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HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images
Meirui Jiang, Zirui Wang, Qi Dou
Multiple medical institutions collaboratively training a model using federated learning (FL) has become a promising solution for maximizing the potential of data-driven models, yet…
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Ruofeng Wei, Bin Li, Hangjie Mo +6
Objective: The computation of anatomical information and laparoscope position is a fundamental block of surgical navigation in Minimally Invasive Surgery (MIS). Recovering a dense…
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko +38
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the…
Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
Cheng Chen, Quande Liu, Yueming Jin +2
Domain adaptation typically requires to access source domain data to utilize their distribution information for domain alignment with the target data. However, in many real-world s…
SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning
Jiaqi Xu, Bin Li, Bo Lu +3
Autonomous surgical execution relieves tedious routines and surgeon's fatigue. Recent learning-based methods, especially reinforcement learning (RL) based methods, achieve promisin…
Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks
Jiaze Wang, Kai Chen, Qi Dou
Category-level 6D pose estimation, aiming to predict the location and orientation of unseen object instances, is fundamental to many scenarios such as robotic manipulation and augm…