347 citations · 957 across the 15 of their papers we have counts for
16 papers
CLABTOOLKIT: An Open-Source Toolkit for Routine Processing, Manipulation, and Visualization of Neuroimaging Data
Yasser Alemán-Gómez, Nino Hervé, Patric Hagmann
Neuroimaging research requires manipulating heterogeneous data structures, including raw MRI volumes, volumetric parcellations, cortical surface meshes, tractograms, and connectivi…
The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information
D. Abler, O. Pusterla, A. Joye-Kühnis +19
Background: Radiomics shows promise in characterizing glioblastoma, but its added value over clinical and molecular predictors has yet to be proven. This study assessed the added v…
Weakly Supervised Learning with Automated Labels from Radiology Reports for Glioma Change Detection
Tommaso Di Noto, Meritxell Bach Cuadra, Chirine Atat +5
Gliomas are the most frequent primary brain tumors in adults. Glioma change detection aims at finding the relevant parts of the image that change over time. Although Deep Learning…
FaBiAN: A Fetal Brain magnetic resonance Acquisition Numerical phantom
Hélène Lajous, Christopher W. Roy, Tom Hilbert +16
Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health lat…
Towards automated brain aneurysm detection in TOF-MRA: open data, weak labels, and anatomical knowledge
Tommaso Di Noto, Guillaume Marie, Sebastien Tourbier +6
Brain aneurysm detection in Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) has undergone drastic improvements with the advent of Deep Learning (DL). However, performances…
An anatomically-informed 3D CNN for brain aneurysm classification with weak labels
Tommaso Di Noto, Guillaume Marie, Sébastien Tourbier +5
A commonly adopted approach to carry out detection tasks in medical imaging is to rely on an initial segmentation. However, this approach strongly depends on voxel-wise annotations…