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Found 9 papers, 6 papers with code
UltraFlwr -- An Efficient Federated Medical and Surgical Object Detection Framework
This paper advances the feasibility of training and deploying detection models on the edge, making federated object detection more practical for time-critical and resource-constrained medical and surgical applications.
SWAG: Long-term Surgical Workflow Prediction with Generative-based Anticipation
To address these limitations, we propose SWAG (Surgical Workflow Anticipative Generation), a unified framework for phase recognition and long-term anticipation of surgical workflows.
DDSB: An Unsupervised and Training-free Method for Phase Detection in Echocardiography
Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography.
Rethinking Low-quality Optical Flow in Unsupervised Surgical Instrument Segmentation
Video-based surgical instrument segmentation plays an important role in robot-assisted surgeries.
SuPRA: Surgical Phase Recognition and Anticipation for Intra-Operative Planning
In conclusion, SuPRA presents a new multi-task approach that paves the way for improved intra-operative assistance through surgical phase recognition and prediction of future events.
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks
First, we introduce an innovative adaptive noise scale that effectively generates the textual elements with more variability while preserving the original text feature's integrity.
SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems.
LoViT: Long Video Transformer for Surgical Phase Recognition
Our results demonstrate the effectiveness of our approach in achieving state-of-the-art performance of surgical phase recognition on two datasets of different surgical procedures and temporal sequencing characteristics whilst introducing mechanisms that cope with long videos.
Ranked #1 on
Surgical phase recognition
on Cholec80
SKiT: a Fast Key Information Video Transformer for Online Surgical Phase Recognition
We highlight that the inference time of SKiT is constant, and independent from the input length, making it a stable choice for keeping a record of important global information, that appears on long surgical videos, essential for phase recognition.
