1. Articles from Ronny Y. Shalev

    1-2 of 2
    1. 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 ...

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    2. AUTOMATED MACHINE LEARNING BASED ANALYSIS OF INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY IMAGES (Thesis)

      AUTOMATED MACHINE LEARNING BASED ANALYSIS OF INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY IMAGES (Thesis)

      Coronary artery disease (CAD) is the leading cause of death in the world. Most acute coronary events (e.g. heart attacks) are due to the rupture of atherosclerotic plaques inside the arteries, however, calcified lesion is the most widely treatable, typically, by stent implantation via percutaneous coronary intervention (PCI). Intravascular Optical Coherence Tomography (IVOCT) imaging has the resolution, contrast, and penetration depth to characterize coronary artery plaques. Conventional manual evaluation of IVOCT images, based on qualitative interpretation of image features, is tedious and time consuming. The aim of this PhD dissertation was to develop advanced algorithms to fully automate the ...

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    1-2 of 2
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  2. Topics in the News

    1. (2 articles) Case Western Reserve University
    2. (1 articles) David L. Wilson
    3. (1 articles) Erasmus University
    4. (1 articles) Evelyn Regar
    5. (1 articles) Antonios Karanasos
    6. (1 articles) Heidelberg Engineering
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    AUTOMATED MACHINE LEARNING BASED ANALYSIS OF INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY IMAGES (Thesis) Automated intravascular plaque classification The Effect of Anti-Tubercular Drugs on Retinal Nerve Fiber Layer Thickness Using Optical Coherence Tomography A Cross-sectional Optical Coherence Tomography Study in Patients on Taxane-based Therapy and A Case Report with the Literature Review Association of systemic inflammatory biomarkers with morphological characteristics of the coronary atherosclerotic plaque by intravascular optical coherence tomography. OCT angiography improves views of retina blood flow Real-time retinal layer segmentation of OCT Volumes with GPU and Deep learning Baylor College of Medicine Receives a 2020 NIH Grant for Biomechanics of Early Mammalian Cardiogenesis University of Houston Receives a 2020 NIH Grant for Biomechanics of Neural Tube Development using Brillouin-OCT Multimodality Oregon Health and Sciences University Receives a 2020 NIH Grant  for Artificial Intelligence Assisted Panoramic Optical Coherence Tomography for Retinopathy of Prematurity UC Irvine Receives a 2020 NIH Grant for In Vivo Imaging and Quantification of Cilia Beating Dynamics Using Phase-Resolved Optical Imaging Technology UC Irvine Receives a 2020 NIH Grant for Phased Resolved ARF Optical Coherence Elastography for Intravascular Imaging