1. Articles from Alauddin Bhuiyan

    1-3 of 3
    1. Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm

      Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm

      In this paper, we propose a novel classification model for automatically identifying individuals with age-related macular degeneration (AMD) or Diabetic Macular Edema (DME) using retinal features from Spectral Domain Optical Coherence Tomography (SD-OCT) images. Our classification method uses retinal features such as the thickness of the retina and the thickness of the individual retinal layers, and the volume of the pathologies such as drusen and hyper-reflective intra-retinal spots. We extract automatically, ten clinically important retinal features by segmenting individual SD-OCT images for classification purposes. The effectiveness of the extracted features is evaluated using several classification methods such as Random Forrest ...

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    2. An Automated Method for Choroidal Thickness Measurement from Enhanced Depth Imaging Optical Coherence Tomography Images

      An Automated Method for Choroidal Thickness Measurement from Enhanced Depth Imaging Optical Coherence Tomography Images

      The choroid is vascular tissue located underneath the retina and supplies oxygen to the outer retina; any damage to this tissue can be a precursor to retinal diseases. This paper presents an automated method of choroidal segmentation from enhanced depth imaging optical coherence tomography (EDI-OCT) images. The Dijkstra shortest path algorithm is used to segment the choroid-sclera interface (CSI), the outermost border of the choroid. A novel intensity-normalisation technique that is based on the depth of the choroid is used to equalise the intensity of all non-vessel pixels in the choroid region. The outer boundary of choroidal vessel and CSI ...

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    3. Automatic Identification of Pathology-Distorted Retinal Layer Boundaries Using SD-OCT Imaging

      Automatic Identification of Pathology-Distorted Retinal Layer Boundaries Using SD-OCT Imaging

      Objective: We propose an effective automatic method for identification of four retinal layer boundaries from the spectral domain optical coherence tomography images in the presence and absence of pathologies and morphological changes due to disease. Methods: The approach first finds an approximate location of three reference layers and then uses these to bound the search space for the actual layers, which is achieved by modeling the problem as a graph and applying Dijkstra's shortest path algorithm. The edge weight between nodes is determined using pixel distance, slope similarity to a reference, and nonassociativity of the layers, which is designed ...

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    1-3 of 3
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  2. Topics in the News

    1. (2 articles) University of Melbourne
    2. (2 articles) Joel S. Schuman
    3. (2 articles) Hiroshi Ishikawa
    4. (1 articles) Singapore Eye Research Institute
    5. (1 articles) Duke University
    6. (1 articles) NYU Langone Medical Center
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