A survey of deep learning methods for multiple sclerosis identification using brain MRI images

M Sah, C Direkoglu - Neural Computing and Applications, 2022 - Springer
Multiple sclerosis (MS) is one of the most common inflammatory neurological diseases in
young adults. There are three types of MS:(1) In relapsing remitting MS (RRMS), people …

Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course–protocol for …

Y Statsenko, D Smetanina, T Arora, L Östlundh… - BMJ open, 2023 - bmjopen.bmj.com
Background The number of patients diagnosed with multiple sclerosis (MS) has increased
significantly over the last decade. The challenge is to identify the transition from relapsing …

Delve into Multiple Sclerosis (MS) lesion exploration: A modified attention U-Net for MS lesion segmentation in Brain MRI

M Hashemi, M Akhbari, C Jutten - Computers in Biology and Medicine, 2022 - Elsevier
Multiple Sclerosis (MS) is a Central Nervous System (CNS) disease that Magnetic
Resonance Imaging (MRI) system can detect and segment its lesions. Artificial Neural …

A framework for interactive medical image segmentation using optimized swarm intelligence with convolutional neural networks

C Kaushal, MK Islam, SA Althubiti… - Computational …, 2022 - Wiley Online Library
Recent improvements in current technology have had a significant impact on a wide range
of image processing applications, including medical imaging. Classification, detection, and …

Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection

S Krishnamoorthy, Y Zhang, S Kadry… - Computational …, 2023 - Wiley Online Library
Malfunctions in the immune system cause multiple sclerosis (MS), which initiates mild to
severe nerve damage. MS will disturb the signal communication between the brain and …

Enhancing multiple sclerosis diagnosis: A comparative study of electroencephalogram signal processing and entropy methods

U Aslan, MF Akşahin - Computers in Biology and Medicine, 2025 - Elsevier
As one of the most common neurodegenerative diseases, Multiple sclerosis (MS) is a
chronic immune-driven disorder that affects the central nervous system (CNS). Due to the …

Brain Lesion Segmentation using Deep Learning and its role in Computer-Aided Differential Diagnosis of Multiple Sclerosis and Neuromyelitis Optica

K Memon, N Yahya, S Siddiqui, H Hashim… - IEEE …, 2024 - ieeexplore.ieee.org
Neurological disorders are debilitating diseases and cause significant morbidity worldwide,
with some resulting in mortality. Magnetic Resonance Imaging (MRI) is the prime modality to …

Multiple sclerosis identification based on ensemble machine learning technique

S Jain, N Rajpal, J Yadav - … of the 2nd International Conference on …, 2020 - papers.ssrn.com
The diagnosis of multiple sclerosis disease (MSD) is crucial because it is a neurological
disease leading to communication failure between brain tissues and other parts of the body …

EFFICIENT SEGMENTATION MODEL USING MRI IMAGES AND DEEP LEARNING TECHNIQUES FOR MULTIPLE SCLEROSIS CLASSIFICATION

G Langat, B Zou, X Kui, K Njagi - International Journal for …, 2024 - dl.begellhouse.com
The segmentation models employing deep learning offer successful outcomes over multiple
medical image complex data resources and public data resources important for huge …

[PDF][PDF] An Efficient Multiple Sclerosis Segmentation Framework using Hybrid Dilated Convolution–based Adaptive Mobilenet Mechanism

G Langat, B Zou, X Kui, K Njagi - Journal of Electrical …, 2024 - pdfs.semanticscholar.org
Multiple Sclerosis (MS) is considered a very popular neurological condition in adults. Poor
walking stability is considered the primary sign of MS. The Magnetic Resonance Imaging …