1. Articles from Bhavna J. Antony

    1-13 of 13
    1. Retinal optical coherence tomography image enhancement via deep learning

      Retinal optical coherence tomography image enhancement via deep learning

      Optical coherence tomography (OCT) images of the retina are a powerful tool for diagnosing and monitoring eye disease. However, they are plagued by speckle noise, which reduces image quality and reliability of assessment. This paper introduces a novel speckle reduction method inspired by the recent successes of deep learning in medical imaging. We present two versions of the network to reflect the needs and preferences of different end-users. Specifically, we train a convolution neural network to denoise cross-sections from OCT volumes of healthy eyes using either (1) mean-squared error, or (2) a generative adversarial network (GAN) with Wasserstein distance and ...

      Read Full Article
    2. Collaborative SDOCT segmentation and analysis software

      Collaborative SDOCT segmentation and analysis software

      Spectral domain optical coherence tomography (SDOCT) is routinely used in the management and diagnosis of a variety of ocular diseases. This imaging modality also finds widespread use in research, where quantitative measurements obtained from the images are used to track disease progression. In recent years, the number of available scanners and imaging protocols grown and there is a distinct absence of a unified tool that is capable of visualizing, segmenting, and analyzing the data. This is especially noteworthy in longitudinal studies, where data from older scanners and/or protocols may need to be analyzed. Here, we present a graphical user ...

      Read Full Article
    3. Longitudinal analysis of mouse SDOCT volumes

      Longitudinal analysis of mouse SDOCT volumes

      Spectral-domain optical coherence tomography (SDOCT), in addition to its routine clinical use in the diagnosis of ocular diseases, has begun to fund increasing use in animal studies. Animal models are frequently used to study disease mechanisms as well as to test drug efficacy. In particular, SDOCT provides the ability to study animals longitudinally and non-invasively over long periods of time. However, the lack of anatomical landmarks makes the longitudinal scan acquisition prone to inconsistencies in orientation. Here, we propose a method for the automated registration of mouse SDOCT volumes. The method begins by accurately segmenting the blood vessels and the ...

      Read Full Article
    4. Voxel based morphometry in optical coherence tomography: validation and core findings

      Voxel based morphometry in optical coherence tomography: validation and core findings

      Optical coherence tomography (OCT) of the human retina is now becoming established as an important modality for the detection and tracking of various ocular diseases. Voxel based morphometry (VBM) is a long standing neuroimaging analysis technique that allows for the exploration of the regional differences in the brain. There has been limited work done in developing registration based methods for OCT, which has hampered the advancement of VBM analyses in OCT based population studies. Following on from our recent development of an OCT registration method, we explore the potential benefits of VBM analysis in cohorts of healthy controls (HCs) and ...

      Read Full Article
    5. Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes

      Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes

      Optical coherence tomography (OCT) is a noninvasive imaging modality that has begun to find widespread use in retinal imaging for the detection of a variety of ocular diseases. In addition to structural changes in the form of altered retinal layer thicknesses, pathological conditions may also cause the formation of edema within the retina. In multiple sclerosis, for instance, the nerve fiber and ganglion cell layers are known to thin. Additionally, the formation of pseudocysts called microcystic macular edema (MME) have also been observed in the eyes of about 5% of MS patients, and its presence has been shown to be ...

      Read Full Article
    6. Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes

      Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes

      Purpose : Off-axis acquisition of spectral domain optical coherence tomography (SDOCT) images has been shown to increase total retinal thickness (TRT) measurements. We analyzed the reproducibility of TRT measurements obtained using either the retinal pigment epithelium (RPE) or Bruch's membrane as reference surfaces in off-axis scans intentionally acquired through multiple pupil positions. Methods : Five volumetric SDOCT scans of the macula were obtained from one eye of 25 normal subjects. One scan was acquired through a central pupil position, while subsequent scans were acquired through four peripheral pupil positions. The internal limiting membrane, the RPE, and Bruch's membrane were segmented ...

      Read Full Article
    7. DIRECTIONAL OPTICAL COHERENCE TOMOGRAPHY PROVIDES ACCURATE OUTER NUCLEAR LAYER AND HENLE FIBER LAYER MEASUREMENTS

      DIRECTIONAL OPTICAL COHERENCE TOMOGRAPHY PROVIDES ACCURATE OUTER NUCLEAR LAYER AND HENLE FIBER LAYER MEASUREMENTS

      PURPOSE: The outer nuclear layer (ONL) contains photoreceptor nuclei, and its thickness is an important biomarker for retinal degenerations. Accurate ONL thickness measurements are obscured in standard optical coherence tomography (OCT) images because of Henle fiber layer (HFL). Improved differentiation of the ONL and HFL boundary is made possible by using directional OCT, a method that purposefully varies the pupil entrance position of the OCT beam. METHODS: Fifty-seven normal eyes were imaged using multiple pupil entry positions with a commercial spectral domain OCT system. Cross-sectional image sets were registered to each other and segmented at the top of HFL, the ...

      Read Full Article
    8. Automated 3D Segmentation of Intraretinal Surfaces in SD-OCT Volumes in Normal and Diabetic Mice

      Automated 3D Segmentation of Intraretinal Surfaces in SD-OCT Volumes in Normal and Diabetic Mice

      Purpose: To describe an adaptation of an existing graph-theoretic method (initially developed for human optical coherence tomography [ OCT ] images) for the three-dimensional ( 3D ) automated segmentation of 10 intraretinal surfaces in mice scans, and assess the accuracy of the method and the reproducibility of thickness measurements. Methods: Ten intraretinal surfaces were segmented in repeat spectral domain ( SD )- OCT volumetric images acquired from normal ( n = 8) and diabetic ( n = 10) mice . The accuracy of the method was assessed by computing the border position errors of the automated segmentation with respect to manual tracings obtained from two experts. The reproducibility was statistically assessed ...

      Read Full Article
    9. Automated 3D segmentation of multiple surfaces with a shared hole: segmentation of the neural canal opening in SD-OCT volumes

      Automated 3D segmentation of multiple surfaces with a shared hole: segmentation of the neural canal opening in SD-OCT volumes

      The need to segment multiple interacting surfaces is a common problem in medical imaging and it is often assumed that such surfaces are continuous within the confines of the region of interest. However, in some application areas, the surfaces of interest may contain a shared hole in which the surfaces no longer exist and the exact location of the hole boundary is not known a priori . The boundary of the neural canal opening seen in spectral-domain optical coherence tomography volumes is an example of a “hole” embedded with multiple surrounding surfaces. Segmentation approaches that rely on finding the surfaces alone ...

      Read Full Article
    10. 3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice

      3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice

      Anterior segment optical coherence tomography (AS-OCT) is a non-invasive imaging modality that allows for the quantitative assessment of corneal thicknesses. Automated approaches for these measurements are not readily available and therefore measurements are often obtained manually. While graph-based approaches that enable the optimal simultaneous segmentation of multiple 3D surfaces have been proposed and applied to 3D optical coherence tomography volumes of the back of the eye, such approaches have not been applied for the segmentation of the corneal surfaces. In this work we propose adapting this graph-based method for the automated 3D segmentation of three corneal surfaces in AS-OCT images ...

      Read Full Article
    11. A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes

      A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes

      Optical coherence tomography is routinely used clinically for the detection and management of ocular diseases as well as in research where the studies may involve animals. This routine use requires that the developed automated segmentation methods not only be accurate and reliable, but also be adaptable to meet new requirements. We have previously proposed the use of a graph-theoretic approach for the automated 3-D segmentation of multiple retinal surfaces in volumetric human SD-OCT scans. The method ensures the global optimality of the set of surfaces with respect to a cost function. Cost functions have thus far been typically designed by ...

      Read Full Article
    12. Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes

      Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes

      While efficient graph-theoretic approaches exist for the optimal (with respect to a cost function) and simultaneous segmentation of multiple surfaces within volumetric medical images, the appropriate design of cost functions remains an important challenge. Previously proposed methods have used simple cost functions or optimized a combination of the same, but little has been done to design cost functions using learned features from a training set, in a less biased fashion. Here, we present a method to design cost functions for the simultaneous segmentation of multiple surfaces using the graph-theoretic approach. Classified texture features were used to create probability maps, which ...

      Read Full Article
    13. Automated 3D segmentation of intraretinal layers from optic nerve head optical coherence tomography images

      Automated 3D segmentation of intraretinal layers from optic nerve head optical coherence tomography images
      Optical coherence tomography (OCT), being a noninvasive imaging modality, has begun to find vast use in the diagnosis and management of ocular diseases such as glaucoma, where the retinal nerve fiber layer (RNFL) has been known to thin. Furthermore, the recent availability of the considerably larger volumetric data with spectral-domain OCT has increased the need for new processing techniques. In this paper, we present an automated 3-D graph-theoretic approach for the segmentation of 7 surfaces (6 layers) of the retina from 3-D spectral-domain OCT images centered on the optic nerve head (ONH). The multiple surfaces are detected simultaneously through the ...
      Read Full Article
    1-13 of 13
  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. (7 articles) University of Iowa
    2. (6 articles) Michael D. Abràmoff
    3. (5 articles) Mona K. Garvin
    4. (4 articles) Johns Hopkins University
    5. (4 articles) Young H. Kwon
    6. (2 articles) Peter A. Calabresi
    7. (2 articles) Kyungmoo Lee
    8. (2 articles) Brandon J. Lujan
    9. (1 articles) University of Pennsylvania
    10. (1 articles) Joel S. Schuman
    11. (1 articles) Sunnybrook Health Sciences Centre
    12. (1 articles) Harvard University
    13. (1 articles) Kyoto University Graduate School of Medicine
    14. (1 articles) Ryerson University
    15. (1 articles) University of Toronto
    16. (1 articles) Nanjing University of Science and Technology
    17. (1 articles) Joel Ramjist
    18. (1 articles) Akitaka Tsujikawa
    19. (1 articles) Lida P. Hariri
    20. (1 articles) Victor X. D. Yang
  3. Popular Articles

  4. Picture Gallery

    Automated 3D segmentation of intraretinal layers from optic nerve head optical coherence tomography images Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes 3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice Automated 3D segmentation of multiple surfaces with a shared hole: segmentation of the neural canal opening in SD-OCT volumes Automated 3D Segmentation of Intraretinal Surfaces in SD-OCT Volumes in Normal and Diabetic Mice DIRECTIONAL OPTICAL COHERENCE TOMOGRAPHY PROVIDES ACCURATE OUTER NUCLEAR LAYER AND HENLE FIBER LAYER MEASUREMENTS Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes Voxel based morphometry in optical coherence tomography: validation and core findings Collaborative SDOCT segmentation and analysis software In Vivo and Ex Vivo Microscopy: Moving Toward the Integration of Optical Imaging Technologies Into Pathology Practice Recognition of calcified neoatherosclerosis