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In this paper, based on the ideas of image texture analysis and motion tracking, we present a new method for left ventricular (LV) strain analysis from cine magnetic resonance images(MRI). First, the marking points are extracted with the Harris corner detector on or close to the endocardium and epicardium. Second, using the tree-structured wavelet algorithm, the corresponding marking points are matched...
Based on contrast enhancement and texture analysis, an automatic segmentation of the left ventricle in 2D tagged MR images is presented in this paper. Incorporating histogram modification and local contrast enhancement is applied as a method for improving contrast between tagged lines and non-tagged tissue. The ventricular blood filled and tagged regions are isolated by subtracting gray minimum from...
In this paper, we propose a data-driven approach that extracts prior information for segmentation of the left ventricle in cardiac MR images of transplanted rat hearts. In our approach, probabilistic priors are generated from prominent features, i.e., corner points and scale-invariant edges, for both endo- and epi-cardium segmentation. We adopt a level set formulation that integrates probabilistic...
Data mining is an expanding research frontier that provides numerous efficient and scalable methods to extract patterns of interest in datasets. In this paper , Computer Aided Diagnosis ( CAD ) is applied to brain MRI image processing. Four features based on texture as proposed by Harlick are extracted and stored in a transactional database. The system is then trained with the proposed efficient associative...
In this paper we propose a new CAD (Computer Aided Diagnosis) system to classify patients with Alzheimer disease. Five textural features proposed by Harlick are extracted from the MRI scans which characterize the disease. An enhanced CBA algorithm is used to classify the images as Normal or Abnormal based on the rule set generated during the training phase. The experiments were conducted on OASIS...
Magnetic Resonance Imaging (MRI) is an important paraclinical tool for diagnosing Multiple Sclerosis (MS) and providing several markers of disease activity and evolution. Traditionally, hypointense lesions on Tl-weighted images have been reported to represent areas where demyelination and axonal loss have occurred, and are the images usually selected for segmenting the encephalic parenchyma. Based...
Mining brain tumors and tracking their growth trends in the course of magnetic resonance imaging is an important task that assists medical professionals to describe the appropriate treatment. Nevertheless, applying conventional techniques to carry out this process manually is time-consuming and often unreliable and insufficiently accurate. Automating this process is a challenging task due to the fact...
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