Neuroscience is undergoing a profound transformation aided by developments in artificial intelligence (AI), particularly in how brain imaging techniques are applied and interpreted.
AI algorithms have revamped traditional brain imaging modalities such as MRI and CT scans, enhancing image reconstruction capabilities and enabling quicker, more accurate comparisons of complex data. Furthermore, advances in deep learning now permit the extraction of intricate patterns from large volumes of imaging data, offering new insights into brain anomalies, functioning, and connectivity.
This Research Topic aims to explore and document the latest AI innovations in neuroscience imaging that are setting new benchmarks for analysing and understanding the brain. The focus is primarily on how these technologies can improve diagnostics, expand our understanding of neurological disorders, and offer advanced solutions for patient care.
To gain further insights in this rapidly evolving field, we welcome articles addressing, but not limited to, the following themes:
• Applications of AI in enhancing MRI, CT, and other traditional brain imaging techniques.
• Deep learning approaches for pattern recognition in neuroimaging data.
• Challenges and solutions in integrating AI with large-scale neuroimaging datasets.
• Case studies on the use of AI in detecting and monitoring neurological disorders.
• Future directions and potential innovations in AI-driven neuroscience imaging.
• These submissions may cover original research, review articles, case studies, and methodological advances in the field.
Keywords: Neuroimaging, EEG, Neural Network, Convolutional Neural Network, Deep Learning
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
