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

17 citations · 20 across the 10 of their papers we have counts for

collaborators

10 papers

eess.IV2025

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51

Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…

eess.IV2025

When Experts Disagree: Characterizing Annotator Variability for Vessel Segmentation in DSA Images

M. Geshvadi, G. So, D. D. Chlorogiannis +12

We analyze the variability among segmentations of cranial blood vessels in 2D DSA performed by multiple annotators in order to characterize and quantify segmentation uncertainty. W…

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

Intraoperative Registration by Cross-Modal Inverse Neural Rendering

Maximilian Fehrentz, Mohammad Farid Azampour, Reuben Dorent +7

We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural…

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 (…

eess.IV2024

Patient-Specific Real-Time Segmentation in Trackerless Brain Ultrasound

Reuben Dorent, Erickson Torio, Nazim Haouchine +5

Intraoperative ultrasound (iUS) imaging has the potential to improve surgical outcomes in brain surgery. However, its interpretation is challenging, even for expert neurosurgeons.…

eess.IV2024★ 1 cited

Registration of Longitudinal Spine CTs for Monitoring Lesion Growth

Malika Sanhinova, Nazim Haouchine, Steve D. Pieper +11

Accurate and reliable registration of longitudinal spine images is essential for assessment of disease progression and surgical outcome. Implementing a fully automatic and robust r…

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…