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In the recent years, reconstructing 3D liver and its vessels from abdominal CT volume images becomes an inevitable and necessary research field. In this paper, a method of 3D reconstruction of liver with its vessels has been implemented, which involves volume preprocessing, de-noising, segmentation, contouring, and combination of different modalities. An advanced liver segmentation algorithms have...
This paper introduces a novel procedure to segment retinal vessels using new technique namely Morphological Angular Scale-Space (MASS). Line structuring element is rotated about the seed point to determine the curvature of the vessels thereby ensuring that the components remains connected along vessels segmented. Scale-Space is created by varying the length of the structuring element which gradually...
In the context of vessel tree structures segmentation with implicit deformable models, we propose to exploit convolution surfaces to introduce a novel variational formulation, robust to bifurcations, tangential vessels and aneurysms. Vessels are represented by an implicit function resulting from the convolution of the centerlines of the vessels, modeled as a second implicit function, with localized...
Segmentation of cerebral vascular networks from 3D angiographic data remains a challenge. Automation generally induces a high computational cost and possible errors, while interactive methods are hard to use due to the dimension and complexity of images. This article presents a compromise between both approaches, by using the concept of example-based segmentation. Segmentation examples of vascular...
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...
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...
In this paper a method for segmentation of vessels in angiographic images is addressed. In this method for detecting the vessels in one angiographic frame, whole of angiographic frames in the sequence are utilized. For this purpose, firstly Hessian based vesselness filter is applied to the angiographic sequence to make discrimination between the vascular structures and the background. Afterward, the...
A new level-set based active contour method for the segmentation of small blood vessels and other elongated structures is presented. Its main particularity is the presence of a length increasing force in the contour driving equation. The effect of this force is to push the active contour in the direction of thin elongated shapes. Although the proposed force is not stable in general, our experiments...
Medical images enhanced at different scales have shown to give good results in mammogram enhancement, tumor classification, and lung nodule detection. However, the studies of multiscale analysis on retinal vasculature have been primarily limited to vessel segmentation. We propose using the Fourier Fractal dimension (FFD) to extract the complexity of the retinal vasculature enhanced at different wavelet...
A system for the automatic segmentation of the pulmonary vasculature in thoracic CT scans is presented. The method is based on a vesselness filter and includes a local thresholding procedure to accurately segment vessels of varying diameters. The output of an automatic segmentation of the airways is used to remove false positive detections in the airway walls. The algorithm is tested with a quantitative...
A novel segmentation algorithm for the detection of retinal vessels in funduscopic images is proposed, in which the benefits of both supervised and unsupervised methods are exploited. Ensemble learning based segmentation (ELBS) is employed for the segmentation of large and medium sized vessels, after which a local curve fitting technique is used for the detection of the thin retinal vessels. The general...
We present an approach for accurate localization of the neck of intracranial aneurysms and quantification of their geometry that is useful for their treatment through endovascular embolization. In particular, we first obtain a vessel segmentation using a topology-preserving level set method and extract the surface of the segmented vessel. We then separate the aneurysm from the parent vessels and localize...
This paper proposes a method to extract vessel trees by continually extending detected branches with locally optimal paths. Our approach uses a cost function from a multiscale vessel enhancement filter. Optimal paths are selected based on rules that take into account the geometric characteristics of the vessel tree. Experiments were performed on 10 low dose chest CT scans for which the pulmonary vessel...
State-of-the-art deformable registration algorithms do not perform as well with FA sequences because they are designed to deal with changes of content appearance (e.g., due to different sensors imaging the same organs) but not with content changes, which occur throughout a FA sequence as different portions or the vascular structure are visible (perfused) in different frames. This paper presents a...
The initial step of vessel segmentation in 3D is the detection of vessel centerlines. The proposed methods in literature are either dependent on vessel radius and/or have low response at vessel bifurcations. In this paper we propose a 3D tubular structure detection method that removes these two drawbacks. The proposed method exploits the observations on the eigenvalues of the Hessian matrix as is...
Vessel segmentation is an essential task in many computer-aided medical systems. However, the topology complexity of vascular structures and the intensity inhomogeneity of angiogram make it a challenging problem. We propose a level set based predictor-corrector algorithm to meet these challenges. In the predictor step, the overall contour of vessel structures is delineated by piecewise constant (PC)...
Microaneurysms (MAs) are the earliest sign of diabetic retinopathy and manifest as small reddish spots on the retina. Generally, algorithm design for MAs detection starts by separating the vascular system from the background for a posterior analysis of candidate MAs presence. Following this approach, this paper assesses three different methods for vessel segmentation and how they affect posterior...
Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing...
Retinal vessel segmentation is an essential step for the diagnoses of various eye diseases. An automated tool for blood vessel segmentation is useful to eye specialists for purpose of patient screening and clinical study. Vascular pattern is normally not visible in retinal images. In this paper, we present a method for enhancing, locating and segmenting blood vessels in images of retina. We present...
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