activity
20232025
most citedUnified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations

17 citations · 19 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2025★ 1 cited

The Brain Resection Multimodal Image Registration (ReMIND2Reg) 2025 Challenge

Reuben Dorent, Laura Rigolo, Colin P. Galvin +8

Accurate intraoperative image guidance is critical for achieving maximal safe resection in brain tumor surgery, yet neuronavigation systems based on preoperative MRI lose accuracy…

cs.CV2024★ 1 cited

Unified Cross-Modal Medical Image Synthesis with Hierarchical Mixture of Product-of-Experts

Reuben Dorent, Nazim Haouchine, Alexandra Golby +3

We propose a deep mixture of multimodal hierarchical variational auto-encoders called MMHVAE that synthesizes missing images from observed images in different modalities. MMHVAE's…

cs.CV2024

Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound

Hassan Rasheed, Reuben Dorent, Maximilian Fehrentz +6

We propose in this paper a texture-invariant 2D keypoints descriptor specifically designed for matching preoperative Magnetic Resonance (MR) images with intraoperative Ultrasound (…

cs.CV2023

Learning Expected Appearances for Intraoperative Registration during Neurosurgery

Nazim Haouchine, Reuben Dorent, Parikshit Juvekar +5

We present a novel method for intraoperative patient-to-image registration by learning Expected Appearances. Our method uses preoperative imaging to synthesize patient-specific exp…

cs.CV2023★ 17 cited

Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations

Reuben Dorent, Nazim Haouchine, Fryderyk Kögl +9

We introduce MHVAE, a deep hierarchical variational auto-encoder (VAE) that synthesizes missing images from various modalities. Extending multi-modal VAEs with a hierarchical laten…