Deep learning for multiple sclerosis lesion classification and stratification using MRI.

Journal: Computers in biology and medicine
Published Date: Apr 24, 2025

Abstract

BACKGROUND AND OBJECTIVE: Multiple sclerosis (MS) is a chronic neurological disease characterized by inflammation, demyelination, and neurodegeneration within the central nervous system. Conventional magnetic resonance imaging (MRI) techniques often struggle to detect small or subtle lesions, particularly in challenging regions such as the cortical gray matter and brainstem. This study introduces a novel deep learning-based approach, combined with a robust preprocessing pipeline and optimized MRI protocols, to improve the precision of MS lesion classification and stratification.

Authors

  • Sabina Umirzakova
    Department of Computer Engineering, Gachon University, Sujeong-gu, Seongnam-si, 461-701, Gyeonggi-do, South Korea.
  • Muksimova Shakhnoza
    Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea.
  • Mardieva Sevara
    Department of IT Convergence Engineering, Gachon University, Seongnam, South Korea.
  • Taeg Keun Whangbo
    Department of Computer Science, Gachon University, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do 461-701, Korea.

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