78 citations · 124 across the 27 of their papers we have counts for
28 papers
EndoControlMag: Robust Endoscopic Vascular Motion Magnification with Periodic Reference Resetting and Hierarchical Tissue-aware Dual-Mask Control
An Wang, Rulin Zhou, Mengya Xu +7
Visualizing subtle vascular motions in endoscopic surgery is crucial for surgical precision and decision-making, yet remains challenging due to the complex and dynamic nature of su…
BleedOrigin: Dynamic Bleeding Source Localization in Endoscopic Submucosal Dissection via Dual-Stage Detection and Tracking
Mengya Xu, Rulin Zhou, An Wang +4
Intraoperative bleeding during Endoscopic Submucosal Dissection (ESD) poses significant risks, demanding precise, real-time localization and continuous monitoring of the bleeding s…
Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge
Tobias Rueckert, David Rauber, Raphaela Maerkl +58
Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…
EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgery
Guankun Wang, Rui Tang, Mengya Xu +3
Endoscopic surgery is the gold standard for robotic-assisted minimally invasive surgery, offering significant advantages in early disease detection and precise interventions. Howev…
ETSM: Automating Dissection Trajectory Suggestion and Confidence Map-Based Safety Margin Prediction for Robot-assisted Endoscopic Submucosal Dissection
Mengya Xu, Wenjin Mo, Guankun Wang +7
Robot-assisted Endoscopic Submucosal Dissection (ESD) improves the surgical procedure by providing a more comprehensive view through advanced robotic instruments and bimanual opera…
PDZSeg: Adapting the Foundation Model for Dissection Zone Segmentation with Visual Prompts in Robot-assisted Endoscopic Submucosal Dissection
Mengya Xu, Wenjin Mo, Guankun Wang +5
Purpose: Endoscopic surgical environments present challenges for dissection zone segmentation due to unclear boundaries between tissue types, leading to segmentation errors where m…
Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data
An Wang, Haochen Yin, Beilei Cui +2
Accurate depth perception is crucial for patient outcomes in endoscopic surgery, yet it is compromised by image distortions common in surgical settings. To tackle this issue, our s…
SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation
Jieming Yu, An Wang, Wenzhen Dong +5
The recent Segment Anything Model (SAM) 2 has demonstrated remarkable foundational competence in semantic segmentation, with its memory mechanism and mask decoder further addressin…
A Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery
Mengya Xu, Ziqi Guo, An Wang +2
As a crucial and intricate task in robotic minimally invasive surgery, reconstructing surgical scenes using stereo or monocular endoscopic video holds immense potential for clinica…
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…
An Efficient MLP-based Point-guided Segmentation Network for Ore Images with Ambiguous Boundary
Guodong Sun, Yuting Peng, Le Cheng +5
The precise segmentation of ore images is critical to the successful execution of the beneficiation process. Due to the homogeneous appearance of the ores, which leads to low contr…
Privacy-Preserving Synthetic Continual Semantic Segmentation for Robotic Surgery
Mengya Xu, Mobarakol Islam, Long Bai +1
Deep Neural Networks (DNNs) based semantic segmentation of the robotic instruments and tissues can enhance the precision of surgical activities in robot-assisted surgery. However,…
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…
Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting
Yiming Huang, Beilei Cui, Long Bai +4
In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fi…
SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation
An Wang, Mobarakol Islam, Mengya Xu +2
The Segment Anything Model (SAM) serves as a fundamental model for semantic segmentation and demonstrates remarkable generalization capabilities across a wide range of downstream s…
Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation
Beilei Cui, Minqing Zhang, Mengya Xu +3
Noisy label problems are inevitably in existence within medical image segmentation causing severe performance degradation. Previous segmentation methods for noisy label problems on…
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis
An Wang, Mobarakol Islam, Mengya Xu +1
Despite their impressive performance in various surgical scene understanding tasks, deep learning-based methods are frequently hindered from deploying to real-world surgical applic…
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation
An Wang, Mobarakol Islam, Mengya Xu +1
Accurate and robust medical image segmentation is fundamental and crucial for enhancing the autonomy of computer-aided diagnosis and intervention systems. Medical data collection n…
SME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation
An Wang, Mengya Xu, Yang Zhang +2
Fully-supervised polyp segmentation has accomplished significant triumphs over the years in advancing the early diagnosis of colorectal cancer. However, label-efficient solutions f…
Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
Aneeq Zia, Max Berniker, Rogerio Garcia Nespolo +153
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms…
SAM Meets Robotic Surgery: An Empirical Study in Robustness Perspective
An Wang, Mobarakol Islam, Mengya Xu +2
Segment Anything Model (SAM) is a foundation model for semantic segmentation and shows excellent generalization capability with the prompts. In this empirical study, we investigate…
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding
Mengya Xu, Mobarakol Islam, Ben Glocker +1
Curriculum learning and self-paced learning are the training strategies that gradually feed the samples from easy to more complex. They have captivated increasing attention due to…
Task-Aware Asynchronous Multi-Task Model with Class Incremental Contrastive Learning for Surgical Scene Understanding
Lalithkumar Seenivasan, Mobarakol Islam, Mengya Xu +2
Purpose: Surgery scene understanding with tool-tissue interaction recognition and automatic report generation can play an important role in intra-operative guidance, decision-makin…
Rethinking Surgical Instrument Segmentation: A Background Image Can Be All You Need
An Wang, Mobarakol Islam, Mengya Xu +1
Data diversity and volume are crucial to the success of training deep learning models, while in the medical imaging field, the difficulty and cost of data collection and annotation…