25 citations · 30 across the 15 of their papers we have counts for
17 papers
Autonomous Robotic Navigation for Endovascular Brain-Computer Interface Access
Harry Robertshaw, Weijie Qi, Nikola Fischer +3
Endovascular brain-computer interfaces (BCIs) avoid craniotomy but require precise device delivery through anatomically variable cerebral veins. This work presents the first demons…
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…
Vascular Geometry Characterization for AI-Based Endovascular Navigation
Han-Ru Wu, Harry Robertshaw, Lisa Dwyer-Joyce +2
Mechanical thrombectomy (MT) is a time-critical intervention for acute ischemic stroke; however, access remains limited due to a shortage of neuroradiologists and specialized cente…
Manual, Joystick, or Haptic Control? An In Vitro Comparison of Navigation Strategies for Robotic Interventional Neuroradiology Procedures
Benjamin Jackson, Nikola Fischer, Harry Robershaw +16
Objective: To evaluate robotic controller interfaces for interventional neuroradiology procedures in-vitro incorporating a force-sensing platform to assess safety. Methods: A custo…
Developing a novel Comorbidities Index for predicting 10-year mortality in Prostate Cancer patients: A computational data-driven approach
Davide Farinati, Francesco Barletta, Paolo Zaurito +6
The Charlson Comorbidities Index (CCI) is a weighted additive index widely used to estimate ten-year mortality risk, but its original weights may not reflect contemporary prognoses…
Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy
Harry Robertshaw, Yanghe Hao, Weiyuan Deng +6
Purpose: Mechanical thrombectomy (MT) improves stroke outcomes, but is limited by a lack of local treatment access. Widespread distribution of reinforcement learning (RL)-based rob…
Stabilizing Temporal Inference Dynamics for Online Surgical Phase Recognition
Yang Liu, Ning Zhu, Jingjing Peng +4
Online Surgical Phase Recognition (SPR) models can reach high frame-wise accuracy, yet their predictions often lack temporal stability, fragmenting workflow understanding and reduc…
A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on behalf of the Stakeholder Taskforce for AI-assisted Robotic Thrombectomy (START)
Harry Robertshaw, Anna Barnes, Phil Blakelock +20
While we are making progress in overcoming infectious diseases and cancer; one of the major medical challenges of the mid-21st century will be the rising prevalence of stroke. Larg…
DARIL: When Imitation Learning outperforms Reinforcement Learning in Surgical Action Planning
Maxence Boels, Harry Robertshaw, Thomas C Booth +3
Surgical action planning requires predicting future instrument-verb-target triplets for real-time assistance. While teleoperated robotic surgery provides natural expert demonstrati…
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…
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…
Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning
Harry Robertshaw, Lennart Karstensen, Benjamin Jackson +2
Purpose: Autonomous navigation of catheters and guidewires can enhance endovascular surgery safety and efficacy, reducing procedure times and operator radiation exposure. Integrati…
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…
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,…