MR Imaging in Screening, Prediction, and Follow-Up of Neurological Disorders
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".
Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 5467
Special Issue Editors
Interests: quantitative MR imaging; artificial intelligence in medicine; software devel-opment for diagnosis; screening; segmentation; etc.
Interests: ultra-high-field fMRI; automatic detection; presurgical planning; high-resolution fMRI; noise reduction in resting state fMRI
Special Issue Information
Dear Colleagues,
Neurological disorders cover a wide range of diseases, including brain tumors, epilepsy, multiple sclerosis, Parkinson’s disease, Alzheimer’s disease, learning disabilities, autism, cerebral palsy, etc. Despite important achievements in the field of the mentioned disorders, the main mechanisms of most are still unclear. Advances in magnetic resonance neuroimaging enable the development of novel approaches for investigating brain alternation with both structural and functional origins. The informative, meaningful, and descriptive information extracted from magnetic resonance imaging provides valuable knowledge about various neurological disorders, and plays an important role in the prognosis prediction of these disorders, and in early detection, screening, disease monitoring, assessing the treatment effects, managing the treatment, etc. In the present Special Issue entitled “MR Imaging in Screening, Prediction, and Follow-Up of Neurological Disorders” we intend to present an excellent overview of the current advanced methods that improve the quality of diagnosis and treatment in neurological disorders with the aid of magnetic resonance imaging approaches.
Dr. Hamidreza Saligheh Rad
Guest Editor
Dr. Vahid Malekian
Guest Editor Assistant
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Keywords
- neurological disorders
- neuroimaging
- functional magnetic resonance imaging
- diffusion tensor imaging
- brain connectivity
- artificial intelligence in neuroimaging
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