2.7k citations · 9.2k across the 86 of their papers we have counts for
18 papers · 1 filter
UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation
Jianghao Wu, Guotai Wang, Ran Gu +6
Domain Adaptation (DA) is important for deep learning-based medical image segmentation models to deal with testing images from a new target domain. As the source-domain data are us…
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…
DEEPBEAS3D: Deep Learning and B-Spline Explicit Active Surfaces
Helena Williams, João Pedrosa, Muhammad Asad +4
Deep learning-based automatic segmentation methods have become state-of-the-art. However, they are often not robust enough for direct clinical application, as domain shifts between…
Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In t…
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…
Deep Homography Prediction for Endoscopic Camera Motion Imitation Learning
Martin Huber, Sebastien Ourselin, Christos Bergeles +1
In this work, we investigate laparoscopic camera motion automation through imitation learning from retrospective videos of laparoscopic interventions. A novel method is introduced…
Synthetic white balancing for intra-operative hyperspectral imaging
Anisha Bahl, Conor C. Horgan, Mirek Janatka +10
Hyperspectral imaging shows promise for surgical applications to non-invasively provide spatially-resolved, spectral information. For calibration purposes, a white reference image…
Deep Reinforcement Learning Based System for Intraoperative Hyperspectral Video Autofocusing
Charlie Budd, Jianrong Qiu, Oscar MacCormac +7
Hyperspectral imaging (HSI) captures a greater level of spectral detail than traditional optical imaging, making it a potentially valuable intraoperative tool when precise tissue d…
LoViT: Long Video Transformer for Surgical Phase Recognition
Yang Liu, Maxence Boels, Luis C. Garcia-Peraza-Herrera +4
Online surgical phase recognition plays a significant role towards building contextual tools that could quantify performance and oversee the execution of surgical workflows. Curren…
Learning-based sound speed estimation and aberration correction in linear-array photoacoustic imaging
Mengjie Shi, Tom Vercauteren, Wenfeng Xia
Photoacoustic (PA) image reconstruction involves acoustic inversion that necessitates the specification of the speed of sound (SoS) within the medium of propagation. Due to the lac…
Text Promptable Surgical Instrument Segmentation with Vision-Language Models
Zijian Zhou, Oluwatosin Alabi, Meng Wei +2
In this paper, we propose a novel text promptable surgical instrument segmentation approach to overcome challenges associated with diversity and differentiation of surgical instrum…
DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images
Andres Diaz-Pinto, Pritesh Mehta, Sachidanand Alle +17
Automatic segmentation of medical images is a key step for diagnostic and interventional tasks. However, achieving this requires large amounts of annotated volumes, which can be te…
Hyperspectral Image Segmentation: A Preliminary Study on the Oral and Dental Spectral Image Database (ODSI-DB)
Luis C. Garcia-Peraza-Herrera, Conor Horgan, Sebastien Ourselin +2
Visual discrimination of clinical tissue types remains challenging, with traditional RGB imaging providing limited contrast for such tasks. Hyperspectral imaging (HSI) is a promisi…
Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation
Muhammad Asad, Helena Williams, Indrajeet Mandal +4
Existing interactive segmentation methods leverage automatic segmentation and user interactions for label refinement, significantly reducing the annotation workload compared to man…
VideoSum: A Python Library for Surgical Video Summarization
Luis C. Garcia-Peraza-Herrera, Sebastien Ourselin, Tom Vercauteren
The performance of deep learning (DL) algorithms is heavily influenced by the quantity and the quality of the annotated data. However, in Surgical Data Science, access to it is lim…
Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: Application to surgical imaging
Peichao Li, Muhammad Asad, Conor Horgan +3
Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snaps…
OpTaS: An Optimization-based Task Specification Library for Trajectory Optimization and Model Predictive Control
Christopher E. Mower, João Moura, Nazanin Zamani Behabadi +3
This paper presents OpTaS, a task specification Python library for Trajectory Optimization (TO) and Model Predictive Control (MPC) in robotics. Both TO and MPC are increasingly rec…