Commercial volumetric MRI reporting tools in multiple sclerosis: a systematic review of the evidence

Z Mendelsohn, HG Pemberton, J Gray, O Goodkin… - Neuroradiology, 2023 - Springer
Purpose MRI is integral to the diagnosis of multiple sclerosis (MS) and is important for
clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the …

A review of self‐supervised, generative, and few‐shot deep learning methods for data‐limited magnetic resonance imaging segmentation

Z Liu, K Kainth, A Zhou, TW Deyer… - NMR in …, 2024 - Wiley Online Library
Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with
applications in disease diagnostics, intervention, and treatment planning. Accurate MRI …

Multi-stage semi-supervised learning enhances white matter hyperintensity segmentation

KTN Duarte, AS Sidhu, MC Barros… - Frontiers in …, 2024 - frontiersin.org
Introduction White matter hyperintensities (WMHs) are frequently observed on magnetic
resonance (MR) images in older adults, commonly appearing as areas of high signal …

Specialized gray matter segmentation via a generative adversarial network: application on brain white matter hyperintensities classification

MB Bawil, M Shamsi, AS Bavil… - Frontiers in Neuroscience, 2024 - frontiersin.org
Background White matter hyperintensities (WMH) observed in T2 fluid-attenuated inversion
recovery (FLAIR) images have emerged as potential markers of neurodegenerative …

[HTML][HTML] A fully automated visual grading system for white matter hyperintensities of T2-fluid attenuated inversion recovery magnetic resonance imaging

ZH Rieu, REY Kim, M Lee, HW Kim, D Kim… - Journal of Integrative …, 2023 - imrpress.com
Background: The Fazekas scale is one of the most commonly used visual grading systems
for white matter hyperintensity (WMH) for brain disorders like dementia from T2-fluid …

[HTML][HTML] Automatic segmentation of white matter hyperintensities in t2-flair with aqua: a comparative validation study against conventional methods

S Lee, ZH Rieu, REY Kim, M Lee, K Yen, J Yong… - Brain Research …, 2023 - Elsevier
White matter hyperintensities (WMHs) are lesions in the white matter of the brain that are
associated with cognitive decline and an increased risk of dementia. The manual …

Brain hyperintensities: automatic segmentation of white matter hyperintensities in clinical brain MRI images using improved deep neural network

PR Kumar, RK Jha, PA Kumar - The Journal of Supercomputing, 2024 - Springer
White matter hyperintensities (WMH) are commonly found in the brains of healthy elderly
individuals and have been associated with various neurological and geriatric disorders …

Application of artificial intelligence‐based magnetic resonance imaging in diagnosis of cerebral small vessel disease

X Hu, L Liu, M **ong, J Lu - CNS Neuroscience & Therapeutics, 2024 - Wiley Online Library
Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment,
and other diseases, and its early quantitative evaluation can significantly improve patient …

Quantitative Analysis of Multimodal MRI Markers and Clinical Risk Factors for Cerebral Small Vessel Disease Based on Deep Learning

Z Zhang, Z Ding, F Chen, R Hua, J Wu… - … Journal of General …, 2024 - Taylor & Francis
Background Cerebral small vessel disease lacks specific clinical manifestations, and
extraction of valuable features from multimodal images is expected to improve its diagnostic …

[HTML][HTML] Improved neurological diagnoses and treatment strategies via automated human brain tissue segmentation from clinical magnetic resonance imaging

PR Kumar, RK Jha, PA Kumar, BD Raju - Intelligent Medicine, 2024 - Elsevier
Objective Segmentation of medical images is a crucial process in various image analysis
applications. Automated segmentation methods excel in accuracy when compared to …