An Automatic Multiple Sclerosis Lesion Segmentation Approach based on Cellular Learning Automata
نویسندگان
چکیده
منابع مشابه
Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images
Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...
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Accurate and consistent multiple sclerosis (MS) brain lesion segmentation and volumetry could be an added value to MS clinicians. In this paper, MSmetrix is presented, an automatic and reliable method, which uses 3D T1-weighted and FLAIR MR images in a probabilistic model to detect white matter lesions as an outlier with respect to the normal brain, while segmenting the brain tissue into grey m...
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Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed ...
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background: multiple sclerosis (ms) is a degenerative disease of central nervous system. ms patients have some dead tissues in their brains called ms lesions. mri is an imaging technique sensitive to soft tissues such as brain that shows ms lesions as hyper-intense or hypo-intense signals. since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2019
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2019.0100726