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Mask R-CNN assisted diagnosis of spinal tuberculosis

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成果类型:
期刊论文、会议论文
作者:
Li, Wenjun;Li, Yanfan;Peng, Huan;Liang, Wenjun
通讯作者:
Liang, WJ
作者机构:
[Li, Wenjun; Peng, Huan; Li, Yanfan] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
[Liang, Wenjun; Liang, WJ] Changsha Cent Hosp, Dept Resp Med, Changsha, Peoples R China.
通讯机构:
[Liang, WJ ] C
Changsha Cent Hosp, Dept Resp Med, Changsha, Peoples R China.
语种:
英文
关键词:
computer-aided diagnosis;deep learning;mask R-CNN;spinal tuberculosis
期刊:
Journal of X-Ray Science and Technology
ISSN:
0895-3996
年:
2025
卷:
33
期:
1
页码:
120-133
会议名称:
2023 9th International Conference on Systems and Informatics (ICSAI)
会议论文集名称:
2023 9th International Conference on Systems and Informatics (ICSAI)
会议时间:
16 December 2023
会议地点:
Changsha, China
出版者:
IEEE
ISBN:
979-8-3503-8371-3
基金类别:
The author(s) received no financial support for the research, authorship, and/or publication of this article.
机构署名:
本校为第一机构
院系归属:
计算机与通信工程学院
摘要:
The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to misdiagnosis and delays in treatment progress but also contributes to the continued transmission of tuberculosis bacteria, posing a risk to other individuals. Currently, CT imaging is extensively utilized in computer-aided diagnosis (CAD). The main features of ST on CT images include bone destruction, osteosclerosis, sequestration formation, and intervertebral disc damage. However, manual diagnosis...

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