137 citations · 607 across the 38 of their papers we have counts for
5 papers · 1 filter
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…
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…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
SegMatch: A semi-supervised learning method for surgical instrument segmentation
Meng Wei, Charlie Budd, Luis C. Garcia-Peraza-Herrera +3
Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted interventions. In this work, we propose Se…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…