2 citations · 4 across the 18 of their papers we have counts for
21 papers
KFSLAM: Adaptive KeyFrame Selection with Structure-Aware Mapping for Endoscopic Gaussian Splatting SLAM
Xinwei Ju, Zhehua Mao, Tianyi Song +3
Gaussian-splatting Simultaneous Localization and Mapping (SLAM) augments conventional SLAM with a dense, renderable 3D scene representation, enabling high-quality reconstruction an…
CasCVS-Net: A Staged Multi-Task Cascade for Critical View of Safety Assessment
Bock-Zien Toh, Yuanchuan Ren, Tay Aw Yu +3
Automated assessment of the Critical View of Safety (CVS) in laparoscopic cholecystectomy requires both recognition of the three CVS criteria and anatomical grounding in small, rar…
Track2Map: Online Deformable SLAM with Motion-Aware Pose Optimization in Robotic Surgery
Tianyi Song, Sierra Bonilla, Xinwei Ju +6
Gaussian splatting is the current state-of-the-art for dense, deformable 3D anatomy reconstruction in robot-assisted minimally invasive surgery (RAMIS); however, most pipelines are…
HyKey: Hyperspectral Keypoint Detection and Matching in Minimally Invasive Surgery
Alexander Saikia, Chiara Di Vece, Zhehua Mao +6
Purpose: 3D reconstruction in minimally invasive surgery (MIS) enables enhanced surgical guidance through improved visualisation, tool tracking, and augmented reality. However, tra…
TemporalDoRA: Temporal PEFT for Robust Surgical Video Question Answering
Luca Carlini, Chiara Lena, Cesare Hassan +4
Surgical Video Question Answering (VideoQA) requires accurate temporal grounding while remaining robust to natural variation in how clinicians phrase questions, where linguistic bi…
Multi-Modal Monocular Endoscopic Depth and Pose Estimation with Edge-Guided Self-Supervision
Xinwei Ju, Rema Daher, Danail Stoyanov +2
Monocular depth and pose estimation play an important role in the development of colonoscopy-assisted navigation, as they enable improved screening by reducing blind spots, minimiz…
A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometry
Chiara Di Vece, Zhehua Mao, Netanell Avisdris +7
Accurate fetal growth assessment from ultrasound (US) relies on precise biometry measured by manually identifying anatomical landmarks in standard planes. Manual landmarking is tim…
SurgAnt-ViVQA: Learning to Anticipate Surgical Events through GRU-Driven Temporal Cross-Attention
Shreyas C. Dhake, Jiayuan Huang, Runlong He +7
Anticipating forthcoming surgical events is vital for real-time assistance in endonasal transsphenoidal pituitary surgery, where visibility is limited and workflow changes rapidly.…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +98
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
SurgViVQA: Temporally-Grounded Video Question Answering for Surgical Scene Understanding
Mauro Orazio Drago, Luca Carlini, Pelinsu Celebi Balyemez +7
Video Question Answering (VideoQA) in the surgical domain aims to enhance intraoperative understanding by enabling AI models to reason over temporally coherent events rather than i…
When to Trust the Answer: Question-Aligned Semantic Nearest Neighbor Entropy for Safer Surgical VQA
Luca Carlini, Dennis Pierantozzi, Mauro Orazio Drago +6
Safety and reliability are critical for deploying visual question answering (VQA) systems in surgery, where incorrect or ambiguous responses can cause patient harm. A key limitatio…
C3VDReg: A Benchmark for Local-to-Local Colonoscopic Registration toward Anatomical Localization
Linzhe Jiang, Jiayuan Huang, Sophia Bano +3
Anatomy-aware colonoscopic navigation requires localizing partial endoscopic observations on a stable 3D reference to support coverage assessment, revisited-region awareness, and C…
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16
Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…
Automated Cervical Os Segmentation for Camera-Guided, Speculum-Free Screening
Aoife McDonald-Bowyer, Anjana Wijekoon, Ryan Laurance Love +7
Cervical cancer is highly preventable, yet persistent barriers to screening limit progress toward elimination goals. Speculum-free devices that integrate imaging and sampling could…
Robotic Arm Platform for Multi-View Image Acquisition and 3D Reconstruction in Minimally Invasive Surgery
Alexander Saikia, Chiara Di Vece, Sierra Bonilla +6
Minimally invasive surgery (MIS) offers significant benefits such as reduced recovery time and minimised patient trauma, but poses challenges in visibility and access, making accur…
Automated Surgical Skill Assessment in Endoscopic Pituitary Surgery using Real-time Instrument Tracking on a High-fidelity Bench-top Phantom
Adrito Das, Bilal Sidiqi, Laurent Mennillo +10
Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective; labour-intensive; and requires domain specific expertise. Automat…
PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery
Adrito Das, Danyal Z. Khan, Dimitrios Psychogyios +29
The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a sur…
PitRSDNet: Predicting Intra-operative Remaining Surgery Duration in Endoscopic Pituitary Surgery
Anjana Wijekoon, Adrito Das, Roxana R. Herrera +7
Accurate intra-operative Remaining Surgery Duration (RSD) predictions allow for anaesthetists to more accurately decide when to administer anaesthetic agents and drugs, as well as…
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation Model
Mona Sheikh Zeinoddin, Chiara Lena, Jiongqi Qu +11
Robotic-assisted surgery (RAS) relies on accurate depth estimation for 3D reconstruction and visualization. While foundation models like Depth Anything Models (DAM) show promise, d…
PitVQA: Image-grounded Text Embedding LLM for Visual Question Answering in Pituitary Surgery
Runlong He, Mengya Xu, Adrito Das +6
Visual Question Answering (VQA) within the surgical domain, utilizing Large Language Models (LLMs), offers a distinct opportunity to improve intra-operative decision-making and fac…
Surgical-DeSAM: Decoupling SAM for Instrument Segmentation in Robotic Surgery
Yuyang Sheng, Sophia Bano, Matthew J. Clarkson +1
Purpose: The recent Segment Anything Model (SAM) has demonstrated impressive performance with point, text or bounding box prompts, in various applications. However, in safety-criti…