578 citations · 700 across the 22 of their papers we have counts for
23 papers
SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding
Yuqing Feng, Jiawei Ma, Kevin Qinghong Lin +6
Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for intraoperative decision-mak…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
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…
SAMSA 2.0: Prompting Segment Anything with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Alfie Roddan, Tobias Czempiel, Chi Xu +2
We present SAMSA 2.0, an interactive segmentation framework for hyperspectral medical imaging that introduces spectral angle prompting to guide the Segment Anything Model (SAM) usi…
Explainable Image Classification with Reduced Overconfidence for Tissue Characterisation
Alfie Roddan, Chi Xu, Serine Ajlouni +3
The deployment of Machine Learning models intraoperatively for tissue characterisation can assist decision making and guide safe tumour resections. For image classification models,…
SAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Alfie Roddan, Tobias Czempiel, Chi Xu +2
Hyperspectral imaging (HSI) provides rich spectral information for medical imaging, yet encounters significant challenges due to data limitations and hardware variations. We introd…
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision
Utsav Rai, Haozheng Xu, Stamatia Giannarou
Accurate pose estimation of surgical tools in Robot-assisted Minimally Invasive Surgery (RMIS) is essential for surgical navigation and robot control. While traditional marker-base…
SurgRIPE challenge: Benchmark of Surgical Robot Instrument Pose Estimation
Haozheng Xu, Alistair Weld, Chi Xu +16
Accurate instrument pose estimation is a crucial step towards the future of robotic surgery, enabling applications such as autonomous surgical task execution. Vision-based methods…
Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentation
Yihang Zhou, Rebecca Towning, Zaid Awad +1
Surgical scene segmentation is essential for enhancing surgical precision, yet it is frequently compromised by the scarcity and imbalance of available data. To address these challe…
Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis
Frank P. -W. Lo, Jianing Qiu, Zeyu Wang +6
Conventional approaches to dietary assessment are primarily grounded in self-reporting methods or structured interviews conducted under the supervision of dietitians. These methods…
Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery
Baoru Huang, Yicheng Hu, Anh Nguyen +2
In surgical oncology, it is challenging for surgeons to identify lymph nodes and completely resect cancer even with pre-operative imaging systems like PET and CT, because of the la…
SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic Surgery
Joao Cartucho, Alistair Weld, Samyakh Tukra +23
This paper introduces the ``SurgT: Surgical Tracking" challenge which was organised in conjunction with MICCAI 2022. There were two purposes for the creation of this challenge: (1)…
Regularising disparity estimation via multi task learning with structured light reconstruction
Alistair Weld, Joao Cartucho, Chi Xu +2
3D reconstruction is a useful tool for surgical planning and guidance. However, the lack of available medical data stunts research and development in this field, as supervised deep…
Caveats on the first-generation da Vinci Research Kit: latent technical constraints and essential calibrations
Zejian Cui, Joao Cartucho, Stamatia Giannarou +1
Telesurgical robotic systems provide a well established form of assistance in the operating theater, with evidence of growing uptake in recent years. Until now, the da Vinci surgic…
Self-Supervised Depth Estimation in Laparoscopic Image using 3D Geometric Consistency
Baoru Huang, Jian-Qing Zheng, Anh Nguyen +6
Depth estimation is a crucial step for image-guided intervention in robotic surgery and laparoscopic imaging system. Since per-pixel depth ground truth is difficult to acquire for…
Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images
Baoru Huang, Jianqing Zheng, Anh Nguyen +4
Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo images pa…
H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry
Baoru Huang, Jian-Qing Zheng, Stamatia Giannarou +1
Depth estimation from a stereo image pair has become one of the most explored applications in computer vision, with most of the previous methods relying on fully supervised learnin…
Surgical Data Science -- from Concepts toward Clinical Translation
Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya +47
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a…
Autonomous Tissue Scanning under Free-Form Motion for Intraoperative Tissue Characterisation
Jian Zhan, Joao Cartucho, Stamatia Giannarou
In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is required for subsurface visualisation to characterise the state of the tissue. However, scanning of larg…
Surgical Data Science: A Consensus Perspective
Lena Maier-Hein, Matthias Eisenmann, Carolin Feldmann +25
Surgical data science is a scientific discipline with the objective of improving the quality of interventional healthcare and its value through capturing, organization, analysis, a…
Motion-Compensated Autonomous Scanning for Tumour Localisation using Intraoperative Ultrasound
Lin Zhang, Menglong Ye, Stamatia Giannarou +2
Intraoperative ultrasound facilitates localisation of tumour boundaries during minimally invasive procedures. Autonomous ultrasound scanning systems have been recently proposed to…
Surgical Data Science: Enabling Next-Generation Surgery
Lena Maier-Hein, Swaroop Vedula, Stefanie Speidel +22
This paper introduces Surgical Data Science as an emerging scientific discipline. Key perspectives are based on discussions during an intensive two-day international interactive wo…
Real-time 3D Tracking of Articulated Tools for Robotic Surgery
Menglong Ye, Lin Zhang, Stamatia Giannarou +1
In robotic surgery, tool tracking is important for providing safe tool-tissue interaction and facilitating surgical skills assessment. Despite recent advances in tool tracking, exi…