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Watershed transformation is a common technique for image segmentation. However, its use for medical image segmentation has been limited particularly due to over-segmentation. In response to the characteristics of medical image, especially the contour extraction from the MRI (Magnetic Resonance Imaging) brain image, this paper proposes an improved method in(More)
Ezrin primarily acts as a linker between the plasma membrane and the cytoskeleton and is a key component in tumor metastasis. In the present study, RNA interference (RNAi) using ezrin small hairpin RNAs (ezrin shRNAs) was used to define the roles of ezrin in the regulation of malignant behaviors of human breast cancer. The highly metastatic human breast(More)
To segment magnetic resonance image series is an interdisciplinary topic that involves both medical and computer science. It is one of the most important steps for medical diagnosis and quantitative analysis. This paper proposes an automatic segmentation method based on support vector machine (SVM). Feature vectors are generated according to both grayscale(More)
—Medical image registration is a critical step in medical image processing. In this paper, a mixed-type image registration approach is presented, which combines the segmentation-based and voxel-based registration. Firstly, the experimental images are preprocessed, including Digital Imaging and Communication of Medicine (DICOM) format conversion, denoising,(More)
Clustering is one of the most commonly data explorer techniques in Data Mining. K-harmonic means clustering (KHM) is an extension of K-means (KM) and solves the problem of KM initialization using a built-in boosting function. However, it is also suffering from running into local optima. As a stochastic global optimization technique, harmony search (HS) can(More)
Due to the importance of gene expression data in cancer diagnosis and treatment, microarray gene expression data have attracted more and more attentions from cancer researchers in recent years. However, in real-world computational analysis, such data common meet with the curse of dimensionality due to the tens of thousands of measures of gene expression(More)