Automated 3 D Segmentation And Analysis Of Retinal Optical Coherence Tomography Images
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Automated 3 D Segmentation And Analysis Of Retinal Optical Coherence Tomography Images
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Author : Mona Kathryn Garvin
language : en
Publisher:
Release Date : 2008
Automated 3 D Segmentation And Analysis Of Retinal Optical Coherence Tomography Images written by Mona Kathryn Garvin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Optical coherence tomography categories.
Automated Segmentation Of Retinal Optical Coherence Tomography Images
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Author : Priyanka Roy
language : en
Publisher:
Release Date : 2018
Automated Segmentation Of Retinal Optical Coherence Tomography Images written by Priyanka Roy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Optical coherence tomography categories.
Aim. Optical Coherence Tomography (OCT) is a fast and non-invasive medical imaging technique which helps in the investigation of each individual retinal layer structure. For early detection of retinal diseases and the study of their progression, segmentation of the OCT images into the distinct layers of the retina plays a crucial role. However, segmentation done by the clinicians manually is extremely tedious, time-consuming and variable with respect to the expertise level. Hence, there is an utmost necessity to develop an automated segmentation algorithm for retinal OCT images which is fast, accurate, and eases clinical decision making. Methods. Graph-theoretical methods have been implemented to develop an automated segmentation algorithm for spectral domain OCT (SD-OCT) images of the retina. As a pre-processing step, the best method for denoising the SD-OCT images prior to graph-based segmentation was determined by comparison between simple Gaussian filtering and an advanced wavelet-based denoising technique. A shortest-path based graph search technique was implemented to accurately delineate intra-retinal layer boundaries within the SD-OCT images. The results from the automated algorithm were also validated by comparison with manual segmentation done by an expert clinician using a specially designed graphical user interface (GUI). Results. The algorithm delineated seven intra-retinal boundaries thereby segmenting six layers of the retina along with computing their thicknesses. The thickness results from the automated algorithm when compared to normative layer thickness values from a published study showed no significant differences (p > 0.05) for all layers except layer 4 (p = 0.04). Furthermore, when a comparative analysis was done between the results from the automated segmentation algorithm and that from manual segmentation by an expert, the accuracy of the algorithm varied between 74.58% (layer 2) to 98.90% (layer 5). Additionally, the comparison of two different denoising techniques revealed that there was no significant impact of an advanced wavelet-based denoising technique over the use of simple Gaussian filtering on the accuracy of boundary detection by the graph-based algorithm. Conclusion. An automated graph-based algorithm was developed and implemented in this thesis for the segmentation of seven intra-retinal boundaries and six layers in SD-OCT images which is as good as manual segmentation by an expert clinician. This thesis also concludes on the note that simple Gaussian filters are sufficient to denoise the images in graph-based segmentation techniques and does not require an advanced denoising technique. This makes the complexity of implementation far more simple and efficient in terms of time and memory requirements.
Automated 3 D Segmentation Of Intraretinal Surfaces From Optical Coherence Tomography Images Centered On The Optic Nerve Head
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Author : Bhavna Josephine Antony
language : en
Publisher:
Release Date : 2009
Automated 3 D Segmentation Of Intraretinal Surfaces From Optical Coherence Tomography Images Centered On The Optic Nerve Head written by Bhavna Josephine Antony and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Glaucoma categories.
Optical coherence tomography (OCT), being a noninvasive imaging modality, has begun to find vast use in the diagnosis and management of retinal diseases. These high-resolution images of the retina allow structural changes to be detected and tracked. For instance, in glaucoma, the retinal nerve fiber layer (RNFL) has been known to thin. The recent availability of the considerably larger volumetric data from the spectral-domain OCT scanners has further increased the need for new processing techniques. This body of work is centered around 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 through the computation of a minimum-cost closed set in a vertex-weighted graph constructed using edge/regional information, and subject to a priori determined varying surface interaction and smoothness constraints. The method also addresses the challenges posed by presence of the neural canal and the large blood vessels found at the ONH. The method was used to study RNFL thickness maps of normal and glaucomatous eyes, which showed average thicknesses of 73.72 +/- 32.72um and 60.38 +/- 25.22um (p
Fully Automated Segmentation Of Fluid Regions In Exudative Age Related Macular Degeneration Subjects Kernel Graph Cut In Neutrosophic Domain
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Author : Abdolreza Rashno
language : en
Publisher: Infinite Study
Release Date :
Fully Automated Segmentation Of Fluid Regions In Exudative Age Related Macular Degeneration Subjects Kernel Graph Cut In Neutrosophic Domain written by Abdolreza Rashno and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
A fully-automated method based on graph shortest path, graph cut and neutrosophic (NS) sets is presented for fluid segmentation in OCT volumes for exudative age related macular degeneration (EAMD) subjects.
Retinal Optical Coherence Tomography Image Analysis
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Author : Xinjian Chen
language : en
Publisher: Springer
Release Date : 2019-07-05
Retinal Optical Coherence Tomography Image Analysis written by Xinjian Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-05 with Science categories.
This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging.
Fully Automated Segmentation Of Fluid Cyst Regions In Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets And Graph Algorithms
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Author : Abdolreza Rashno
language : en
Publisher: Infinite Study
Release Date :
Fully Automated Segmentation Of Fluid Cyst Regions In Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets And Graph Algorithms written by Abdolreza Rashno and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
This paper presents a fully-automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema (DME).
High Resolution Imaging In Microscopy And Ophthalmology
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Author : Josef F. Bille
language : en
Publisher: Springer
Release Date : 2019-08-13
High Resolution Imaging In Microscopy And Ophthalmology written by Josef F. Bille and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-13 with Medical categories.
This open access book provides a comprehensive overview of the application of the newest laser and microscope/ophthalmoscope technology in the field of high resolution imaging in microscopy and ophthalmology. Starting by describing High-Resolution 3D Light Microscopy with STED and RESOLFT, the book goes on to cover retinal and anterior segment imaging and image-guided treatment and also discusses the development of adaptive optics in vision science and ophthalmology. Using an interdisciplinary approach, the reader will learn about the latest developments and most up to date technology in the field and how these translate to a medical setting. High Resolution Imaging in Microscopy and Ophthalmology – New Frontiers in Biomedical Optics has been written by leading experts in the field and offers insights on engineering, biology, and medicine, thus being a valuable addition for scientists, engineers, and clinicians with technical and medical interest who would like to understand the equipment, the applications and the medical/biological background. Lastly, this book is dedicated to the memory of Dr. Gerhard Zinser, co-founder of Heidelberg Engineering GmbH, a scientist, a husband, a brother, a colleague, and a friend.
Automated Retinal Layer Segmentation And Pre Apoptotic Monitoring For Three Dimensional Optical Coherence Tomography
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Author : Vedran Kajic
language : en
Publisher:
Release Date : 2011
Automated Retinal Layer Segmentation And Pre Apoptotic Monitoring For Three Dimensional Optical Coherence Tomography written by Vedran Kajic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
The aim of this PhD thesis was to develop segmentation algorithm adapted and optimized to retinal OCT data that will provide objective 3D layer thickness which might be used to improve diagnosis and monitoring of retinal pathologies. Additionally, a 3D stack registration method was produced by modifying an existing algorithm. A related project was to develop a pre-apoptotic retinal monitoring based on the changes in texture parameters of the OCT scans in order to enable treatment before the changes become irreversible; apoptosis refers to the programmed cell death that can occur in retinal tissue and lead to blindness. These issues can be critical for the examination of tissues within the central nervous system. A novel statistical model for segmentation has been created and successfully applied to a large data set. A broad range of future research possibilities into advanced pathologies has been created by the results obtained. A separate model has been created for choroid segmentation located deep in retina, as the appearance of choroid is very different from the top retinal layers. Choroid thickness and structure is an important index of various pathologies (diabetes etc.). As part of the pre-apoptotic monitoring project it was shown that an increase in proportion of apoptotic cells in vitro can be accurately quantified. Moreover, the data obtained indicates a similar increase in neuronal scatter in retinal explants following axotomy (removal of retinas from the eye), suggesting that UHR-OCT can be a novel non-invasive technique for the in vivo assessment of neuronal health. Additionally, an independent project within the computer science department in collaboration with the school of psychology has been successfully carried out, improving analysis of facial dynamics and behaviour transfer between individuals. Also, important improvements to a general signal processing algorithm, dynamic time warping (DTW), have been made, allowing potential application in a broad signal processing field.
Computational Retinal Image Analysis
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Author : Emanuele Trucco
language : en
Publisher: Academic Press
Release Date : 2019-11-19
Computational Retinal Image Analysis written by Emanuele Trucco and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-19 with Computers categories.
Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies
Deep Learning Approach For The Detection And Quantification Of Intraretinal Cystoid Fluid In Multivendor Optical Coherence Tomography
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Author : FREERK G. VENHUIZEN
language : en
Publisher: Infinite Study
Release Date :
Deep Learning Approach For The Detection And Quantification Of Intraretinal Cystoid Fluid In Multivendor Optical Coherence Tomography written by FREERK G. VENHUIZEN and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition.