Using the fuzzy methods to examine changes in brain lesions and atrophy from MRI images for rapid diagnosis of MS

Subject Areas : Fuzzy logic, fuzzy set theory, and many-valued logic

Alireza Banitalebi Dehkordi ¹

1 -

Received: 2024-05-03 Accepted : 2024-06-10 Published : 2024-06-17

Keywords: MRI, Multiple sclerosis, Fuzzy method, Controlled watershed.,

Abstract :

Multiple sclerosis (MS) is a disease that affects the central nervous system, during which the myelin present on the nerve fibers that have a protective role is destroyed, and therefore the conduction of electric current is disturbed and the symptoms of MS disease appear. In this disease, the white blood cells that play a defensive role in the body attack the myelin, which is a protection for nerve fibers, as a foreign agent, and each time these blood cells attack the nerve fibers of one of the organs of the patient's body. Which is unclear, that organ will have problems. The best way to diagnose MS is to examine brain MRI images. Therefore, the existence of a fast and accurate method to evaluate changes in brain atrophy or the creation and increase of lesions (plaques) caused by this disease is a key component in diagnosing and evaluating the progress of the disease and the effectiveness of its treatment courses. Manual detection of changes in lesions (plaques) and brain atrophy caused by this disease usually requires a trained specialist and is very slow and difficult, and the results are somewhat subjective. Therefore, the existence of an automatic system for extracting and checking these changes is essential. Although many automatic methods have been proposed, the segmentation results are not accurate enough. As a result, there is a great need to develop a strong, fast, and accurate method to diagnose MS and brain lesions caused by it. In this article, by combining two fuzzy methods and the controlled watershed algorithm, we propose a fast method with high accuracy to diagnose MS from brain MR images

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