1. David L. Wilson

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    1. Mentioned In 36 Articles

    2. 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 ...
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    3. 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 ...
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    4. 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 ...
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    5. 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 ...
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    6. 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 ...
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    7. Longitudinal Detection of Radiation-Induced Peripapillary and Macular Retinal Capillary Ischemia Using Optical Coherence Tomography Angiography

      Longitudinal Detection of Radiation-Induced Peripapillary and Macular Retinal Capillary Ischemia Using Optical Coherence Tomography Angiography
      Purpose To study longitudinal changes in retinal capillary circulation in eyes treated with iodine 125 (I-125) plaque brachytherapy for uveal melanoma using optical coherence tomography angiography (OCTA). Design Longitudinal prospective study of 21 subjects undergoing treatment for uveal melanoma with I-125 plaque brachytherapy. Eyes with melanoma were imaged with OCTA prior to treatment and at 12 month intervals until 2 years post-brachytherapy. Participants After IRB-approval, participants were enrolled prospectively from ...
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    8. 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 (7000images), consisting of both clinical in-vivo images and an ...
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    9. 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 ...
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    10. Case Western Reserve University Receives NIH Grant for Computer Assisted Coronary Artery Stent Interventions

      Case Western Reserve University Receives NIH Grant for Computer Assisted Coronary Artery Stent Interventions
      Case Western Reserve University Receives a 2019 NIH Grant for $732,934 for Computer Assisted Coronary Artery Stent Interventions. The principal investigator is David WIlson. The program began in 2018 and ends in 2022. Below is a summary of the proposed work. Computer assisted coronary artery stent interventions Summary When treating highly calcified coronary artery lesions with stents, interventional cardiologists, with limited information, make stressful treatment decisions, which can lead ...
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    11. 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 ...
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    12. 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.
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    13. Deep neural networks for A-line-based plaque classification in coronary intravascular optical coherence tomography images

      Deep neural networks for A-line-based plaque classification in coronary intravascular optical coherence tomography images
      We develop neural-network-based methods for classifying plaque types in clinical intravascular optical coherence tomography (IVOCT) images of coronary arteries. A single IVOCT pullback can consist of 500 microscopic-resolution images, creating both a challenge for physician interpretation during an interventional procedure and an opportunity for automated analysis. In the proposed method, we classify each A-line, a datum element that better captures physics and pathophysiology than a voxel, as a fibrous layer ...
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    14. Automated Volumetric Intravascular Plaque Classification Using Optical Coherence Tomography

      Automated Volumetric Intravascular Plaque Classification Using Optical Coherence Tomography
      An estimated 17.5 million people died from a cardiovascular disease in 2012, representing 31 percent of all global deaths. Most acute coronary events result from rupture of the protective fibrous cap overlying an atherosclerotic plaque. The task of early identification of plaque types that can potentially rupture is, therefore, of great importance. The state-of-the-art approach to imaging blood vessels is intravascular optical coherence tomography (IVOCT). However, currently, this is ...
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    15. Detailed Vascular Anatomy of the Human Retina by Projection-Resolved Optical Coherence Tomography Angiography

      Detailed Vascular Anatomy of the Human Retina by Projection-Resolved Optical Coherence Tomography Angiography
      Optical coherence tomography angiography (OCTA) is a noninvasive method of 3D imaging of the retinal and choroidal circulations. However, vascular depth discrimination is limited by superficial vessels projecting flow signal artifact onto deeper layers. The projection-resolved (PR) OCTA algorithm improves depth resolution by removing projection artifact while retaining in-situ flow signal from real blood vessels in deeper layers. This novel technology allowed us to study the normal retinal vasculature in ...
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    16. 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 100frames/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 ...
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    17. 1-15 of 36 1 2 3 »
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  2. About David L. Wilson

    David L. Wilson

    David L. Wilson is the Robert Herbold Professor in the Biomedical Engineering department at Case Western Reserve University. Dr. Wilson research involves minimally invasive, interventional medical imaging. In one project, cancerous tumors are tumors are treated with MR-guided RF thermal ablation. My research group is developing 3D registration, segmentation, and visualization imaging is high definition TV viewing of moving objects in the body. This quantum-limited image sequence is quite noisy, and spatio-temporal processing by the human visual system is an extremely important step in the imaging chain. Thus, we study new digital image enhancement techniques using experimental and theoretical image perception evaluations. In yet another application of imaging to treatment, we use high-resolution, 3D MR images to estimate biomechanical parameters in the fingers and wrist in order to plan tendon transfer surgery and functional neuromuscular stimulation (FNS) interventions. Digital image processing can also be applied to nanoscale images, and we are creating techniques using mathematical morphology to improve AFM images of single biomolecules.