4 papers
A continually expandable foundation model for brain MRI
Michail Mamalakis, Carmen Jimenez-Mesa, Yonghao Li +8
Brain magnetic resonance imaging (MRI) is central to neuroscience and clinical assessment, but models are commonly developed for individual diseases, populations or imaging protoco…
Latent space projections and atlases: A cautionary tale in deep neuroimaging using autoencoders
J. M. Gorriz, F. Segovia, C. Jimenez +5
This study introduces a deep learning framework for the inferential exploration of latent representations in 3D brain MRI, leveraging a simple convolutional autoencoder with a hier…
An explainable framework for the relationship between dementia and glucose metabolism patterns
C. Vázquez-GarcÃa, F. J. MartÃnez-Murcia, F. Segovia Román +6
High-dimensional neuroimaging data presents challenges for assessing neurodegenerative diseases due to complex non-linear relationships. Variational Autoencoders (VAEs) can encode…
Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods
Carmen Jimenez-Mesa, Yizhou Wan, Guilio Sansone +7
Brain tumor resection is a highly complex procedure with profound implications for survival and quality of life. Predicting patient outcomes is crucial to guide clinicians in balan…