版权说明 操作指南
首页 > 成果 > 详情

Zygomatic Osteotomy surgery design software based on skull CT scans - Self-supervised algo reduces workload

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Qiu, Xiaohui;Zhong, Chi;Chen, Qiuyang;Zhao, Yingchao;Yang, Tong;...
通讯作者:
Chen, Jing
作者机构:
[Qiu, Xiaohui] National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
[Qiu, Xiaohui] Department of Plastic and Reconstructive Surgery, Xiangya III Hospital of Central South University, China
[Zhou, Jianda; Zhong, Chi] Department of Plastic and Reconstructive Surgery, Xiangya III Hospital of Central South University, China
[Chen, Qiuyang; Liao, Shenghui] School of Computer Science, Central South University, China
[Yang, Tong; Zhao, Yingchao] School of Mechanical Engineering, South China University, China
通讯机构:
[Chen, Jing] D
Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. Electronic address:
语种:
英文
关键词:
Artificial intelligence;CT big dataset;Surgical design
期刊:
Journal of Cranio-Maxillofacial Surgery
ISSN:
1010-5182
年:
2025
机构署名:
本校为其他机构
院系归属:
机械工程学院
摘要:
Background The morphology of the zygomatic complex significantly influences facial appearance, leading to a focus on zygomatic osteotomy. The current technique, the “L-shaped” zygomatic osteotomy, requires a small incision and preoperative osteotomy design for an osteotomy guide. However, the use of multiple software programs in the design process makes it time-consuming and clinically challenging. The morphology of the zygomatic complex significantly influences facial appearance, leading to a focus on zygomatic osteotomy. The current techniq...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com