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In this paper, we propose a new segmentation algorithm that combines a graph-based shape model with image cues based on boosted features. The landmark-based shape model encodes prior constraints through the normalized Euclidean distances between pairs of control points, alleviating the need of a large database for the training. Moreover, the graph topology is deduced from the dataset using manifold...
The spinal cord is a vital organ that serves as the only communication link between the brain and the various parts of the body. It is vulnerable to traumatic spinal cord injury and various diseases such as tumors, infections, inflammatory diseases and degenerative diseases. The exact segmentation and localization of the spinal cord are essential to effective clinical management of such conditions...
A fast global minimization segmentation model based on total variation is presented around Functional modeling and algorithm constructing. Firstly, a new active contour model is developed by maximum a-posterior probability (MAP), and a total variation model based on gradient information is constructed by the hint of geodesic active contour (GAC) model. So the improved M-S segmentation model is given...
We present an iterative model-constrained graph-cut algorithm for the segmentation of Abdominal Aortic Aneurysm (AAA) thrombus. Given an initial segmentation of the aortic lumen, our method automatically segments the thrombus by iteratively coupling intensity-based graph min-cut segmentation and geometric parametric model fitting. The geometric model effectively constrains the graph min-cut segmentation...
This paper presents the work of establishing Chinese human voxel model on basis of Chinese Visible Human database. The original data are segmented by the experienced operators. The head of the female model is introduced as the example. Work for plan of segmentation, 2D-3D re-construction and evaluation for EMF exposure have been presented in details. The same configuration has been applied for the...
In this paper, we simplify the model of local binary model and propose an improved region-based active contour model for medical image segmentation. Our model combines the advantages of the simplification of local binary fitting model by taking the local intensity information and the speed function using the minimal variance term, which enable the model to cope with intensity inhomogeneity. We define...
We propose a novel representation of shape variation using diffusion wavelets, and a search paradigm based on local features. The representation can reflect arbitrary and continuous interdependencies in the training data. In contrast to state-of-the-art methods our approach during the learning stage optimizes the coefficients as well as the number and the position of landmarks using geometric constraints...
Multi-atlas segmentation has been proved to perform well in segmenting sub-cortical structures from images. In this work, we study different components of multi-atlas segmentation and propose new techniques to improve the segmentation accuracy. We found that the use of gradient information in addition to standard normalised mutual information increases the registration accuracy. We also studied different...
Morphometry of human magnetic resonance images (MRI) is the process of measuring structural variations that occur in the brain. Morphometrics provide a mechanism to monitor and relate structural changes of anatomy to the onset or progression of a disease. It is therefor a very important area of research, specifically since MRI sequences are non-invasive and can be acquired in-vivo. This paper addresses...
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