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Image segmentation is a very important pre-requisite in medical image analysis, therapy planning and CAD (Computer Aided Diagnose). Heart segmentation is a difficult task for its similarity in gray level with neighboring organs coursed by tissue conglutination and the complexity of anatomical configuration. Some earlier methods focused on the segmentation of parts of heart, e.g. ventricles, which...
This paper proposes the use of high-dimensional, point-based shape models for the study of phenotype, which offer some important advantages over traditional morphometries, including a more detailed representation of shape and a more systematic approach to shape statistics. Our approach allows for the analysis of shape at both global and local scales and can automatically extract lower- dimensional...
The traditional medical image fusion method based on pixel weighting has the problem how to obtain the deciding weights. Using the complementation of the CT and MRI images, an adaptive weighted method based on local priority is proposed. The local brightness and detail information of the two original images is considered and the local priority of the fused image is employed, the more raw information...
In this paper, we propose a novel multistage method for three-dimensional (3-D) segmentation of medical images and a new radial distance-based segmentation validation approach. For the 3-D segmentation method, we first employ a morphological recursive erosion operation to reduce the connectivity between the region of interest and its surrounding neighborhood; then we design a hybrid segmentation method...
Non-rigid image registration has been widely developed over the last years. However, many registration techniques do not take into account any a priori information on the structures in the images. We present in this article a general locally affine registration framework, which allows us to register local areas in the images using affine transformations having few degrees of freedom. Thanks to our...
Invasive intracranial electroencephalography (EEG) studies help identify the epileptogenic focus and assess if the identified zone overlies eloquent cortex by means of cortical stimulation. Proper interpretation and use of the intracranial recording/stimulation studies requires an effective display of multimodal information. We developed a software system which can combine the patient's segmented...
A novel implementation of watershed transform using a multi-degree immersion simulation is presented in this paper. The method is based on the improvement of traditional watershed by simulating immersion, which is originally proposed by Vincent & Soille in 1991. By changing the simulation procedure to multi-degree, which means the flood step is different on each degree of intensity, the proposed...
A new approach of medical image registration based on theories of mutual information and edge correlative deviation has been given in this paper. It takes advantage of the information contributed by the overall intensity values of original images as well as the correlation derived from the voxels' positions in edge images. It has been proven by tests that this new method inherits most merits of the...
We propose an image matching method based on cumulative distribution function (CDF). The CDF of the query and database images are approximated by piecewise linear models with two parameters, slope and intercept at various grayscale intervals. The equations solving the least squares line fitting algorithm are very simple to form, due to closed form expressions. The contiguous set of lines approximating...
In this paper, a framework combining the atlas registration and the fuzzy connectedness for the automatic segmentation of abdominal organs is proposed. First, a pre-labeled atlas is registered onto the subject to establish the proper correspondence between the atlas and subject. Second, we utilize the fuzzy connectedness framework to segment organs of interest from the subject image. Taking advantage...
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