Automated Segmentation Of Retinal Optical Coherence Tomography Images
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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 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.
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).
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.
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.
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
Analytical Tools For High Resolution Oct Imaging Of Human Retina
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Author : Hitesh Pratapkumar Tanna
language : en
Publisher:
Release Date : 2009
Analytical Tools For High Resolution Oct Imaging Of Human Retina written by Hitesh Pratapkumar Tanna and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Optical coherence tomography categories.
With the advent of optical coherence tomography (OCT), remarkably detailed information about retina is now available. However, most of the clinical use of OCT relies on qualitative analysis of the data. While technological advances have provided increased resolution and quicker data acquisition, the clinical utility of OCT has not been fully realized as quantitative methods for image analysis have not kept pace with the technological advances. Hence, there is a pressing need to develop analytical tools that allow OCT to achieve its full potential as an early diagnostic tool of early degenerations. This study examined the practical improvement in image quality afforded by a broadband light source in a clinical setting and defined image quality metrics for future use in evaluating spectral domain optical coherence tomography (SD-OCT) images. Significant improvement in local contrast, resolution and contrast to noise ratio was found using a commercial broad-band light source. Horizontal striations within the IPL were also observed and believed to represent synaptic sub lamination, though further investigation is required. A novel automated segmentation algorithm to extract four retinal boundaries was developed and verified against the current gold standard - manual segmentation. This algorithm provided accurate, reliable and reproducible thickness measurements for linear and volumetric scans. The algorithm was developed for segmenting healthy retinal images, and hence can be used for normative database for thickness profiles of retinal layers.
Automated Three Dimensional Segmentation Of Intraretinal Layers 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 Three Dimensional Segmentation Of Intraretinal Layers 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 categories.
A Combined Machine Learning And Graph Based Framework For The 3 D Automated Segmentation Of Retinal Structures In Sd Oct Images
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Author : Bhavna Josephine Antony
language : en
Publisher:
Release Date : 2013
A Combined Machine Learning And Graph Based Framework For The 3 D Automated Segmentation Of Retinal Structures In Sd Oct Images 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 2013 with Retina categories.
A machine-learning based approach was also used here to learn descriptive features of the NCO. Thus, the major contributions of this work include 1) a method for the automated correction of axial artifacts in SD-OCT images, 2) a combined machine-learning and graph-theoretic framework for the segmentation of retinal surfaces in SD-OCT images (applied to humans, mice and canines), 3) a novel formulation of the graph-theoretic approach for the segmentation of multiple surfaces and their shared hole (applied to the segmentation of the neural canal opening), and 4) the investigation of textural markers that could precede structural and functional change in degenerative retinal diseases.