中文版 | English
题名

Jaw Segmentation from CBCT Images

作者
通讯作者Zhang, Songze
DOI
发表日期
2018
ISSN
1546-1874
ISBN
978-1-5386-6812-2
会议录名称
卷号
2018-November
页码
1-5
会议日期
19-21 Nov. 2018
会议地点
Shanghai, China
出版地
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者
摘要
Nowadays, more people pay attcntion to the dental health including oral cavities, bone tumors or cancers, so the dental CBCT images becomes popular and are widely used in dental diagnosis. Dental implants, orthodontic orthodontics and other surgical procedures are employed in daily life, Accurate jaw separation from neighboring tissues can greatly improve diagnosis results, space measurements and success rates of surgical operations. This paper proposes an automatic segmentation algorithm to separate jaw hone from CBCT images. This algorithm uses the idea of three-dimensional region growing to perform segmentation, then optimizes the segmentation results with active contours, This algorithm yields more accurate segmentation of the jaw bone. Experiments are performed to both manually and automatically segment 10 groups of CBCT datasets. With manual segmentation references, our algorithm demonstrated our automatic segmentation algorithm work well, and further confirmed by evaluation of four quantitative metrics PSNR, SSIM, Precision and Recall. It can potentially assist doctors in diagnosis and surgical planning.
关键词
学校署名
第一 ; 通讯
语种
英语
相关链接[来源记录]
收录类别
WOS研究方向
Engineering
WOS类目
Engineering, Electrical & Electronic
WOS记录号
WOS:000458909600200
EI入藏号
20191106629409
EI主题词
Bone ; Dental prostheses ; Diagnosis ; Digital signal processing ; Implants (surgical) ; Petroleum reservoir evaluation ; Surgery
EI分类号
Biological Materials and Tissue Engineering:461.2 ; Medicine and Pharmacology:461.6 ; Dental Equipment and Supplies:462.3 ; Prosthetics:462.4 ; Petroleum Deposits : Development Operations:512.1.2
来源库
Web of Science
全文链接https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8631819
引用统计
被引频次[WOS]:0
成果类型会议论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/24597
专题工学院_电子与电气工程系
作者单位
Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen, Peoples R China
第一作者单位电子与电气工程系
通讯作者单位电子与电气工程系
第一作者的第一单位电子与电气工程系
推荐引用方式
GB/T 7714
Zhang, Songze,Xie, Junjie,Shi, Hongjian. Jaw Segmentation from CBCT Images[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2018:1-5.
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