent designs. We developed a highly automated method for detecting stent struts and measuring tissue coverage. We trained a bagged decision trees classifier to classify candidate struts using features extracted from the images. With 12 best features identified by forward selection, recall (precision) were 90%–94% (85%–90%). Including struts deemed insufficiently bright for manual analysis, precision improved to 94%. Strut detection statistics approached variability of manual analysis. Differences between manual and automatic area measurements were 0.12 ± 0.20 mm 2 and 0.11 ...

      Read Full Article
    19. Three-Dimensional Fourier-Domain Optical Coherence Tomography Imaging: Advantages and Future Development

      Three-Dimensional Fourier-Domain Optical Coherence Tomography Imaging: Advantages and Future Development

      Traditionally, intravascular imaging methods display the coronary anatomy in two dimensions, through a series of consecutive cross-sectional tomographic images. The physician is then required to mentally reassemble these images in order to visualize the vascular anatomy and all its complex interactions. The ability to depict the vascular structure with its actual spatial appearance, in three dimensions, is a powerful way to provide an easy, objective, and comprehensive overview of its complex and dynamic anatomy. However, three-dimensional (3D) application of intravascular imaging has been plagued by lack of enough resolution, frequent presence of imaging and motion artifacts and need for extensive ...

      Read Full Article
    20. Volumetric quantification of fibrous caps using intravascular optical coherence tomography

      Volumetric quantification of fibrous caps using intravascular optical coherence tomography

      The rupture of thin-cap fibroatheroma accounts for most acute coronary events. Optical Coherence Tomography (OCT) allows quantification of fibrous cap (FC) thickness in vivo. Conventional manual analysis, by visually determining the thinnest part of the FC is subject to inter-observer variability and does not capture the 3-D morphology of the FC. We propose and validate a computer-aided method that allows volumetric analysis of FC. The radial FC boundary is semi-automatically segmented using a dynamic programming algorithm. The thickness at every point of the FC boundary, along with 3-D morphology of the FC, can be quantified. The method was validated against ...

      Read Full Article
    21. Measuring hemodynamics in the developing heart tube with four-dimensional gated Doppler optical coherence tomography

      Measuring hemodynamics in the developing heart tube with four-dimensional gated Doppler optical coherence tomography

      Hemodynamics is thought to play a major role in heart development, yet tools to quantitatively assess hemodynamics in the embryo are sorely lacking. The especially challenging analysis of hemodynamics in the early embryo requires new technology. Small changes in blood flow could indicate when anomalies are initiated even before structural changes can be detected. Furthermore, small changes in the early embryo that affect blood flow could lead to profound abnormalities at later stages. We present a demonstration of 4-D Doppler optical coherence tomography (OCT) imaging of structure and flow, and present several new hemodynamic measurements on embryonic avian hearts at ...

      Read Full Article
    22. Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images

      Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images
      Coronary calcified plaque (CP) is both an important marker of atherosclerosis and major determinant of the success of coronary stenting. Intracoronary optical coherence tomography (OCT) with high spatial resolution can provide detailed volumetric characterization of CP. We present a semiautomatic method for segmentation and quantification of CP in OCT images. Following segmentation of the lumen, guide wire, and arterial wall, the CP was localized by edge detection and traced using a combined intensity and gradient-based level-set model. From the segmentation regions, quantification of the depth, area, angle fill fraction, and thickness of the CP was demonstrated. Validation by comparing the ...
      Read Full Article
    23. Imaging system

      Imaging system
      Systems, methods, media, and other embodiments associated with episcopic, histological, autoradiographic, and/or other imaging are described. One exemplary system includes a cryomicrotome, an episcopic imaging device and a histological imaging device, logic for registering episcopic images with histological images, and logic for manipulating images acquired from the episcopic imaging device and the histological imaging device.
      Read Full Article
    24. High temporal resolution OCT using image-based retrospective gating

      High temporal resolution OCT using image-based retrospective gating
      High temporal resolution OCT imaging is very advantageous for analyzing cardiac mechanics in the developing embryonic heart of small animals. An image-based retrospective gating technique is presented to increase the effective temporal resolution of an OCT system and to allow visualization of systolic dynamics in 3D. The gating technique employs image similarity measures for rearranging asynchronously acquired input data consisting of a time series of 2D images at each z position along the heart volume, to produce a time sequence of 3D volumes of the beating heart. The study includes a novel robust validation technique, which quantitatively evaluates the accuracy ...
      Read Full Article
    1-25 of 25
  1. Categories

    1. Applications:

      Art, Cardiology, Dentistry, Dermatology, Developmental Biology, Gastroenterology, Gynecology, Microscopy, NDE/NDT, Neurology, Oncology, Ophthalmology, Other Non-Medical, Otolaryngology, Pulmonology, Urology
    2. Business News:

      Acquisition, Clinical Trials, Funding, Other Business News, Partnership, Patents
    3. Technology:

      Broadband Sources, Probes, Tunable Sources
    4. Miscellaneous:

      Jobs & Studentships, Student Theses, Textbooks
  2. Topics in the News

    1. (25 articles) Case Western Reserve University
    2. (25 articles) David L. Wilson
    3. (19 articles) Hiram G. Bezerra
    4. (13 articles) Andrew M. Rollins
    5. (10 articles) Marco A. Costa
    6. (10 articles) Madhusudhana Gargesha
    7. (9 articles) Zhao Wang
    8. (4 articles) Michael W. Jenkins
    9. (4 articles) Hong Lu
    10. (3 articles) Guilherme F. Attizzani
    11. (1 articles) Capital Medical University
    12. (1 articles) Medical University of Vienna
    13. (1 articles) New York Eye and Ear Infirmary
    14. (1 articles) Nanjing University of Science and Technology
    15. (1 articles) Bern University Hospital
    16. (1 articles) Martin S. Zinkernagel
  3. Popular Articles

  4. Picture Gallery

    High temporal resolution OCT using image-based retrospective gating Semiautomatic segmentation and quantification of calcified plaques in intracoronary optical coherence tomography images Measuring hemodynamics in the developing heart tube with four-dimensional gated Doppler optical coherence tomography Volumetric quantification of fibrous caps using intravascular optical coherence tomography Three-Dimensional Fourier-Domain Optical Coherence Tomography Imaging: Advantages and Future Development Automatic stent detection in intravascular OCT images using bagged decision trees Feature Of The Week 1/20/13: CWRU Demonstrates Automatic Stent Detection in Intravascular OCT Images Using Bagged Decision Trees Differences determined by optical coherence tomography volumetric analysis in non-culprit lesion morphology and inflammation in ST-segment elevation myocardial infarction and stable angina pectoris patients Classification of calcium in intravascular OCT images for the purpose of intervention planning Retinal Vascular Features in Ocular Blunt Trauma by Optical Coherence Tomography Angiography Non-invasive imaging of a choroidal macrovessel Correlation between optical coherence tomography, multifocal electroretinogram findings and visual acuity in diabetic macular edema