Advances of AI in Neuroimaging

Dear Colleagues,

Neuroimaging is a rapidly evolving field that involves the use of non-invasive imaging techniques to visualize and study the structure and function of the human brain. With the advent of artificial intelligence (AI), the field of neuroimaging has seen significant breakthroughs in terms of accuracy, speed, and efficiency in identifying various brain disorders. AI models have been widely applied in the analysis and interpretation of neuroimaging data, aiding researchers and clinicians to diagnose, treat, and monitor patients with neurological and psychiatric disorders. The aim of this research topic is to present advanced AI methods for application in neuroimaging techniques such as magnetic resonance imaging, positron emission tomography, and computed tomography. We are interested in understanding how AI models, coupled with neuroimaging, can advance our understanding of the human brain, its functions, and the mechanisms of brain diseases. We are also keen to know how AI methods in neuroimaging can be used in diagnosis, the improvement of patient care, cost reduction, the enhancement of clinical decision making, as well as the treatment and monitoring of patients with neurological and psychiatric disorders. In this research topic, we welcome original research papers or high-quality manuscripts focusing on the applications of AI methods in neuroimaging. Potential topics include, but are not limited to:

• AI methods for brain diagnosis and diseases outcome;
• AI in brain abnormality segmentations;
• Interpreting machine-learning models in neuroimaging;
• AI models in neurofeedback;
• AI models for neuroimaging-based biomarker discovery;
• Neuroimaging analysis.

Dr. Iman Beheshti
Dr. Daichi Sone
Prof. Dr. Carson Leung
Guest Editors

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