Deep Omni-Supervised Learning for Rib Fracture Detection From Chest Radiology Images-Reference-Cited by-同舟云学术

Deep Omni-Supervised Learning for Rib Fracture Detection From Chest Radiology Images

Published:2024-05 Issue:5 Volume:43 Page:1972-1982
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Chai Zhizhong¹^ORCID,Luo Luyang²^ORCID,Lin Huangjing¹,Heng Pheng-Ann³^ORCID,Chen Hao⁴^ORCID

Affiliation:

1. Imsight AI Research Laboratory, Shenzhen, China

2. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China

4. Department of Computer Science and Engineering and the Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

Funder

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

Innovation and Technology Commission

Shenzhen Science and Technology Innovation Committee Funding

Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/42/10517791/10398253.pdf?arnumber=10398253

Reference46 articles.

1. Traumatic Rib Injury: Patterns, Imaging Pitfalls, Complications, and Treatment

2. Rib Fracture Location Should be Evaluated When Predicting Morbidity and Mortality in Trauma Patients

3. Assessment of a Deep Learning Algorithm for the Detection of Rib Fractures on Whole-Body Trauma Computed Tomography

4. Development and Evaluation of a Deep Learning Algorithm for Rib Segmentation and Fracture Detection from Multicenter Chest CT Images

5. Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility

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