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For automatic screening of eye diseases, it is very important to segment regions corresponding to the different eye-parts from the fundal images. A challenging task, in this context, is to segment the network of blood vessels. The blood vessel network runs all along the fundal image, varying in density and fineness of structure. Besides, changes in illumination, color and pathology also add to the...
The proliferation of blood vessels originating from the choroid area causing a rupture in the Bruch membrane hooked on the sub-retinal pigment epithelium (sub-RPE) leads to Choroidal Neovascularization (CNV). The need for texture analysis and quantification rises due to the prediction of prevalence of CNV in near future. Improvement to conventional Covering Blanket method gave us better results for...
In this paper we present a novel method for the automatic location and segmentation of the optical disk in fundus images. It is based on the decoupling of vessel and background information obtained with morphological segmentation and inpainting. A multiresolution optimization scheme finding elliptic contours optimally adapted to a brightness model is then applied on the inpainted brightness image,...
Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus...
Segmentation of 3D cerebral vasculature is important for clinical diagnosis. However, many relevant thin vessels are not visible in 1.5T and 3T MRA. With the recent introduction of 7T MRA, images of higher resolution can be acquired, which contain much more thin vessels. We propose a fully automatic hybrid approach for segmenting vessels from 7T MRA images of the human cerebrovascular system. First,...
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...
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...
Vessel tracking is a topic that has had extensive coverage when dealing with high axial resolution data, obtained from modalities requiring patients to be exposed to greater levels of radiation dose, possibly to the detriment of their health[10]. The use of low axial resolution data such as multi-slice CT(MSCT) used in coronary artery disease screening is becoming widely used clinically to provide...
Enhancement of vessels in medical images is still an unsolved problem. Multiscale approaches were proposed to improve the vessel enhancement effect based on the structure size and image resolution. Vessel enhancing diffusion (VED) filter is one of the multiscale approaches, which was based on the scale space theory. VED performs well on enhancing vessel structures but cannot preserve complex structures...
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...
Segmentation of microcirculation is a major step in analyzing blood circulatory system. In this study, a method for segmentation of capillaries and small blood vessels in video recordings captured from lingual surface is presented. The main objective is to monitor and quantitatively assess the variations that occur in microcirculation over a period of treatment for diseases or during a resuscitation...
Diabetic retinopathy is a major cause of blindness. Earliest signs of diabetic retinopathy are damage to blood vessels in the eye and then the formation of lesions in the retina. This paper presents an automated method for the detection of bright lesions (exudates) in retinal images. In this work, an adaptive thresholding based on a novel algorithm for pure splitting of the image is proposed. A coarse...
Retinal vessels can show different states of several diseases, making the detection of vessels in retinal images very crucial. Retinal images can be used for other applications such as ocular fundus operations and human recognition. Due to the acquisition process, these images often have low grey level contrast and dynamic range that can seriously affect diagnosis procedure results. In this paper,...
Identification and characterization of diffuse parenchyma lung disease patterns challenges computer aided diagnosis (CAD) schemes in computed tomography (CT). Accuracy of these preprocessing stages is expected to influence the accuracy of lung CAD schemes. Although algorithms aimed at improving the accuracy of segmentation of lung fields in presence of DPLDs have been reported, the corresponding vessel...
Optical coherence tomography (OCT) is a rapidly emerging imaging modality that can provide non-invasive, cross-sectional, high-resolution images of tissue morphology in situ and in real-time. Previous studies have demonstrated that OCT can non-invasively visualize the pathological changes in the living kidney in real-time using the Munich-Wistar rat model. In this work, we demonstrate, for the first...
This paper presents a new method to segment thin tree structures, such as extensions of microglia and cardiac or cerebral blood vessels. The Fast Marching method allows the segmentation of tree structures from a single point chosen by the user when a priori information is available about the length of the tree. In our case, no a priori information about the length of the tree structure to extract...
Segmentation of blood vessels and extraction of their centerlines in 3D angiography are essential to diagnosis and prognosis of vascular diseases, and advanced image processing and analysis. In this paper, we propose a semi-automatic method to perform those two tasks simultaneously. A user supplies two end points to the algorithm and a vessel centerline between the two given points is extracted automatically...
Since myocardial motion is directly related to cardiac vascular supply, it can be helpful in diagnosing the heart abnormalities. The most comprehensive and available imaging study of the cardiac function is echocardiography and therefore it is important to make the echocardiography motion more quantitative. To overcome the sensitivity to shear, rotation and wide range of motion, we propose an adaptive...
A major problem of pulmonary nodules segmentation can't be solved well by conventional methods, which is other tissue in chest CT image slices, such as blood vessels and bronchi, often overlap with the nodules and they also have the same gray scale intensity approximately, for big size (>40pixels) nodules especially. This paper presents a novel approach to solve above problem, which works in two...
In this paper, we proposed a new scheme for detection of small blood vessels in retinal images. A novel filter called Gabor variance filter and a modified histogram equalization technique are developed to enhance the contrast between vessels and background. Vessel segmentation is then performed on the enhanced map using thresholding and branch pruning based on the vessel structures. The experiments...
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