129 citations · 143 across the 13 of their papers we have counts for
7 papers · 1 filter
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…