20 citations · 22 across the 6 of their papers we have counts for
6 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…
An explainable framework for the relationship between dementia and glucose metabolism patterns
C. Vázquez-García, F. J. Martínez-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…
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…
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…
A connection between the pattern classification problem and the General Linear Model for statistical inference
Juan Manuel Gorriz, SIPBA group, John Suckling
A connection between the General Linear Model (GLM) in combination with classical statistical inference and the machine learning (MLE)-based inference is described in this paper. F…
Statistical Agnostic Mapping: a Framework in Neuroimaging based on Concentration Inequalities
J M Gorriz, SiPBA Group, CAM neuroscience
In the 70s a novel branch of statistics emerged focusing its effort in selecting a function in the pattern recognition problem, which fulfils a definite relationship between the qu…