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Accurate 3D models of the human brain vessels can greatly help to diagnose serious diseases. Such models can be constructed by segmentation of 3D MRA images, especially the recently introduced high resolution 7T MRA. We propose a new two-step approach for fully automatic segmentation of 7T MRA images of the human cerebrovascular system. First, a 3D model-based approach is applied to segment thick...
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,...
In this paper, we propose a fully automatic method to segment bone compartments in magnetic resonance (MR) images of knee joints gathered from a public database for research on knee osteoarthritis (OA), the osteoarthritis initiative (OAI). Considering the fixed scanning parameters which include position and flexion of the knee joint, the proposed method efficiently utilizes both shape and intensity...
Liver segmentation on computed tomography (CT) images is a challenging task due to the anatomic complexity and the imaging system noises. In this paper a complex algorithm based on active contour is proposed to automatically extract the liver region in abdominal CT images. Combined with threshold segmentation, morphology image processing and active contour models, we can automatically extract the...
In diagnosing pulmonary diseases aided by computer, accurate segmentation of the airway tree from the CT images is the basis for subsequent processing and analyzing. It is still a challenging task due to the image noise, partial volume effect and texture similarity of the airway and parenchyma. In order to solve these problems, various algorithms have been proposed, among which the region growing...
In this paper we propose a fully automatic algorithm for coronary artery extraction from X-ray data (3D-CT scan, 64 detectors) based on the mathematical morphology techniques and guided by anatomical knowledge. Growing and thresholding methods, in their most general form, are not sufficient to extract only the whole coronary arteries, because of the properties of these images. Finding appropriate...
An automatic 3D segmentation based on fuzzy connectedness (FQ) is proposed for MRI brain images. The main contribution of the present paper includes two parts: the accurate extraction of brain tissues and the automatic selection of the seed of FC. The brain tissues are extracted through obtaining approximate region of brain tissues via improved region growing, choosing the optimal threshold value...
In this study, we propose an automatic method to extract the heart volume from the cardiac positron emission tomography (PET) transmission images. The method combines the automatic 3D segmentation of the transmission image using Markov random fields (MRFs) to surface extraction using deformable models. Deformable models were automatically initialized using the MRFs segmentation result. The extraction...
In this study, we propose an automatic method to extract the heart volume from the cardiac positron emission tomography (PET) transmission images. The method combines the automatic 3D segmentation of the transmission image using Markov random fields (MRFs) to surface extraction using deformable models. Deformable models were automatically initialized using the MRFs segmentation result. The extraction...
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