COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm
- DOI
- 10.1016/j.bspc.2022.104159
- Published
- 2023-01
- Container
- Biomedical Signal Processing and Control
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.bspc.2022.104159,
title = {COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm},
author = {Guowei Wang and Shuli Guo and Lina Han and Zhilei Zhao and Xiaowei Song},
year = {2023},
journal = {Biomedical Signal Processing and Control},
doi = {10.1016/j.bspc.2022.104159},
url = {https://doi.org/10.1016/j.bspc.2022.104159}
}RIS
TY - JOUR TI - COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm AU - Guowei Wang AU - Shuli Guo AU - Lina Han AU - Zhilei Zhao AU - Xiaowei Song PY - 2023 JO - Biomedical Signal Processing and Control DO - 10.1016/j.bspc.2022.104159 UR - https://doi.org/10.1016/j.bspc.2022.104159 ER -
APA
Wang, G., Guo, S., Han, L., Zhao, Z., & Song, X. (2023). COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm. Biomedical Signal Processing and Control. https://doi.org/10.1016/j.bspc.2022.104159
Source records
- crossref · retrieved 2026-09-25T11:24:10.672Z