21 citations · 54 across the 20 of their papers we have counts for
20 papers
Progressive Experience Fusion for Multi-Task World Model Control in Endovascular Navigation
Harry Robertshaw, Maxence Boels, Nikola Fischer +4
Autonomous endovascular navigation could support the delivery of mechanical thrombectomy to underserved areas, but controllers must navigate long, multi-stage paths across varying…
From Pre- to Intra-operative MRI: Predicting Brain Shift in Temporal Lobe Resection for Epilepsy Surgery
Jingjing Peng, Giorgio Fiore, Yang Liu +8
Introduction: In neurosurgery, image-guided Neurosurgery Systems (IGNS) highly rely on preoperative brain magnetic resonance images (MRI) to assist surgeons in locating surgical ta…
Localising under the drape: proprioception in the era of distributed surgical robotic system
Martin Huber, Nicola A. Cavalcanti, Ayoob Davoodi +15
Despite their mechanical sophistication, surgical robots remain blind to their surroundings. This lack of spatial awareness causes collisions, system recoveries, and workflow disru…
WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentation
Silin Cheng, Yang Liu, Xinwei He +3
Weakly supervised referring expression comprehension(WREC) and segmentation(WRES) aim to learn object grounding based on a given expression using weak supervision signals like imag…
Hydra: Marker-Free RGB-D Hand-Eye Calibration
Martin Huber, Huanyu Tian, Christopher E. Mower +4
This work presents an RGB-D imaging-based approach to marker-free hand-eye calibration using a novel implementation of the iterative closest point (ICP) algorithm with a robust poi…
UltraFlwr -- An Efficient Federated Surgical Object Detection Framework
Yang Li, Soumya Snigdha Kundu, Maxence Boels +6
Surgical object detection in laparoscopic videos enables real-time instrument identification for workflow analysis and skills assessment, but training robust models such as You Onl…
SWAG: Long-term Surgical Workflow Prediction with Generative-based Anticipation
Maxence Boels, Yang Liu, Prokar Dasgupta +2
While existing approaches excel at recognising current surgical phases, they provide limited foresight and intraoperative guidance into future procedural steps. Similarly, current…
SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation
Jiayu Huo, Sebastien Ourselin, Rachel Sparks
Medical image translation is crucial for reducing the need for redundant and expensive multi-modal imaging in clinical field. However, current approaches based on Convolutional Neu…
Self-supervised Brain Lesion Generation for Effective Data Augmentation of Medical Images
Jiayu Huo, Sebastien Ourselin, Rachel Sparks
Accurate brain lesion delineation is important for planning neurosurgical treatment. Automatic brain lesion segmentation methods based on convolutional neural networks have demonst…
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew +55
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable A…
Label merge-and-split: A graph-colouring approach for memory-efficient brain parcellation
Aaron Kujawa, Reuben Dorent, Sebastien Ourselin +1
Whole brain parcellation requires inferring hundreds of segmentation labels in large image volumes and thus presents significant practical challenges for deep learning approaches.…
RetiGen: A Framework for Generalized Retinal Diagnosis Using Multi-View Fundus Images
Ze Chen, Gongyu Zhang, Jiayu Huo +7
This study introduces a novel framework for enhancing domain generalization in medical imaging, specifically focusing on utilizing unlabelled multi-view colour fundus photographs.…
DDSB: An Unsupervised and Training-free Method for Phase Detection in Echocardiography
Zhenyu Bu, Yang Liu, Jiayu Huo +7
Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography. However, traditional methods face severa…
SuPRA: Surgical Phase Recognition and Anticipation for Intra-Operative Planning
Maxence Boels, Yang Liu, Prokar Dasgupta +2
Intra-operative recognition of surgical phases holds significant potential for enhancing real-time contextual awareness in the operating room. However, we argue that online recogni…
Generative Medical Segmentation
Jiayu Huo, Xi Ouyang, Sébastien Ourselin +1
Rapid advancements in medical image segmentation performance have been significantly driven by the development of Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs…
MatchSeg: Towards Better Segmentation via Reference Image Matching
Jiayu Huo, Ruiqiang Xiao, Haotian Zheng +3
Recently, automated medical image segmentation methods based on deep learning have achieved great success. However, they heavily rely on large annotated datasets, which are costly…
Motion-Boundary-Driven Unsupervised Surgical Instrument Segmentation in Low-Quality Optical Flow
Yang Liu, Peiran Wu, Jiayu Huo +7
Unsupervised video-based surgical instrument segmentation has the potential to accelerate the adoption of robot-assisted procedures by reducing the reliance on manual annotations.…
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks
Yang Liu, Xiaomin Yu, Gongyu Zhang +5
"A data scientist is tasked with developing a low-cost surgical VQA system for a 2-month workshop. Due to data sensitivity, she collects 50 hours of surgical video from a hospital,…
SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge
Dimitrios Psychogyios, Emanuele Colleoni, Beatrice Van Amsterdam +47
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to de…
LBR-Stack: ROS 2 and Python Integration of KUKA FRI for Med and IIWA Robots
Martin Huber, Christopher E. Mower, Sebastien Ourselin +2
The LBR-Stack is a collection of packages that simplify the usage and extend the capabilities of KUKA's Fast Robot Interface (FRI). It is designed for mission critical hard real-ti…