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A reliable and accurate method to measure the width of retinal blood vessel in fundus photography is proposed in this paper. Our approach is based on a graph-theoretic algorithm. The two boundaries of the same blood vessel are segmented simultaneously by converting the two-boundary segmentation problem into a two-slice, three-dimension surface segmentation problem, which is further converted into...
This article presents a novel photoreceptor detection algorithm applied to in-vivo Adaptive Optics (AO) images of the retina obtained from an advanced ophthalmic diagnosis device. Our algorithm is based on a recursive construction of thresholded connected components when the seeds of the recursions are the regional maxima of the image. This algorithm results in a labeling of the AO image which is...
This paper presents a novel unsupervised vascular segmentation algorithm which is applied to retinal fundus images, however could be generalised to any two-dimensional vascular image. The algorithm presents a new fully automatic framework for vessel segmentation and comprises the following features: novel application of the NPWindows method for intensity distribution estimation on localised `image...
Retinal image analysis is currently a very vivid field in biomedical image analysis. One of the most challenging tasks is the reliable automatic detection of microaneurysms (MAs). Computer systems that aid the automatic detection of diabetic retinopathy (DR) greatly rely on MA detection. In this paper, we present a method to construct an MA score map, from which the final MAs can be extracted by simple...
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging...
Fundus Fluorescein Angiography (FA) is a powerful tool for imaging and evaluating Diabetic Macular Edema (DME), where the fluorescein dye leaks and accumulates in the diseased areas. Currently, the assessment of FA images is qualitative and suffers from large inter-observer variability. A necessary step towards quantitative assessment of DME is automatic segmentation of fluorescein leakage. In this...
Choroidal Neovascularization (CNV) is a severe retinal disease characterized by abnormal growth of blood vessels in the choroidal layer. Current diagnosis of CNV depends mainly on qualitative assessment of a temporal sequence of fundus fluorescein angiography images. Automated segmentation and identification of the CNV lesion types (either occult or classic) is required to reduce the inter-and intra-...
The proper segmentation of the vascular system of the retina currently attracts wide interest. As a precious outcome, a successful segmentation may lead to the improvement of automatic screening systems. Namely, the detection of the vessels helps the localization of other anatomical parts and lesions besides the vascular disorders. In this paper, we recommend a novel approach for the segmentation...
Analyzing high-resolution images of astrocytes is important in understanding the diseases, such as glaucoma and retinal detachment, to which astrocytes are known to become reactive. This is challenging because the cells are small, homogeneous, and closely packed. We propose an interactive visualization system designed for such images. Our system employs a probabilistic segmentation algorithm to help...
The morphology of retinal blood vessels contains valuable information for the diagnosis of retinal dysfunctions. The vessels can be segmented from color fundus images but the connectivity of the segmented vessels is not always preserved because of low contrast, imaging noise and artifacts. If a continuous vessel is interpreted as multiple disjoint vessel segments, the morphological measurements such...
Clinical research suggests that changes in the retinal blood vessels (e.g., vessel caliber) are important indicators for earlier diagnosis of diabetes and cardiovascular diseases. Reliable vessel detection or segmentation is a prerequisite for quantifiable retinal blood vessel analysis for predicting these diseases. However, the segmentation of blood vessels is complicated by its huge variations such...
Image analysis is becoming increasingly prominent as a non intrusive diagnosis in modern ophthalmology. Blood vessel morphology is an important indicator for diseases like diabetes, hypertension and retinopathy. This paper presents an automated and unsupervised method for retinal blood vessels segmentation using the graph cut technique. The graph is constructed using a rough segmentation from a pre-processed...
Image segmentation is a method which is widely used in image processing application, and it is one of the most difficult steps of the process. This matter becomes more significant when we try to use the algorithms presented in complicated systems, such as the biometric systems. Different methods of iris segmentation have been presented so far. In this article, a new algorithm has been proposed for...
Vessel segmentation is very important in an automatic screening system for fundus images. Vessels are often segmented and removed from retinal images before the other residual lesions are detected. Incomplete vessel removal usually causes a false positive in lesion detection, especially for Microaneurysms detection. Segmenting vessels in spatial image domain makes miss detection due to non illumination...
Retinal images are used for the automated diagnosis of diabetic retinopathy. The retinal image quality must be improved for the detection of features and abnormalities and for this purpose segmentation of retinal images is vital. In this paper, we present a novel automated approach for segmentation of colored retinal images. Our segmentation technique smoothes and strengthens images by separating...
Automated segmentation of blood vessels in retinal images will help eye care specialists screen larger populations for vessel abnormalities. However, automated retinal segmentation is complicated by the fact that a number of vessels are very thin and the local contrast is low. We propose the radial projection method to locate the vessel centerlines which contains the thin vessels. Then the aggregate...
An automated system for screening and diagnosis of diabetic retinopathy should segment blood vessels from colored retinal image to assist the ophthalmologists. We present a method for blood vessel enhancement and segmentation. This paper proposes a wavelet based method for vessel enhancement, piecewise threshold probing and adaptive thresholding for vessel localization and segmentation respectively...
Age-related macular degeneration (AMD) with the complication of choroidal neovascularization (CNV) has been the major cause of severe, irreversible vision loss in many developed countries. The imaging modality that is commonly used to reveal the vascular abnormalities of CNV is fluorescein angiography (FA). Analysis and interpretation of FA sequences are largely performed by skilled observers on single...
Fluorescein angiograms of the human retina are widely used in the diagnosis and treatment of several diseases such as diabetic retinopathy and age relate macular degeneration. They analyze the micro circulation of the retina and choroid. Hence, accurate extraction of the vascular tree network is of crucial importance. Previous approaches to retinal vessel extraction assume either bright vessels on...
This paper presents an automatic optic disc (OD) detection technique. Given a retinal image, the proposed method first estimates a retinal background surface through an iterative Savitzky-Golay smoothing procedure. The OD is then detected through the global thresholding of the difference between the retinal image and the estimated background surface. Finally, an OD boundary is determined after a pair...
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