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Multiple sclerosis is a chronic inflammatory disease of the central nervous system. Lesions detected by Magnetic resonance (MR) sequences not only confirme the diagnosis of MS, but let monitor them to determine the evolutionary state of the disease and to evaluate the therapeutic efficiency. Thus, the change in lesion load is a criterion determining the degree of progress of the disease in volume,...
Recent research agrees on the utility of fuzzy reasoning for the development of Decision Support Systems, which help to classify clinical data. In this context, methods or techniques for representing fuzzy terms in the form of interpretable fuzzy sets obtained from numerical data are strongly required. Typically, in medical settings, statistical data are available or can be obtained from rough data,...
In this study, a fuzzy clustering method has been proposed in order to segment brain tissues affected by the multiple sclerosis (MS). In traditional fuzzy clustering, the neighboring relations between pixels have not been taken account of. Additionally, the performance of the clustering reduces drastically because of the pixels having close gray levels due to noise. Therefore, in this study, a novel...
The diagnosis and monitoring of Multiple Sclerosis (MS) are very thorny tasks due to extremely variable and often quite subtle symptoms. The use of MR images as MS marker requires the expert's knowledge and intervention to classify MS lesions. In this respect, the paper proposes an evolutionary-fuzzy approach aimed at supporting the classification of lesions in the diagnosis and monitoring of MS....
Neurological diseases can cause atrophy of the corpus callosum resulting in a change in its size and shape. The measurement and analysis of this change is one of the goals of clinical research. We perform statistical analysis of the shape of the corpus callosum extracted from MR brain scans of a group of multiple sclerosis patients undergoing a longitudinal (serial) study. In contrast to the classical...
The location, size and shape of Multiple Sclerosis (MS) lesions are often used to diagnose and track disease progression. In order to effectively compare lesions in MRI stacks for the same patient imaged at intervals, these stacks must be aligned. This automatic alignment method was designed to minimize modification of segmented pixel values. The aligned lesion stacks can be browsed independently...
The location, size and shape of Multiple Sclerosis (MS) lesions are often used to diagnose and track disease progression. In order to effectively compare lesions in MRI stacks for the same patient imaged at intervals, these stacks must be aligned. This automatic alignment method was designed to minimize modification of segmented pixel values. The aligned lesion stacks can be browsed independently...
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)...
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