Feature Studies in AI-Driven Neuroimaging

Dear Colleagues,

Neuroimaging plays a central role in the diagnosis, monitoring and management of neurological conditions. Advances in artificial intelligence (AI), including machine learning and deep learning, are rapidly reshaping how imaging data are acquired, processed and interpreted. These developments offer opportunities to improve diagnostic accuracy, workflow efficiency and clinical decision-making. At the same time, they raise important questions around reliability, interpretability and integration into real-world practice.

This Special Issue aims to bring together current research that examines how AI is being applied within neuroimaging and how these applications translate into clinical and research settings. The focus is on practical and clinically relevant contributions that move beyond technical performance to consider implementation, evaluation and impact.

We welcome original research articles and reviews that address, but are not limited to, the following areas:

• AI-assisted image acquisition, reconstruction and enhancement
• Automated detection, segmentation and classification of neurological conditions
• AI in stroke, neurodegeneration, oncology and brain injury imaging
• Validation, reproducibility and generalisability of AI models

By focusing on both innovation and application, this Special Issue aims to support the responsible integration of AI into neuroimaging and contribute to improved patient care and clinical practice.

We look forward to receiving your contributions.

Dr. Shayne Chau
Dr. Kelly Bentley-Spuur
Guest Editors

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