HipXNet: Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images
- DOI
- 10.1109/access.2022.3173424
- Published
- 2022
- Container
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/access.2022.3173424,
title = {HipXNet: Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images},
author = {Tawsifur Rahman and Amith Khandakar and Khandaker Reajul Islam and Md Mohiuddin Soliman and Mohammad Tariqul Islam and Ahmed Elsayed and Yazan Qiblawey and Sakib Mahmud and Ashiqur Rahman and Farayi Musharavati and Erfan Zalnezhad and Muhammad E. H. Chowdhury},
year = {2022},
journal = {IEEE Access},
doi = {10.1109/access.2022.3173424},
url = {https://doi.org/10.1109/access.2022.3173424}
}RIS
TY - JOUR TI - HipXNet: Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images AU - Tawsifur Rahman AU - Amith Khandakar AU - Khandaker Reajul Islam AU - Md Mohiuddin Soliman AU - Mohammad Tariqul Islam AU - Ahmed Elsayed AU - Yazan Qiblawey AU - Sakib Mahmud AU - Ashiqur Rahman AU - Farayi Musharavati AU - Erfan Zalnezhad AU - Muhammad E. H. Chowdhury PY - 2022 JO - IEEE Access DO - 10.1109/access.2022.3173424 UR - https://doi.org/10.1109/access.2022.3173424 ER -
APA
Rahman, T., Khandakar, A., Islam, K. R., Soliman, M. M., Islam, M. T., Elsayed, A., Qiblawey, Y., Mahmud, S., Rahman, A., Musharavati, F., Zalnezhad, E., & Chowdhury, M. E. H. (2022). HipXNet: Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images. IEEE Access. https://doi.org/10.1109/access.2022.3173424
Source records
- crossref · retrieved 2026-09-27T04:48:23.901Z