1. 1-4 of 4
    1. A Machine-Learning Graph-Based Approach for 3D Segmentation of Bruch’s Membrane Opening from Glaucomatous SD-OCT Volumes

      A Machine-Learning Graph-Based Approach for 3D Segmentation of Bruch’s Membrane Opening from Glaucomatous SD-OCT Volumes

      Bruch’s membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Measuring this structural parameter requires identification of BMO locations within spectral domain-optical coherence tomography (SD-OCT) volumes. While most automated approaches for segmentation of the BMO either segment the 2D projection of BMO points or identify BMO points in individual B-scans, in this work, we propose a machine-learning graph-based approach for true 3D segmentation of BMO from glaucomatous SD-OCT volumes. The problem is formulated as an optimization ...

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    2. Integrated Local Binary Pattern Texture Features for Classification of Breast Tissue Imaged by Optical Coherence Microscopy

      Integrated Local Binary Pattern Texture Features for Classification of Breast Tissue Imaged by Optical Coherence Microscopy

      This paper proposes a texture analysis technique that can effectively classify different types of human breast tissue imaged by Optical Coherence Microscopy (OCM). OCM is an emerging imaging modality for rapid tissue screening and has the potential to provide high resolution microscopic images that approach those of histology. OCM images, acquired without tissue staining, however, pose unique challenges to image analysis and pattern classification. We examined multiple types of texture features and found Local Binary Pattern (LBP) features to perform better in classifying tissues imaged by OCM. In order to improve classification accuracy, we propose novel variants of LBP features ...

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    3. Online Tracking and Retargeting with Applications to Optical Biopsy in Gastrointestinal Endoscopic Examinations

      Online Tracking and Retargeting with Applications to Optical Biopsy in Gastrointestinal Endoscopic Examinations

      With recent advances in biophotonics, techniques such as narrow band imaging, confocal laser endomicroscopy, fluorescence spectroscopy, and optical coherence tomography, can be combined with normal white-light endoscopes to provide in vivo microscopic tissue characterisation, potentially avoiding the need for offline histological analysis. Despite the advantages of these techniques to provide online optical biopsy in situ , it is challenging for gastroenterologists to retarget the optical biopsy sites during endoscopic examinations. This is because optical biopsy does not leave any mark on the tissue. Furthermore, typical endoscopic cameras only have a limited field-of-view and the biopsy sites often enter or exit the ...

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    4. Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography

      Loosely coupled level sets for simultaneous 3D retinal layer segmentation in optical coherence tomography

      Optical coherence tomography (OCT) yields high-resolution, three-dimensional images of the retina. Reliable segmentation of the retinal layers is necessary for the extraction of clinically useful information. We present a novel segmentation method that operates on attenuation coefficients and incorporates anatomical knowledge about the retina. The attenuation coefficients are derived from in-vivo human retinal OCT data and represent an optical property of the tissue. Then, the layers in the retina are simultaneously segmented via a new flexible coupling approach that exploits the predefined order of the layers. The accuracy of the method was evaluated on 20 peripapillary scans of healthy subjects ...

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    1-4 of 4
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