Rib fracture detection in chest CT image based on a centernet network with heatmap pyramid structure-Reference-Cited by-同舟云学术

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Rib fracture detection in chest CT image based on a centernet network with heatmap pyramid structure

Published:2023-01-04 Issue:5 Volume:17 Page:2343-2350
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Su Yipeng,Zhang Xiong,Shangguan Hong,Li Ranran

Funder

Excellent Graduate Innovation Project of TYUST

Fundamental Research Program of Shanxi Province

The Natural Science for Youth Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-022-02451-5.pdf

Reference29 articles.

1. Schulze, C., Hoppe, H., Schweitzer, W., Schwendener, N., Grabherr, S., Jackowski, C.: Rib fractures at postmortem computed tomography (PMCT) validated against the autopsy. Forensic Sci. Int. 233(1–3), 90–98 (2013). https://doi.org/10.1016/j.forsciint.2013.08.025

2. Fang, L., Xiaojun, G., Cheng, L., Liang, J., Xiu, J., Ming, L.: The value of CT ribs unfolded algorithm in the diagnosis of rib fracture[J]. Chinese J. Radiol. (2017). https://doi.org/10.3760/CMA.J.ISSN.1005-1201.2017.09.013

3. Saba, L., Biswas, M., Kuppili, V., et al.: The present and future of deep learning in radiology. Eur. J. Radiol. 114, 14–24 (2019). https://doi.org/10.1016/j.ejrad.2019.02.038

4. Esteva, A., Kuprel, B., Novoa, R.A., et al.: Dermatologist-level classification of skin cancer with deep neural networks [published correction appears in Nature. Nature. 542(7639), 115–118 (2017). https://doi.org/10.1038/nature21056

5. Bonavita, I., Rafael-Palou, X., Ceresa, M., Piella, G., Ribas, V., González Ballester, M.A.: Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline. Comput Methods Programs Biomed. 185, 105172 (2020). https://doi.org/10.1016/j.cmpb.2019.105172

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