Bidirectional Semi-Supervised Dual-Branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions-Reference-Cited by-同舟云学术

Bidirectional Semi-Supervised Dual-Branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions

Published:2023-11 Issue:11 Volume:42 Page:3269-3282
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Shi Hongkuan¹^ORCID,Wang Zhiwei¹^ORCID,Zhou Ying¹,Li Dun²,Yang Xin³^ORCID,Li Qiang¹^ORCID

Affiliation:

1. Wuhan National Laboratory for Optoelectronics, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China

2. United Imaging Surgical Healthcare Company Ltd., Wuhan, China

3. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

Research Grants from Wuhan United Imaging Healthcare Surgical Technology Company Ltd

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/ielx7/42/10299534/10136208.pdf?arnumber=10136208

Reference43 articles.

1. Semi-supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model

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3. Details preserved unsupervised depth estimation by fusing traditional stereo knowledge from laparoscopic images

4. Quantitative Evaluation of Confidence Measures in a Machine Learning World

5. A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

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