99 citations · 369 across the 31 of their papers we have counts for
5 papers · 1 filter
OOD-SEG: Exploiting out-of-distribution detection techniques for learning image segmentation from sparse multi-class positive-only annotations
Junwen Wang, Zhonghao Wang, Oscar MacCormac +2
Despite significant advancements, segmentation based on deep neural networks in medical and surgical imaging faces several challenges, two of which we aim to address in this work.…
Scribble-Based Interactive Segmentation of Medical Hyperspectral Images
Zhonghao Wang, Junwen Wang, Charlie Budd +3
Hyperspectral imaging (HSI) is an advanced medical imaging modality that captures optical data across a broad spectral range, providing novel insights into the biochemical composit…
A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging
Peichao Li, Oscar MacCormac, Jonathan Shapey +1
Hyperspectral imaging holds promises in surgical imaging by offering biological tissue differentiation capabilities with detailed information that is invisible to the naked eye. Fo…
ReCAP: Recursive Cross Attention Network for Pseudo-Label Generation in Robotic Surgical Skill Assessment
Julien Quarez, Marc Modat, Sebastien Ourselin +2
In surgical skill assessment, the Objective Structured Assessments of Technical Skills (OSATS) and Global Rating Scale (GRS) are well-established tools for evaluating surgeons duri…
Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
Dominic LaBella, Valeriia Abramova, Mehdi Astaraki +102
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional da…