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This research concerned one advanced methodology for automatic localization of brain tumors that could be imaged by Magnetic Resonance Image (MRI) modality. Such methodology could be based on Iterative closest point (ICP) matching technique by using axial MRI symmetry. The idea behind this work is to compare right and left hemispheres mirrored across a central axis. Indeed a healthy brain has a strong...
Medical image fusion of computer tomography (CT) and magnetic resonance imaging (MRI) is to obtain more information from the CT and MRI respectively. In this paper, we present a wavelet-based texture fusion of CT/MRI images. Wavelet transform is employed to extract energy and regional information entropy of texture features from images. In the process of fusion, we adopt the fusion rule of energy...
The clinical interpretation of breast MRI remains largely subjective, and the reported findings qualitative. Although the sensitivity of the method for detecting breast cancer is high, its specificity is poor. Computerised interpretation offers the possibility of improving specificity through objective quantitative measurement. This paper reviews the plethora of such features that have been proposed...
In this study the value of magnetic resonance image (MRI) shape and texture analysis was assessed in multiple sclerosis (MS) subjects, both in differentiating between normal or normal appearing and abnormal tissue and in assessing disease onset. Shape and texture analysis was carried out in normal brain white matter and lesions detected in transverse sections of T2-weighted magnetic resonance (MR)...
Objective: To investigate the differences of texture features among macroscopic lesion white matter (LWM), normal appearing white matter (NAWM) in magnetic resonance images (MRI) from patients with multiple sclerosis (MS) and normal white matter (NWM) from normal controls by gray-level difference statistics, and to detect the hidden abnormality of NAWM. Methods: T2-weighted MRI of 26 MS patients and...
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