Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
Brain atrophy assessment in multiple sclerosis: technical–and subject-related barriers for translation to real-world application in individual subjects
R Zivadinov, A Tranquille, JA Reeves… - Expert Review of …, 2024 - Taylor & Francis
Introduction Brain atrophy is a well-established MRI outcome for predicting clinical
progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at …
progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at …
Superpixel-ComBat modeling: A joint approach for harmonization and characterization of inter-scanner variability in T1-weighted images
CL Chen, ME Torbati, DS Minhas, CM Laymon… - Imaging …, 2024 - direct.mit.edu
T1-weighted imaging holds wide applications in clinical and research settings; however, the
challenge of inter-scanner variability arises when combining data across scanners, which …
challenge of inter-scanner variability arises when combining data across scanners, which …
[引用][C] Editorial for “Evaluating the Impact of Intracranial Volume Correction Approaches on the Quantification of Intracranial Structures: A Systematic Analysis”
T Yamamoto, T Okada - Journal of Magnetic Resonance …, 2024 - Wiley Online Library