15 citations · 19 across the 4 of their papers we have counts for
6 papers
Supervised Tractogram Filtering using Geometric Deep Learning
Pietro Astolfi, Ruben Verhagen, Laurent Petit +5
A tractogram is a virtual representation of the brain white matter. It is composed of millions of virtual fibers, encoded as 3D polylines, which approximate the white matter axonal…
Automatic Tissue Segmentation with Deep Learning in Patients with Congenital or Acquired Distortion of Brain Anatomy
Gabriele Amorosino, Denis Peruzzo, Pietro Astolfi +4
Brains with complex distortion of cerebral anatomy present several challenges to automatic tissue segmentation methods of T1-weighted MR images. First, the very high variability in…
Tractogram filtering of anatomically non-plausible fibers with geometric deep learning
Pietro Astolfi, Ruben Verhagen, Laurent Petit +4
Tractograms are virtual representations of the white matter fibers of the brain. They are of primary interest for tasks like presurgical planning, and investigation of neuroplastic…
A Test for Shared Patterns in Cross-modal Brain Activation Analysis
Elena Kalinina, Fabian Pedregosa, Vittorio Iacovella +2
Determining the extent to which different cognitive modalities (understood here as the set of cognitive processes underlying the elaboration of a stimulus by the brain) rely on ove…
Anatomically-Informed Multiple Linear Assignment Problems for White Matter Bundle Segmentation
Giulia Bertò, Paolo Avesani, Franco Pestilli +3
Segmenting white matter bundles from human tractograms is a task of interest for several applications. Current methods for bundle segmentation consider either only prior knowledge…
Comparison of Distances for Supervised Segmentation of White Matter Tractography
Emanuele Olivetti, Giulia Bertò, Pietro Gori +2
Tractograms are mathematical representations of the main paths of axons within the white matter of the brain, from diffusion MRI data. Such representations are in the form of polyl…