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Found 9 papers, 2 papers with code
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects
Policy learning in robot-assisted surgery (RAS) lacks data efficient and versatile methods that exhibit the desired motion quality for delicate surgical interventions.
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud
In deformable object manipulation, we often want to interact with specific segments of an object that are only defined in non-deformed models of the object.
Grounding Graph Network Simulators using Physical Sensor Observations
Our method results in utilization of additional point cloud information to accurately predict stable simulations where existing Graph Network Simulators fail.
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution
It is worth noting that our ensemble models took first place in the final evaluation on the BraTS testing dataset with Dice scores of 0. 9294, 0. 8788, and 0. 8803, and Hausdorf distance of 5. 23, 13. 54, and 12. 05, for the whole tumor, tumor core, and enhancing tumor, respectively.
Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients
Reliable and accurate registration of patient-specific brain magnetic resonance imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes.
LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes
The semantic segmentation of surgical scenes is a prerequisite for task automation in robot assisted interventions.
Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI
Accurate identification of the malignant brain tumor and its sub-regions is still one of the most challenging problems in medical image segmentation.
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance.
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems.
Ranked #1 on
Surgical phase recognition
on HeiChole Benchmark
