Modified Self-Organizing Map Algorithm for Brain Tumor Detection and Analysis Using Magnetic Resonance Brain Images
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Date
2019-06-30
Authors
Isselmou, Abd El Kader
Guizhi, Xu
Zhang, Shuai
Saminu, Sani
Journal Title
Journal ISSN
Volume Title
Publisher
Services for Science and Education, United Kingdom
Abstract
medical image processing play an important role to help radiologists and support their decisions in
diagnosis of the patient, magnetic resonance imaging (MRI) has ability to diagnosis the small details in the
human body with a high resolution; in this paper, we propose modified self-organizing map algorithm
(MSOM) for brain tumor detection and analysis using magnetic resonance brain images the significance
of the (MSOM) algorithm is ability to detect tumor area in the magnetic resonance brain image (MRI)
clearly with a high accuracy and best performance according of different values, the advantage of method
proposed can segment and detect different types of MRI brain images FLAIR, T1 and T2-weight images
with same performance and accuracy, the (MSOM) method start through input magnetic resonance brain
image (MRI) and preprocessing applied to remove the noise from the image, applied modified selforganizing map (MSOM), applied tumor area, performance of the method, finally the applied of modified
self-organizing map (MSOM) gave a best results us shown in the results.
Description
Keywords
MRI, brain tumor detection, modified self-organizing map, accuracy values