AI for open neuroimaging: opportunities and challenges from an open science perspective

Brisbane Convention & Exhibition Centre 

Recent advancements in large-scale brain imaging, combined with the rapid progress in deep learning and generative AI, are transforming our understanding of the human brain.
This convergence offers a unique opportunity to enhance cognitive abilities throughout the lifespan and to develop personalized, precise treatments for neurological disorders.
In this talk, I will explore how open science approaches—such as open datasets, open- source software, and collaborative tools—are driving the development and refinement of AI methods for brain imaging. These include applications in brain lesion segmentation, vision decoding, and the creation of brain foundation models.
I will discuss how open science fosters the reusability and reproducibility of AI-driven brain imaging analyses, while addressing key challenges, such as adaptation across diverse cohorts, database harmonization, cross-validation, hyperparameter optimization, and benchmark evaluation.
Open science is crucial for advancing AI applications in neuroscience and medicine, and it plays an essential role in overcoming current barriers to progress.