[Comparison of two registration methods for constructing virtual craniodentofacial patients based on cone beam computed tomography images].

Q3 Medicine

北京大学学报（医学版） Pub Date : 2025-04-18

Jiahui Ye, Shimin Wang, Zixuan Wang, Yunsong Liu, Yuchun Sun, Hongqiang Ye, Yongsheng Zhou

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引用次数: 0

Abstract

Objective: To compare the registration accuracy of cone beam computed tomography (CBCT) images while registering to virtual craniodentofacial patients based on soft tissue and the dentition registration method.

Methods: Virtual dentofacial patients out of 13 selected participants who needed CBCT scanning were established by impression with a registered-block impression (RBI) based on digital dental images, three-dimensional (3D) facial images and maxillofacial CBCT images. CBCT images were processed in the Mimics software program, establishing the craniofacial virtual patients based on CBCT images (CCTs). Registration between virtual patients from RBI and CCT, using the soft tissue in lower half face (STE) and dentition (DTN) as the reference area, respectively, forming two kinds of virtual craniofacial patients based on digital dental images, 3D facial images and skeletal images of CBCT (hiding the soft tissue and dental casts from CBCT). Three-dimensional deviation analysis was performed in the upper half face and lower half face of facial images from CBCT between two kinds of virtual craniodentofacial patients and compared with 3D facial images from RBI and recorded as root mean square error (RMSE). Paired-t test was used to compare the deviations of RMSEs between the upper and lower half of the face and the upper half of the face of facial images from CCT, respectively, between the two kinds of virtual craniodentofacial patients based on STE and DTN methods.

Results: Paired-t tests showed that there was no statistically significant difference between the upper and lower half faces of facial images from CCT between STE and DTN (P>0.05), but the deviation of RMSEs of the upper half face of facial images from CCT in STE was smaller than those in DTN [(1.696±0.420) mm vs. (1.752±0.424) mm, P < 0.01].

Conclusion: The registration accuracy of CBCT registered in virtual craniodentofacial patients using soft tissue as the reference area was higher.

本刊更多论文

[基于锥束ct图像构建虚拟颅颌面患者的两种配准方法的比较]。

目的：比较锥形束ct （cone beam computed tomography， CBCT）图像在基于软组织的虚拟颅牙面患者配准与牙列配准时的配准精度。方法：选取13例需要CBCT扫描的虚拟牙面患者，采用基于数字牙齿图像、三维（3D）面部图像和颌面CBCT图像的注册块印象（RBI）建立虚拟牙面患者。在Mimics软件程序中对CBCT图像进行处理，建立基于CBCT图像的颅面虚拟患者（CCTs）。RBI和CCT虚拟患者注册，分别以下半脸软组织（STE）和牙列软组织（DTN）作为参考区域，形成基于数字牙科图像、三维面部图像和CBCT骨骼图像（隐藏CBCT的软组织和牙模）的两种虚拟颅面患者。对两类虚拟颅牙面患者的CBCT面部图像的上半部分和下半部分进行三维偏差分析，并与RBI的三维面部图像进行比较，记录为均方根误差（RMSE）。采用配对t检验比较基于STE和DTN方法的两种虚拟颅牙面患者的CCT面部图像上、下半部分面部和上半部分面部的均方根误差的偏差。结果：配对t检验显示，STE组与DTN组CCT面部图像上、下半部分面部差异无统计学意义（P < 0.05），但STE组CCT面部图像上半部分面部的rmse偏差小于DTN组[(1.696±0.420)mm vs(1.752±0.424)mm, P < 0.01]。结论：以软组织为参考区域的虚拟颅牙面患者CBCT配准精度较高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

北京大学学报（医学版） Medicine-Medicine (all)

CiteScore

0.80

自引率

0.00%

发文量

9815

期刊介绍： Beijing Da Xue Xue Bao Yi Xue Ban / Journal of Peking University (Health Sciences), established in 1959, is a national academic journal sponsored by Peking University, and its former name is Journal of Beijing Medical University. The coverage of the Journal includes basic medical sciences, clinical medicine, oral medicine, surgery, public health and epidemiology, pharmacology and pharmacy. Over the last few years, the Journal has published articles and reports covering major topics in the different special issues (e.g. research on disease genome, theory of drug withdrawal, mechanism and prevention of cardiovascular and cerebrovascular diseases, stomatology, orthopaedic, public health, urology and reproductive medicine). All the topics involve latest advances in medical sciences, hot topics in specific specialties, and prevention and treatment of major diseases. The Journal has been indexed and abstracted by PubMed Central (PMC), MEDLINE/PubMed, EBSCO, Embase, Scopus, Chemical Abstracts (CA), Western Pacific Region Index Medicus (WPR), JSTChina, and almost all the Chinese sciences and technical index systems, including Chinese Science and Technology Paper Citation Database (CSTPCD), Chinese Science Citation Database (CSCD), China BioMedical Bibliographic Database (CBM), CMCI, Chinese Biological Abstracts, China National Academic Magazine Data-Base (CNKI), Wanfang Data (ChinaInfo), etc.