计算机软件在三维面部成像与测量中的应用进展

doi:10.13701/j.cnki.kqyxyj.2023.08.003

口腔医学研究 ›› 2023, Vol. 39 ›› Issue (8): 675-678.DOI: 10.13701/j.cnki.kqyxyj.2023.08.003

计算机软件在三维面部成像与测量中的应用进展

杨怡卿, 刘亚非^*

河北医科大学第一医院口腔正畸科河北石家庄 050030

收稿日期:2022-12-28 发布日期:2023-08-17
通讯作者: *刘亚非,E-mail:yafei_lyf@sina.com
作者简介:杨怡卿(1995~ ),女,内蒙古人,硕士,医师,研究方向:口腔正畸学,现在河北省眼科医院工作。

Application Progress of Computer Software in Three-dimensional Facial Imaging and Measurement

YANG Yiqing, LIU Yafei^*

Department of Orthodontics, First Hospital of Hebei Medical University, Shijiazhuang 050030, China

Received:2022-12-28 Published:2023-08-17

摘要/Abstract

摘要： 如今三维面部成像技术在整形外科、正畸科等颜面部美学相关学科中变得越来越重要。三维面部成像的发展与计算机技术的广泛应用密切相关,三维激光扫描、锥型束CT(CBCT)、3dMD立体摄影系统、卷积神经网络等在面部测量分析中的应用均是两者紧密结合的结果,将医生与患者的沟通、治疗计划和结果评估提升到了一个新的水平。现代计算机软件技术正在日益成为临床医师的重要辅助工具。本文就各类软件技术在三维面部成像与测量中的具体应用及其特点作一综述。

关键词: 计算机软件, 三维面部成像, 三维立体建模

Abstract: Three-dimensional facial imaging technology is becoming more and more important in the current facial aesthetics related disciplines such as plastic surgery and orthodontics. The development of three-dimensional facial imaging is closely related to the extensive application of computer technology. The applications of three-dimensional laser scanning, cone-beam CT (CBCT), 3dMD stereoscopic imaging system, and convolutional neural network in facial measurement and analysis are all the results of closely combination of both, which brings the communication between doctors and patients, treatment plan, and result evaluation to a new level. Modern computer software technology is increasingly becoming an important auxiliary tool for clinicians. This paper reviews the specific applications and characteristics of various software techniques in three-dimensional facial imaging and measurement.

Key words: computer software, three-dimensional facial imaging, three-dimensional modeling

杨怡卿, 刘亚非. 计算机软件在三维面部成像与测量中的应用进展[J]. 口腔医学研究, 2023, 39(8): 675-678.

YANG Yiqing, LIU Yafei. Application Progress of Computer Software in Three-dimensional Facial Imaging and Measurement[J]. Journal of Oral Science Research, 2023, 39(8): 675-678.

参考文献

[1] Javaid M, Haleem A, Singh RP, et al. Industrial perspectives of 3D scanning: features, roles and it's analytical applications [J]. Sensors International, 2021, 2: 100114.
[2] 郭培闪,杜黎明. 运用Geomagic Studio实现点云数据的曲面重建及误差分析[J].地理信息世界,2015,22(1):57-60.
[3] 高宇,李卫民,赵旭东,等. 逆向工程技术研究现状与展望[J]. 辽宁工业大学学报(自然科学版),2021,41(2):90-94+128.
[4] 温奥楠,朱玉佳,郑盛文,等. 基于三维人脸模板的颜面解剖标志点自动定点方法初探[J]. 中华口腔医学杂志,2022,57(4):358-365.
[5] Cheng B, Mohamed AS, Habumugisha J, et al. A study of the facial soft tissue morphology in nasal-and mouth-breathing patients [J]. Int Dent J, 2023, 73(3):403-409.
[6] 赵一姣,熊玉雪,杨慧芳,等. 3种不同原理颜面部扫描仪测量精度的评价[J]. 北京大学学报(医学版),2014,46(1):76-80.
[7] Yasuda K, Nakano H, Yamada T, et al. Identifying differences between a straight face and a posed smile using the homologous modeling technique and the principal component analysis [J]. J Craniofac Surg, 2019, 30(8): 2378-2380.
[8] Kapila SD, Nervina JM. CBCT in orthodontics: assessment of treatment outcomes and indications for its use [J]. Dentomaxillofac Radiol, 2015, 44(1): 20140282.
[9] 陈虹羽,王晨齐,赖文莉. Dolphin软件的介绍及其在口腔正畸临床中的应用[J]. 中国医师杂志,2015,17(4):611-613.
[10] Santana N, Starbuck JM. Breaking symmetry: a quantitative analysis of facial skeleton disharmony in children born with bilateral cleft lip and palate [J]. Anat Rec (Hoboken), 2019, 302(10): 1726-1732.
[11] Akan B, Gökçe G, Karadede Ünal B, et al. Assessment of soft tissue changes after LeFort I advancement [J]. Eur Arch Otorhinolaryngol, 2021, 278(3): 813-819.
[12] Imani MM, Sanei E, Niaki EA, et al. Esthetic preferences of orthodontists, oral surgeons, and laypersons for Persian facial profiles [J]. Am J Orthod Dentofacial Orthop, 2018, 154(3): 412-420.
[13] Cohen A, Sela MC, Shooraki N, et al. The influence of articular eminence morphology on temporomandibular joint anterior dislocations [J]. Oral Surg Oral Med Oral Pathol Oral Radiol, 2021, 131(1): 9-15.
[14] Ras F, Habets L, Van Ginkel FC, et al. Quantification of facial morphology using stereophotogrammetry-demonstration of a new concept [J]. J Dent, 1996, 24(5): 369-374.
[15] Lübbers HT, Medinger L, Kruse A, et al. Precision and accuracy of the 3dMD photogrammetric system in craniomaxillofacial application [J]. J Craniofac Surg, 2010, 21(3): 763-767.
[16] Tzou CHJ, Artner NM, Pona I, et al. Comparison of three-dimensional surface-imaging systems [J]. J Plast Reconstr Aesthet Surg, 2014, 67(4): 489-497.
[17] Blasi A, Nucera R, Ronsivalle V, et al. Asymmetry index for the photogrammetric assessment of facial asymmetry [J]. Am J Orthod Dentofacial Orthop, 2022, 162(3): 394-402.
[18] Büyükçavus MH, Findik Y, Baykul T. Evaluation of changes in nasal projection after surgically assisted rapid maxillary expansion with 3dMD face system [J]. J Craniofac Surg, 2020, 31(5): e462-e465.
[19] Ünal BK, Hüseyin C. Evaluation of facial soft tissues by stereophotogrammetry method in patients with obstructive sleep apnoea: a morphological study [J]. Folia Morphol (Warsz), 2021, 80(2): 432-441.
[20] 高洁. 正畸治疗对成人面部软组织影响的三维初步探索研究[D]. 第四军医大学, 2017.
[21] 周勤,高洁,张旭,等. 成人女性正畸治疗后鼻唇沟处软组织变化的三维定量研究[J]. 实用口腔医学杂志,2021,37(2):237-241.
[22] Currie G, Hawk KE, Rohren E, et al. Machine learning and deep learning in medical imaging: intelligent imaging [J]. J Med Imaging Radiat Sci, 2019, 50(4): 477-487.
[23] Takeda S, Mine Y, Yoshimi Y, et al. Landmark annotation and mandibular lateral deviation analysis of posteroanterior cephalograms using a convolutional neural network [J]. J Dent Sci, 2021, 16(3): 957-963.
[24] Ding M, Kang Y, Yuan Z, et al. Detection of facial landmarks by a convolutional neural network in patients with oral and maxillofacial disease [J]. Int J Oral Maxillofac Surg, 2021, 50(11): 1443-1449.
[25] McCullough M, Ly S, Auslander A, et al. Convolutional neural network models for automatic preoperative severity assessment in unilateral cleft lip [J]. Plast Reconstr Surg, 2021, 148(1): 162-169.
[26] Hancock PJB, Somai RS, Mileva VR. Convolutional neural net face recognition works in non-human-like ways [J]. R Soc Open Sci, 2020, 7(10): 200595.
[27] 苏昳娴. 基于轻量级网络的人脸识别系统[J]. 中国科技信息,2022,(21): 105-108.
[28] 贾茜伟,闫娟,杨慧斌,等. 基于面部多个局部特征的人脸表情识别算法[J]. 智能计算机与应用,2022,12(10):144-149.

计算机软件在三维面部成像与测量中的应用进展

Application Progress of Computer Software in Three-dimensional Facial Imaging and Measurement

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics