Machine learning approaches in study of multiple sclerosis disease through magnetic resonance images

F Moazami, A Lefevre-Utile, C Papaloukas… - Frontiers in …, 2021 - frontiersin.org
Multiple sclerosis (MS) is one of the most common autoimmune diseases which is commonly
diagnosed and monitored using magnetic resonance imaging (MRI) with a combination of …

An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor

M Sharif, J Amin, M Raza, M Yasmin… - Pattern Recognition …, 2020 - Elsevier
Tumor in brain is a major cause of death in human beings. If not treated properly and timely,
there is a high chance of it to become malignant. Therefore, brain tumor detection at an …

Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm

ESA El-Dahshan, HM Mohsen, K Revett… - Expert systems with …, 2014 - Elsevier
Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities
of physicians and reduce the time required for accurate diagnosis. The objective of this …

[HTML][HTML] Automated MS lesion detection and segmentation in clinical workflow: a systematic review.

F Spagnolo, A Depeursinge, S Schädelin, A Akbulut… - NeuroImage: Clinical, 2023 - Elsevier
Introduction: Over the past few years, the deep learning community has developed and
validated a plethora of tools for lesion detection and segmentation in Multiple Sclerosis …

[PDF][PDF] Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm

A El-Sayed, HM Mohsen, K Revett… - Expert systems with …, 2014 - academia.edu
abstract Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic
capabilities of physicians and reduce the time required for accurate diagnosis. The objective …

[PDF][PDF] Survey of brain tumor segmentation techniques on magnetic resonance imaging

M Hameurlaine, A Moussaoui - Nano Biomedicine and Engineering, 2019 - academia.edu
Brain tumor extraction is challenging task because brain image and its structure are
complicated that can be analyzed only by expert physicians or radiologist. Brain tumor …

Investigating efficient CNN architecture for multiple sclerosis lesion segmentation

A Fenneteau, P Bourdon, D Helbert… - Journal of Medical …, 2021 - spiedigitallibrary.org
Purpose: The automatic segmentation of multiple sclerosis lesions in magnetic resonance
imaging has the potential to reduce radiologists' efforts on a daily time-consuming task and …

Automatic brain tumor detection in medical imaging using machine learning

K Abbas, PW Khan, KT Ahmed… - … on information and …, 2019 - ieeexplore.ieee.org
The segmentation of brain tumor is a very crucial task for detecting the tumor in the early
stage. Many methods of brain tumor segmentation are available in the literature but none of …

Cerebrospinal fluid T1 value phantom reproduction at scan room temperature

A Yamashiro, M Kobayashi… - Journal of Applied Clinical …, 2019 - Wiley Online Library
The T1 value of pure water, which is often used as a phantom to simulate cerebrospinal
fluid, is significantly different from that of in‐vivo cerebrospinal fluid. The purpose of this …

A Bibliography of multiple sclerosis lesions detection methods using brain MRIs

A Shah, MS Al-Shaibani, M Ahmad… - arXiv preprint arXiv …, 2023 - arxiv.org
Introduction: Multiple Sclerosis (MS) is a chronic disease that affects millions of people
across the globe. MS can critically affect different organs of the central nervous system such …