127 citations · 651 across the 21 of their papers we have counts for
21 papers
Which Modality Decides? Counterfactual Modality Attribution for Multimodal LLMs
Vahidin Hasic, Chao Wang, Luis C. Garcia-Peraza-Herrera +2
Multimodal large language models (MLLMs) increasingly support high-stakes decision making by combining complementary information from images and text. While existing explainability…
Can LLM-Generated Text Empower Surgical Vision-Language Pre-training?
Chengan Che, Chao Wang, Jiayuan Huang +2
Recent advancements in self-supervised learning have led to powerful surgical vision encoders capable of spatiotemporal understanding. However, extending these visual foundations t…
Back to the Feature: Explaining Video Classifiers with Video Counterfactual Explanations
Chao Wang, Chengan Che, Xinyue Chen +2
Counterfactual explanations (CFEs) are minimal and semantically meaningful modifications of the input of a model that alter the model predictions. They highlight the decisive featu…
A Stitch in Time: Learning Procedural Workflow via Self-Supervised Plackett-Luce Ranking
Chengan Che, Chao Wang, Xinyue Chen +2
Procedural activities, ranging from routine cooking to complex surgical operations, are highly structured sequences of actions performed in a specific temporal order. Despite the s…
Average Calibration Losses for Reliable Uncertainty in Medical Image Segmentation
Theodore Barfoot, Luis C. Garcia-Peraza-Herrera, Samet Akcay +2
Deep neural networks for medical image segmentation are often overconfident, compromising both reliability and clinical utility. In this work, we propose differentiable formulation…
LEMON: A Large Endoscopic MONocular Dataset and Foundation Model for Perception in Surgical Settings
Chengan Che, Chao Wang, Tom Vercauteren +2
Traditional open-access datasets focusing on surgical procedures are often limited by their small size, typically consisting of fewer than 100 videos and less than 30 hours of foot…
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation
Theodore Barfoot, Luis Garcia-Peraza-Herrera, Ben Glocker +1
Deep neural networks for medical image segmentation often produce overconfident results misaligned with empirical observations. Such miscalibration, challenges their clinical trans…
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…
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…
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…
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…
Rapid and robust endoscopic content area estimation: A lean GPU-based pipeline and curated benchmark dataset
Charlie Budd, Luis C. Garcia-Peraza-Herrera, Martin Huber +2
Endoscopic content area refers to the informative area enclosed by the dark, non-informative, border regions present in most endoscopic footage. The estimation of the content area…
Robotic Endoscope Control via Autonomous Instrument Tracking
Caspar Gruijthuijsen, Luis C. Garcia-Peraza-Herrera, Gianni Borghesan +5
Many keyhole interventions rely on bi-manual handling of surgical instruments, forcing the main surgeon to rely on a second surgeon to act as a camera assistant. In addition to the…
Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology
Luis C. Garcia-Peraza-Herrera, Martin Everson, Laurence Lovat +6
Purpose. Early squamous cell neoplasia (ESCN) in the oesophagus is a highly treatable condition. Lesions confined to the mucosal layer can be curatively treated endoscopically. We…
Image Compositing for Segmentation of Surgical Tools without Manual Annotations
Luis C. Garcia-Peraza-Herrera, Lucas Fidon, Claudia D'Ettorre +3
Producing manual, pixel-accurate, image segmentation labels is tedious and time-consuming. This is often a rate-limiting factor when large amounts of labeled images are required, s…
Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking
Luis C. García-Peraza-Herrera, Wenqi Li, Caspar Gruijthuijsen +7
Real-time tool segmentation is an essential component in computer-assisted surgical systems. We propose a novel real-time automatic method based on Fully Convolutional Networks (FC…
Incompressible image registration using divergence-conforming B-splines
Lucas Fidon, Michael Ebner, Luis C. Garcia-Peraza-Herrera +3
Anatomically plausible image registration often requires volumetric preservation. Previous approaches to incompressible image registration have exploited relaxed constraints, ad ho…
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
Sebastian Bodenstedt, Max Allan, Anthony Agustinos +17
Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking sys…
Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks
Lucas Fidon, Wenqi Li, Luis C. Garcia-Peraza-Herrera +4
The Dice score is widely used for binary segmentation due to its robustness to class imbalance. Soft generalisations of the Dice score allow it to be used as a loss function for tr…
ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools
Luis C. Garcia-Peraza-Herrera, Wenqi Li, Lucas Fidon +8
Real-time tool segmentation from endoscopic videos is an essential part of many computer-assisted robotic surgical systems and of critical importance in robotic surgical data scien…
Scalable multimodal convolutional networks for brain tumour segmentation
Lucas Fidon, Wenqi Li, Luis C. Garcia-Peraza-Herrera +4
Brain tumour segmentation plays a key role in computer-assisted surgery. Deep neural networks have increased the accuracy of automatic segmentation significantly, however these mod…