137 citations · 607 across the 38 of their papers we have counts for
41 papers
Representation Alignment from a Few Paired Data via Distilled Optimal Transport
Julien Kordes, Reuben Dorent
Aligning two independently pretrained unimodal encoders typically demands millions of paired examples. In this paper, we study the regime where only -- pairs are a…
Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior
Hugues Roy, Reuben Dorent, Ninon Burgos
Unsupervised anomaly detection (UAD) aims to localize abnormal regions in medical scans without pixel-level annotations. A typical strategy seeks to reconstruct a pseudo-healthy im…
SinkSLOT: Sinkhorn via Sparse Lifted Optimal Transport
Ian Hsieh, Soumya Snigdha Kundu, Tom Vercauteren +1
Entropic optimal transport (EOT) has been shown to offer a computationally tractable approximation to exact optimal transport. However, the standard Sinkhorn-Knopp algorithm has tw…
Disentangled Shared Representations Improve Morpho-Transcriptomic Integration
Julian Ostermaier, Swann Ruyter, Reuben Dorent +1
Spatial transcriptomics (ST) enables the simultaneous profiling of gene expression and tissue morphology, creating an opportunity to learn multimodal representations capturing shar…
SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Training
Romain Valabregue, Ines Khemir, Eric Badinet +3
Synthetic training has recently advanced brain MRI segmentation by enabling contrast-agnostic models trained entirely on generated data. However, most existing approaches rely on h…
Data-driven registration and modeling of brain deformation for image-guided neurosurgery
Tiago Assis, Colin P. Galvin, Joshua P. Castillo +12
Accurate compensation of brain deformation is critical for reliable image-guided neurosurgery. Surgical manipulation and tumor resection induce tissue motion, causing preoperative…