Colonoscopy analysis, particularly automatic polyp segmentation and
dete...
Accurate segmentation of surgical instrument tip is an important task fo...
One critical challenge in 6D object pose estimation from a single RGBD i...
Reinforcement learning is still struggling with solving long-horizon sur...
Intracerebral hemorrhage (ICH) is the second most common and deadliest f...
Foundation models have exhibited remarkable success in various applicati...
Despite that the segment anything model (SAM) achieved impressive result...
This paper presents an effective and general data augmentation framework...
Semi-supervised learning (SSL) methods assume that labeled data, unlabel...
Video dehazing aims to recover haze-free frames with high visibility and...
Needle picking is a challenging surgical task in robot-assisted surgery ...
This paper proposes a novel bin picking framework, two-stage grasping, a...
Recent advancements toward perception and decision-making of flexible
en...
Histopathological tissue classification is a fundamental task in
computa...
Task automation of surgical robot has the potentials to improve surgical...
Radiance fields have gradually become a main representation of media.
Al...
Mitigating the discrimination of machine learning models has gained
incr...
Surgical robot automation has attracted increasing research interest ove...
Brain midline shift (MLS) is one of the most critical factors to be
cons...
Estimating precise metric depth and scene reconstruction from monocular
...
Most existing methods for category-level pose estimation rely on object ...
Learning high-performance deep neural networks for dynamic modeling of h...
In this paper, we present a novel and generic data-driven method to
serv...
Computer-assisted minimally invasive surgery has great potential in
bene...
Machine learning models fail to perform well on real-world applications ...
Surgical scene segmentation is fundamentally crucial for prompting cogni...
Class distribution plays an important role in learning deep classifiers....
Reconstruction of the soft tissues in robotic surgery from endoscopic st...
Domain generalization typically requires data from multiple source domai...
Deep neural networks have achieved remarkable success in a wide variety ...
In this paper, we propose an iterative self-training framework for
sim-t...
Despite the remarkable success on medical image analysis with deep learn...
With the growing popularity of robotic surgery, education becomes
increa...
Supervised federated learning (FL) enables multiple clients to share the...
Automatic laparoscope motion control is fundamentally important for surg...
Magnetic resonance imaging (MRI) can present multi-contrast images of th...
Industrial bin picking is a challenging task that requires accurate and
...
This paper presents the design and results of the "PEg TRAnsfert Workflo...
The demand of competent robot assisted surgeons is progressively expandi...
Multiple medical institutions collaboratively training a model using
fed...
The computation of anatomical information and laparoscope position is a
...
PURPOSE: Surgical workflow and skill analysis are key technologies for t...
Domain adaptation typically requires to access source domain data to uti...
Autonomous surgical execution relieves tedious routines and surgeon's
fa...
Category-level 6D pose estimation, aiming to predict the location and
or...
Reconstructing the scene of robotic surgery from the stereo endoscopic v...
Federated learning (FL) has emerged with increasing popularity to collab...
The superior performance of CNN on medical image analysis heavily depend...
Automatic surgical workflow recognition is a key component for developin...
The "MIcro-Surgical Anastomose Workflow recognition on training sessions...