Less Is More: Surgical Phase Recognition From Timestamp Supervision-Reference-Cited by-同舟云学术

Less Is More: Surgical Phase Recognition From Timestamp Supervision

Published:2023-06 Issue:6 Volume:42 Page:1897-1910
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Ding Xinpeng¹^ORCID,Yan Xinjian²,Wang Zixun¹^ORCID,Zhao Wei³^ORCID,Zhuang Jian⁴,Xu Xiaowei⁴^ORCID,Li Xiaomeng¹^ORCID

Affiliation:

1. Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, SAR, China

2. Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Academy of Medical Sciences, Guangzhou, China

3. School of Physics, Beihang University, Beijing, China

4. Department of Cardiovascular Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

Funder

Shenzhen Municipal Central Government Guides Local Science and Technology Development Special Funded Projects

Hong Kong University of Science and Technology (HKUST)- Beijing Institute of Collaborative Innovation (BICI) Exploratory Fund

Research Grants Council of the Hong Kong Special Administrative Region, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/10142147/10043791.pdf?arnumber=10043791

Reference71 articles.

1. Leveraging uncertainty information from deep neural networks for disease detection

2. Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer

3. Uncertainty quantification in computer-aided diagnosis: Make your model say ‘I don’t know’ for ambiguous cases;laves;arXiv 1908 00792,2019

4. Exploring Segment-Level Semantics for Online Phase Recognition From Surgical Videos

5. MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation

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3. Surgical Temporal Action-aware Network with Sequence Regularization for Phase Recognition;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

4. SPHASE: Multi-Modal and Multi-Branch Surgical Phase Segmentation Framework based on Temporal Convolutional Network;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

5. Reducing the Label Bias for Timestamp Supervised Temporal Action Segmentation;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06