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Author: Anchal Sharma Publisher: Infinite Study ISBN: Category : Languages : en Pages : 5
Book Description
Conceptual Segmentation is a critical technique in medical imaging. The Processes of identification and division of optic circle and veins are the fundamental strides for the analysis of a few infections that causes visual deficiency like diabetic retinopathy, hypertension, glaucoma and different visual deficiency ailment.
Author: Anchal Sharma Publisher: Infinite Study ISBN: Category : Languages : en Pages : 5
Book Description
Conceptual Segmentation is a critical technique in medical imaging. The Processes of identification and division of optic circle and veins are the fundamental strides for the analysis of a few infections that causes visual deficiency like diabetic retinopathy, hypertension, glaucoma and different visual deficiency ailment.
Author: Xiaolu Zhu Publisher: Springer Nature ISBN: 3031016491 Category : Technology & Engineering Languages : en Pages : 95
Book Description
Fundus images of the retina are color images of the eye taken by specially designed digital cameras. Ophthalmologists rely on fundus images to diagnose various diseases that affect the eye, such as diabetic retinopathy and retinopathy of prematurity. A crucial preliminary step in the analysis of retinal images is the identification and localization of important anatomical structures, such as the optic nerve head (ONH), the macula, and the major vascular arcades. Identification of the ONH is an important initial step in the detection and analysis of the anatomical structures and pathological features in the retina. Different types of retinal pathology may be detected and analyzed via the application of appropriately designed techniques of digital image processing and pattern recognition. Computer-aided analysis of retinal images has the potential to facilitate quantitative and objective analysis of retinal lesions and abnormalities. Accurate identification and localization of retinal features and lesions could contribute to improved diagnosis, treatment, and management of retinopathy. This book presents an introduction to diagnostic imaging of the retina and an overview of image processing techniques for ophthalmology. In particular, digital image processing algorithms and pattern analysis techniques for the detection of the ONH are described. In fundus images, the ONH usually appears as a bright region, white or yellow in color, and is indicated as the convergent area of the network of blood vessels. Use of the geometrical and intensity characteristics of the ONH, as well as the property that the ONH represents the location of entrance of the blood vessels and the optic nerve into the retina, is demonstrated in developing the methods. The image processing techniques described in the book include morphological filters for preprocessing fundus images, filters for edge detection, the Hough transform for the detection of lines and circles, Gabor filters to detect the blood vessels, and phase portrait analysis for the detection of convergent or node-like patterns. Illustrations of application of the methods to fundus images from two publicly available databases are presented, in terms of locating the center and the boundary of the ONH. Methods for quantitative evaluation of the results of detection of the ONH using measures of overlap and free-response receiver operating characteristics are also described. Table of Contents: Introduction / Computer-aided Analysis of Images of the Retina / Detection of Geometrical Patterns / Datasets and Experimental Setup / Detection of the\\Optic Nerve Head\\Using the Hough Transform / Detection of the\\Optic Nerve Head\\Using Phase Portraits / Concluding Remarks
Author: Eddie Y. K. Ng Publisher: CRC Press ISBN: 1466559306 Category : Technology & Engineering Languages : en Pages : 412
Book Description
Digital fundus images can effectively diagnose glaucoma and diabetes retinopathy, while infrared imaging can show changes in the vascular tissues. Likening the eye to the conventional camera, Image Analysis and Modeling in Ophthalmology explores the application of advanced image processing in ocular imaging. This book considers how images can be used to effectively diagnose ophthalmologic problems. It introduces multi-modality image processing algorithms as a means for analyzing subtle changes in the eye. It details eye imaging, textural imaging, and modeling, and highlights specific imaging and modeling techniques. The book covers the detection of diabetes retinopathy, glaucoma, anterior segment eye abnormalities, instruments on detection of glaucoma, and development of human eye models using computational fluid dynamics and heat transfer principles to predict inner temperatures of the eye from its surface temperature. It presents an ultrasound biomicroscopy (UBM) system for anterior chamber angle imaging and proposes an automated anterior segment eye disease classification system that can be used for early disease diagnosis and treatment management. It focuses on the segmentation of the blood vessels in high-resolution retinal images and describes the integration of the image processing methodologies in a web-based framework aimed at retinal analysis. The authors introduce the A-Levelset algorithm, explore the ARGALI system to calculate the cup-to-disc ratio (CDR), and describe the Singapore Eye Vessel Assessment (SIVA) system, a holistic tool which brings together various technologies from image processing and artificial intelligence to construct vascular models from retinal images. The text furnishes the working principles of mechanical and optical instruments for the diagnosis and healthcare administration of glaucoma, reviews state-of-the-art CDR calculation detail, and discusses the existing methods and databases. Image Analysis and Modeling in Ophthalmology includes the latest research development in the field of eye modeling and the multi-modality image processing techniques in ocular imaging. It addresses the differences, performance measures, advantages and disadvantages of various approaches, and provides extensive reviews on related fields.
Author: Herbert Jelinek Publisher: CRC Press ISBN: 1420037005 Category : Technology & Engineering Languages : en Pages : 386
Book Description
Discusses the Effect of Automated Assessment Programs on Health Care ProvisionDiabetes is approaching pandemic numbers, and as an associated complication, diabetic retinopathy is also on the rise. Much about the computer-based diagnosis of this intricate illness has been discovered and proven effective in research labs. But, unfortunately, many of
Author: Mohammad Shorif Uddin Publisher: Springer Nature ISBN: 9811536074 Category : Technology & Engineering Languages : en Pages : 642
Book Description
This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2019), held at the University of Liberal Arts Bangladesh (ULAB), Dhaka, on 25–26 October 2019 and jointly organized by the University of Liberal Arts Bangladesh (ULAB), Bangladesh; Jahangirnagar University (JU), Bangladesh; and South Asian University (SAU), India. These proceedings present novel contributions in the areas of computational intelligence, and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.
Author: SINDHU SARANYA Publisher: Infinite Study ISBN: Category : Languages : en Pages : 10
Book Description
Segmenting blood vessel from the retinal image is important for detecting many retinal vascular disorders. Diseases which are all affecting the blood vessels of the eye are known as Retinal vascular disorders.
Author: Emanuele Trucco Publisher: Academic Press ISBN: 0081028164 Category : Computers Languages : en Pages : 504
Book Description
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
Author: Esra Ataer-Cansizoglu Publisher: ISBN: Category : Image analysis Languages : en Pages : 107
Book Description
The need for computerized analysis of retinal images has been increasing with the wide clinical use of fundus photography. Retinopathy of prematurity (ROP) is among the diseases that can be diagnosed through the use of retinal images. It is a disease affecting low-birth weight infants, in which blood vessels in the retina of the eye develop abnormally and cause potential blindness. We propose an image processing and machine learning framework from the vasculature segmentation to diagnosis of Retinopathy of Prematurity (ROP) in retinal images. The system takes a retinal image as an input, does automatic vessel segmentation and tracing, extracts various features, performs feature selection and outputs a diagnostic decision. Although, ROP is the leading cause of childhood blindness in the world, there exists a wide variability among experts in diagnosis. We propose a method to do an in-depth feature and observer analysis by employing Mutual Information (MI) to understand the underlying causes of inter-expert disagreement. The contributions of this dissertation are (i) extraction of new features quantifying tortuosity and amount of branching that are useful for ROP diagnosis, (ii) a novel feature representation paradigm utilizing Gaussian Mixture Models of image features to better model tortuous and straight vessels, (iii) an accurate pairwise similarity measure between images based on the proposed feature representation, (iv) the use of the proposed similarity measure in support vector machine (SVM) and k-nearest neighbor (KNN) classifiers, and (v) a MI-based feature-observer analysis technique to understand the features that lead inter-expert disagreement. The proposed framework is the first fully-automated computer-aided diagnosis system for ROP disease. The experiments are carried out on two datasets each of which consists of wide-angle colored retinal images acquired during routine ROP exams. The first one is designed for feature-observer analysis and consists of 34 images diagnosed by 22 experts. The second one is designed for classification experiments and contains 77 images with reference standard diagnosis. In our feature-observer analysis, we observed that although ROP is defined based on arteriolar tortuosity and venous dilation, there exists other features that highly correlate with expert opinions. This finding shows that the definition of the disease is subjective. We obtain 95\% accuracy compared to the reference standard on the second dataset when we use features extracted from manual segmentations. This performance is comparable to the performance of the individual experts (96%, 93%, 92%), Williams test = 1.0. With the features extracted from computer-based segmentation algorithm, we achieve 80% accuracy, which is promising for a fully-automated system.
Author: Ishmeet Kaur Publisher: Infinite Study ISBN: Category : Languages : en Pages : 7
Book Description
Diabetic Retinopathy is a disease which causes a menace to the eyesight. The detection of this at an early stage can aid the person from vision loss. The examination of retinal blood vessel structure can help to detect the disease, so segmentation of retinal blood vessel vasculature is important and is appreciated by the ophthalmologists
Author: Anchal Sharma
Author: Anchal Sharma
Author: Xiaolu Zhu
Author: Eddie Y. K. Ng
Author: Herbert Jelinek
Author: Mohammad Shorif Uddin
Author: Wei Huang
Author: SINDHU SARANYA 
Author: Emanuele Trucco
Author: Esra Ataer-Cansizoglu
Author: Ishmeet Kaur