129 citations · 143 across the 13 of their papers we have counts for
14 papers
Trusting the Inverse: Reliability-Aware Mapping for Simulation-Based Microstructure Estimation in Diffusion MRI
Juan Luis Villarreal Haro, Ileana Jelescu, Jean-Philippe Thiran +1
Diffusion-weighted MRI can probe tissue microstructure non-invasively, however interpreting microstructural parameter estimates remains challenging due to the intrinsic ambiguity o…
Exact analytical PGSE signal for diffusion confined to a cylindrical surface using a spectral Laplacian formalism
Erick J Canales-Rodríguez, Chantal M. W. Tax, Juan Manuel Górriz +3
Objective. To derive an exact analytical expression for the diffusion MRI signal arising from diffusion confined to a cylindrical surface under finite rectangular pulsed-gradient s…
Towards Early Detection: AI-Based Five-Year Forecasting of Breast Cancer Risk Using Digital Breast Tomosynthesis Imaging
Manon A. Dorster, Felix J. Dorfner, Mason C. Cleveland +6
As early detection of breast cancer strongly favors successful therapeutic outcomes, there is major commercial interest in optimizing breast cancer screening. However, current risk…
S-R2D2: a spherical extension of the R2D2 deep neural network series paradigm for wide-field radio-interferometric imaging
A. Tajja, A. Aghabiglou, E. Tolley +3
Recently, the R2D2 paradigm, standing for ''Residual-to-Residual DNN series for high-Dynamic-range imaging'', was introduced for image formation in Radio Interferometry (RI) as a l…
A diffusion MRI model for random walks confined on cylindrical surfaces: Towards non-invasive quantification of myelin sheath radius
Erick J Canales-Rodríguez, Chantal M. W. Tax, Elda Fischi-Gomez +3
Quantifying the myelin sheath radius of myelinated axons in vivo is important for understanding, diagnosing, and monitoring various neurological disorders. Despite advancements in…
Ground-truth effects in learning-based fiber orientation distribution estimation in neonatal brains
Rizhong Lin, Hamza Kebiri, Ali Gholipour +4
Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive method for depicting brain microstructure in vivo. Fiber orientation distributions (FODs) are mathematical representat…
What to align in multimodal contrastive learning?
Benoit Dufumier, Javiera Castillo-Navarro, Devis Tuia +1
Humans perceive the world through multisensory integration, blending the information of different modalities to adapt their behavior. Contrastive learning offers an appealing solut…
Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR-CSD) of Diffusion MRI Data
Ekin Taskin, Gabriel Girard, Juan Luis Villarreal Haro +4
Constrained Spherical Deconvolution (CSD) is widely used to estimate the white matter fiber orientation distribution (FOD) from diffusion MRI data. Its angular resolution depends o…
PIV3CAMS: a multi-camera dataset for multiple computer vision problems and its application to novel view-point synthesis
Sohyeong Kim, Martin Danelljan, Radu Timofte +2
The modern approaches for computer vision tasks significantly rely on machine learning, which requires a large number of quality images. While there is a plethora of image datasets…
Uncertainty modeling for fine-tuned implicit functions
Anna Susmelj, Mael Macuglia, Nataša Tagasovska +4
Implicit functions such as Neural Radiance Fields (NeRFs), occupancy networks, and signed distance functions (SDFs) have become pivotal in computer vision for reconstructing detail…
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran +1
Recent test-time adaptation methods heavily rely on nuanced adjustments of batch normalization (BN) parameters. However, one critical assumption often goes overlooked: that of inde…
Pore size estimation in axon-mimicking microfibres with diffusion-relaxation MRI
Erick J. Canales-Rodríguez, Marco Pizzolato, Feng-Lei Zhou +5
Purpose: This study aims to evaluate two distinct approaches for fibre radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfibre phantoms that mimic h…
Cross-Age and Cross-Site Domain Shift Impacts on Deep Learning-Based White Matter Fiber Estimation in Newborn and Baby Brains
Rizhong Lin, Ali Gholipour, Jean-Philippe Thiran +3
Deep learning models have shown great promise in estimating tissue microstructure from limited diffusion magnetic resonance imaging data. However, these models face domain shift ch…
Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity
Richard F. Betzel, Alessandra Griffa, Andrea Avena-Koenigsberger +4
The human connectome has been widely studied over the past decade. A principal finding is that it can be decomposed into communities of densely interconnected brain regions. This r…