Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review

A Shoeibi, M Khodatars, M Jafari, P Moridian… - Computers in Biology …, 2021 - Elsevier
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI

C Zeng, L Gu, Z Liu, S Zhao - Frontiers in Neuroinformatics, 2020 - frontiersin.org
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …

Multiple sclerosis lesion analysis in brain magnetic resonance images: techniques and clinical applications

Y Ma, C Zhang, M Cabezas, Y Song… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central
nervous system, characterized by the appearance of focal lesions in the white and gray …

Triplanar U-Net with lesion-wise voting for the segmentation of new lesions on longitudinal MRI studies

S Hitziger, WX Ling, T Fritz, T D'Albis… - Frontiers in …, 2022 - frontiersin.org
We present a deep learning method for the segmentation of new lesions in longitudinal
FLAIR MRI sequences acquired at two different time points. In our approach, the 3D volumes …

Improving the detection of new lesions in multiple sclerosis with a cascaded 3D fully convolutional neural network approach

M Salem, MA Ryan, A Oliver, KF Hussain… - Frontiers in …, 2022 - frontiersin.org
Longitudinal magnetic resonance imaging (MRI) has an important role in multiple sclerosis
(MS) diagnosis and follow-up. Specifically, the presence of new lesions on brain MRI scans …

Coactseg: Learning from heterogeneous data for new multiple sclerosis lesion segmentation

Y Wu, Z Wu, H Shi, B Picker, W Chong, J Cai - International conference on …, 2023 - Springer
New lesion segmentation is essential to estimate the disease progression and therapeutic
effects during multiple sclerosis (MS) clinical treatments. However, the expensive data …

Multiple sclerosis lesion segmentation-a survey of supervised CNN-based methods

H Zhang, I Oguz - Brainlesion: Glioma, Multiple Sclerosis, Stroke and …, 2021 - Springer
Lesion segmentation is a core task for quantitative analysis of MRI scans of Multiple
Sclerosis patients. The recent success of deep learning techniques in a variety of medical …

New MS lesion segmentation with deep residual attention gate U-Net utilizing 2D slices of 3D MR images

B Sarica, DZ Seker - Frontiers in Neuroscience, 2022 - frontiersin.org
Multiple sclerosis (MS) is an autoimmune disease that causes lesions in the central nervous
system of humans due to demyelinating axons. Magnetic resonance imaging (MRI) is widely …

Deep learning based multiple sclerosis lesion detection utilizing synthetic data generation and soft attention mechanism

OZ Shmueli, C Solomon, N Ben-Eliezer… - Medical Imaging …, 2022 - spiedigitallibrary.org
In this work we focus on identifying healthy brain slices vs brain slices with Multiple sclerosis
(MS) lesions. MS is an autoimmune, demyelinating disease characterized by inflammatory …

[PDF][PDF] ISTANBUL TECHNICAL UNIVERSITY 击GRADUATE SCHOOL

B SARICA - 2023 - polen.itu.edu.tr
Multiple Sclerosis (MS) is a chronic inflammatory, immune-mediated, neurodegenerative,
and demyelinating disease that impacts the Central Nervous System (CNS)[1–3]. In MS, the …