60 citations · 61 across the 3 of their papers we have counts for
9 papers
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
Vien Ngoc Dang, Francesco Galati, Rosa Cortese +7
Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors…
A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments
Raphaël Sivera, Hervé Delingette, Marco Lorenzi +2
In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combi…
Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data
Clement Abi Nader, Nicholas Ayache, Philippe Robert +1
We introduce a probabilistic generative model for disentangling spatio-temporal disease trajectories from series of high-dimensional brain images. The model is based on spatio-temp…
Modeling and inference of spatio-temporal protein dynamics across brain networks
Sara Garbarino, Marco Lorenzi
Models of misfolded proteins (MP) aim at discovering the bio-mechanical propagation properties of neurological diseases (ND) by identifying plausible associated dynamical systems.…
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi +5
Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-te…
Disease Knowledge Transfer across Neurodegenerative Diseases
Razvan V. Marinescu, Marco Lorenzi, Stefano B. Blumberg +8
We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal bio…