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cs.CV2026
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…
cs.CV2024
Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks
Michail Mamalakis, Antonios Mamalakis, Ingrid Agartz +4
The accelerated progress of artificial intelligence (AI) has popularized deep learning models across various domains, yet their inherent opacity poses challenges, particularly in c…
cs.CV2023
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognition
Michail Mamalakis, Heloise de Vareilles, Atheer AI-Manea +8
The significant features identified in a representative subset of the dataset during the learning process of an artificial intelligence model are referred to as a 'global' explanat…