Quantitative Measurement Method for Possible Rib Fractures in Chest Radiographs-Reference-Cited by-同舟云学术

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Quantitative Measurement Method for Possible Rib Fractures in Chest Radiographs

Published:2013 Issue:3 Volume:19 Page:196
ISSN:2093-3681
Container-title:Healthcare Informatics Research
language:en
Short-container-title:Healthc Inform Res

Author:

Kim Jaeil¹,Kim Sungjun²,Kim Young Jae³,Kim Kwang Gi³,Park Jinah¹

Affiliation:

1. Department of Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Korea.

2. Department of Radiology, Yonsei University College of Medicine, Seoul, Korea.

3. Biomedical Engineering Branch, Division of Convergence Technology, National Cancer Center, Goyang, Korea.

Publisher

The Korean Society of Medical Informatics

Subject

Health Information Management,Health Informatics,Biomedical Engineering

Link

https://synapse.koreamed.org/pdf/10.4258/hir.2013.19.3.196

Reference15 articles.

1. When and how to image a suspected broken rib

2. Non-life-threatening blunt chest trauma: Appropriate investigation and treatment

3. A Fully Automated Adaptive Unsharp Masking Technique in Digital Chest Radiograph

4. Improved parameters for unsharp mask filtering of digital chest radiographs.

5. Digital radiography enhancement by nonlinear multiscale processing

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep convolutional neural network for rib fracture recognition on chest radiographs;Frontiers in Medicine;2023-08-01

2. Deep-learning algorithm for rib fracture detection in low-dose chest CT images;Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering;2022-11-10

3. Deep learning-based framework for segmentation of multiclass rib fractures in CT utilizing a multi-angle projection network;International Journal of Computer Assisted Radiology and Surgery;2022-04-06

4. Precise anatomical localization and classification of rib fractures on CT using a convolutional neural network;Clinical Imaging;2022-01

5. Rib fracture detection system based on deep learning;Scientific Reports;2021-12

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