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The optic disc (OD) segmentation in an retinal image is prerequisite for an computerized detection of diabetic retinopathy and also for monitoring changes due to diseases such as glaucoma. The OD segmentation is also used for the detection of other anatomical structures like fovea and vascular tree. Many algorithms based on thresholding, active contour model, GVF snake and clustering have been proposed...
A method is proposed using image processing techniques, which is an automated method for detection of suspected glaucoma. In this paper an algorithm is proposed to detect suspected glaucoma by using the presence or absence of hemorrhages in a particular region, near the optic disc, in fundus image. Unlike existing methods, which only uses cup to disc ratio as a deciding parameter to detect glaucoma,...
Glaucoma is one among major causes of blindness in working population. Early detection of Glaucoma through automated retinal image analysis helps in preventing vision loss. Optic disk (OD) segmentation from retinal images is the preliminary step in developing the diagnostic tool for early Glaucoma detection. In this paper, we have presented a novel hierarchical technique for fast and accurate OD localization...
Astronomy is an observation-based discipline which can obtain the important information about target stars by their spectrum. The two-dimensional fiber spectra contains abundant astrophysical information which plays an important role in the digital sky survey. But, the source observed data must be processed by several procedures before being used by astronomers, and spectra extraction is one of the...
This work compares Triangle, Maximum Entropy and Mean Peak thresholding methods to locate the optic disc in color fundus images. Localizing the optic disc is a significant task in an automated retinal image analysis process as is used on most vessel segmentation, disease diagnostic, and retinal recognition algorithms. The DIARETDBv1 dataset includes 89 retinal images are used to evaluate the 3 thresholding...
Glaucoma, an eye disease, is often referred to as the silent thief of sight. The damage done by glaucoma is irreversible. Early detection and treatment of glaucoma is the only solution. Till date many works have been done towards automatic glaucoma detection using Color Fundus Images (CFI) and Optical Coherence Tomography (OCT) images by extracting structural features. Structural features can be extracted...
Glaucoma is the major cause of ocular damage and vision loss in which increased Intraocular Pressure (IOP) of the eye progressively damages the optic nerve. In this proposed study, an automatic system is developed for glaucoma detection by extracting various features like vertical Cup to Disc Ratio (CDR), Horizontal to Vertical CDR (H-V CDR), Cup to Disc Area Ratio(CDAR), and Rim to Disc Area Ratio...
The thickness of retinal nerve fibre layer (RNFL) is one of the parameters for assessing the Glaucoma. It is second largest disease which causes blindness. Glaucoma is caused due to the increase of intra ocular pressure (IOP). Vision is lost before the patient becomes aware of glaucoma. Optical Coherence Tomography (OCT) provides enhanced depth and clarity of viewing tissues with high resolution compared...
Retinal fundus image is a widely used image modality to diagnose ocular diseases such as glaucoma, age-related macular degeneration and diabetic retinopathy. There are a number of fundus image databases available online. However, most of them are used for blood vessel extraction and optic disc localization, and hardly any have optic cup annotation. In this paper, we present a fundus image database...
Detection of the optic cup, which is an excavation in the optic disc, is an essential step in glaucoma assessment. In digital fundus photography, which captures 2D images of the retina, identification of the optic cup can be challenging. Kinks are bendings of vessels as they traverse the optic cup boundary, and are used clinically to determine the location of the optic cup. In this paper, we propose...
The segmentation of the optic nerve fibers is important for the morphometry study of optic nerve. However, such studies are hampered by the thousands of fibers involved when manual segmentation has to be used. We have developed an automatic segmentation method which is principally based on improved Chan-Vese level set model which integrating myelin sheath intensity priority. Next, identify the axon...
The optic disc is an important feature in the retina. We propose a method for the detection of the optic disc based on a supervised learning scheme. The method employs pixel and local neighbourhood features extracted from the ROI of a digital retinal fundus photograph. A support vector machine based classification mechanism is used to classify each image point as belonging to the cup and retina. The...
Various morphological and functional techniques for retina examination have been established in the recent years. Although many examination results are spatially resolved and can be mapped onto data originating from other modalities, usually only data from one modality is analyzed by a clinician at a time. This is mainly because there is no software available to the public that enables the registration...
Optical coherence tomography (OCT) as a new imaging technology is gaining popularity in the diagnosis of ocular diseases. It enable clinicians to perform accurate, objective, and reproducible measurements of the retinal nerve fibre layer (RNFL) whose thickness is closely related to many ocular diseases. Automatic segmenting RNFL is a challenging image processing problem, which is a critical job for...
This paper presents a methodology for automatic initialization of a level-set segmentation algorithm to find the margin of the optic disc in fundus images as an indicator for glaucoma. Accurate segmentation of the optic disc is fundamental to the diagnosis and treatment of glaucoma. Our algorithm improves on previous applications by automatically finding the initialization points for ideal segmentation...
Freehand 3D ultrasound imaging has been growing in popularity. However, the unavoidable reconstruction errors introduced by freehand motion have limited its usefulness. To overcome this, freehand ultrasound systems have been augmented with external tracking sensors to produce accurate 3D images in mainly experimental settings, but these systems have yet to be accepted for general clinical use. In...
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