SPHASE: Multi-Modal and Multi-Branch Surgical Phase Segmentation Framework based on Temporal Convolutional Network
Author:
Affiliation:
1. Central South University,Big Data Institution,Changsha,China
2. Central South University,School of Computer Science and Engineering,Changsha,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385579.pdf?arnumber=10385579
Reference40 articles.
1. Image Based Surgical Instrument Pose Estimation with Multi-class Labelling and Optical Flow
2. Aggregating Long-Term Context for Learning Laparoscopic and Robot-Assisted Surgical Workflows
3. Histogram of Oriented Gradients meet deep learning: A novel multi-task deep network for 2D surgical image semantic segmentation
4. M2CAI workflow challenge: Convolutional neural networks with time smoothing and hidden markov model for video frames classification;Cadène;CoRR,2016
5. TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks
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