Using DeepLab v3 + -based semantic segmentation to evaluate platelet activation-Reference-Cited by-同舟云学术

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Using DeepLab v3 + -based semantic segmentation to evaluate platelet activation

Published:2022-04-29 Issue:6 Volume:60 Page:1775-1785
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

Kuo Tsung-Chen,Cheng Ting-Wei,Lin Ching-Kai,Chang Ming-Che,Cheng Kuang-Yao,Cheng Yun-Chien

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11517-022-02575-3.pdf

Reference19 articles.

1. Modic M, Junkar I, Stana-Kleinschek K, Kostanjšek R, Mozetič M, Polymers PJPPa (2014) Morphology transformations of platelets on plasma activated surfaces. Plasma Processes Polym 11(6):596–605. https://doi.org/10.1002/ppap.201400001

2. Yun S-H, Sim E-H, Goh R-Y, Park J-I, Han J-Y. 2016 Platelet activation: the mechanisms and potential biomarkers. BioMed research international 2016. https://doi.org/10.1155/2016/9060143.

3. Cheng K-Y, Lin Z-H, Cheng Y-P, Chiu H-Y, Yeh N-L, Wu T-K, Wu J-S (2018) Wound healing in streptozotocin-induced diabetic rats using atmospheric-pressure argon plasma jet. Sci Rep 8(1):1–15. https://doi.org/10.1038/s41598-018-30597-1

4. Miao H, Xiao C (2018) Simultaneous segmentation of leukocyte and erythrocyte in microscopic images using a marker-controlled watershed algorithm. Comput Math Methods Med 2018:1–9. https://doi.org/10.1155/2018/7235795

5. Roy K, Dey R, Bhattacharjee D, Nasipuri M, Ghosh P. 2016 An automated system for platelet segmentation using histogram-based thresholding. 2016 2nd International Conference on Advances in Computing, Communication, & Automation (ICACCA)(Fall) 1–7. https://doi.org/10.1109/ICACCAF.2016.7749000.

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