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Found 13 papers, 5 papers with code
MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopy
We demonstrate that mesh stylization is a promising approach for creating realistic simulations for downstream tasks such as training and preoperative planning.
Zero-shot Prompt-based Video Encoder for Surgical Gesture Recognition
Purpose: Surgical video is an important data stream for gesture recognition.
Depth Anything in Medical Images: A Comparative Study
Monocular depth estimation (MDE) is a critical component of many medical tracking and mapping algorithms, particularly from endoscopic or laparoscopic video.
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
Rethinking Causality-driven Robot Tool Segmentation with Temporal Constraints
Method: To address the above limitations, we take temporal relation into consideration and propose a temporal causal model for robot tool segmentation on video sequences.
CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data
Vision-based segmentation of the robotic tool during robot-assisted surgery enables downstream applications, such as augmented reality feedback, while allowing for inaccuracies in robot kinematics.
An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
The method operates similarly to human interpretation of CT scans and first detects distinct pelvic fractures on CT with high specificity using a Faster-RCNN model that are then interpreted using a structural causal model based on clinical best practices to infer an initial Tile grade.
Estimation of Trocar and Tool Interaction Forces on the da Vinci Research Kit with Two-Step Deep Learning
Measurement of environment interaction forces during robotic minimally-invasive surgery would enable haptic feedback to the surgeon, thereby solving one long-standing limitation.
Robotics
Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery
Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery.
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Action Segmentation
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Multimodal and self-supervised representation learning for automatic gesture recognition in surgical robotics
We develop a self-supervised, multi-modal representation learning paradigm that learns representations for surgical gestures from video and kinematics.
A County-level Dataset for Informing the United States' Response to COVID-19
As the coronavirus disease 2019 (COVID-19) becomes a global pandemic, policy makers must enact interventions to stop its spread.
Computers and Society Databases Physics and Society Populations and Evolution
Leveraging Vision and Kinematics Data to Improve Realism of Biomechanic Soft-tissue Simulation for Robotic Surgery
We train a network to predict this correction factor.
LumiPath -- Towards Real-time Physically-based Rendering on Embedded Devices
With the increasing computational power of today's workstations, real-time physically-based rendering is within reach, rapidly gaining attention across a variety of domains.
