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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...
In this work, we present a novel content-based 3D shape retrieval system for Abdominal Aortic Aneurysm (AAA) rupture risk prediction. The algorithms incorporate shape context, RANdom SAmple Consensus (RANSAC) and thin plate spline (TPS) to achieve a reliable AAA rupture risk assessment system. Pre-labeled unruptured and ruptured cases (`-1' for unruptured and `1' for ruptured cases) are built and...
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...
Diabetic retinopathy is the commonest cause of blindness. Diabetes causes cataracts, Glaucoma and diabetic retinopathy. The Optic Disc is the exit point of retinal nerve fibers from the eye and the entrance and exit point for retinal blood vessels. The detection of Optic Disc is very essential to locate the various anatomical features in the retinal images. We describe a new filtering approach in...
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...
CTA technology is characterized by the higher clinically practical value in the inspection of the vascular diseases compared with other similar technologies. The bone-subtraction is the key method to improve the quality of CTA subtraction image and promotion of CTA technology. In this paper, a bone-subtraction method of the 3D CTA was proposed. The method includes a bone segmentation algorithm with...
Lobewise analysis of the pulmonary parenchyma is of clinical relevance for diagnosing and monitoring pathologies. In this work, a fully automatic lobe segmentation approach is presented, which is based on a previously proposed watershed transformation approach. The proposed extension explicitly considers the pulmonary fissures by including them in the cost image for the watershed segmentation. The...
The accuracy of the estimation of the aortic lumen area was investigated using an automated segmentation method (ART-FUN). The study included both Steady State Free Precession (SSFP) and Phase Contrast (PC) MR acquisition sequences. The precision of the segmented lumen area was tested against expert manual contouring for 860 aorta sections from three different MR scanners. Comparison of lumen areas...
Automatic or semi-automatic segmentation and tracking of artery trees from computed tomography angiography (CTA) is an important step to improve the diagnosis and treatment of artery diseases, but it still remains a significant challenging problem. In this paper, we present an artery extraction method to address the challenge. The proposed method consists of two steps: (1) a geometric moments based...
Geometric characteristics and arrangement of the cerebral vessels are assumed to be related to the development of vascular diseases. Identifying anatomical segments and bifurcations of the cerebral vasculature allows the comparison of these characteristics across and within subjects. In this paper, we focus on the automatic identification of internal carotid artery (ICA) from 3D rotational angiographic...
Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration. An extensive related literature often excludes the inherent heterogeneity of ophthalmic clinical images. The contribution of this paper consists...
Retinal blood vessels can give information about an abnormality or disease by examining its pathological changes. One of the abnormalities is diabetic retinopathy that is signed by a disorder of retinal blood vessels resulting from diabetes mellitus. Currently, diabetic retinopathy is one of major cause of human vision abnormalities or even blindness. Hence, early detection of such an abnormality...
The segmented blood vessel in retinal images is an important indicator in medical treatment. In 2007, Ricci and Perfetti proposed a simple and efficient blood vessel segmentation method based on line operator. However, this scheme makes some false segmentation when it is used to process the pixels which are close to a thick blood vessel. To overcome the above problem, a novel retinal blood vessel...
This paper addresses the detection and segmentation of vascular myocytes. The detection and segmentation of these cells are critical to the investigation of atherosclerosis among other cardiovascular diseases. Our approach to detection is unique in that it attempts to compute the underlying external energy in an active contour model. Isolines in this computed external energy can be employed to localize...
The categorization of retinal vessels morphological features and the investigation of their branching patterns are used in the process for automated diagnosis and screening of ophthalmologic diseases. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. In this paper, the performance comparison of two retinal vessel...
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