Learning Orthodontic Cephalometry through Augmented Reality: A Conceptual Machine Learning Validation Approach

被引：0

作者：

Rao, Gururajaprasad Kaggal Lakshmana ^{[1
]}

Mokhtar, Norehan ^{[1
]}

Iskandar, Yulita Hanum P. ^{[2
]}

Srinivasa, Arvind Channarayapatna ^{[3
]}

机构：

[1] Univ Sains Malaysia, Adv Med & Dent Inst, Craniofacial & Biomat Sci Cluster, George Town 13200, Malaysia

[2] Univ Sains Malaysia, Grad Sch Busines, George Town 11800, Malaysia

[3] Cognizant Technol Solut, Global Technol Off, Res Lab, Cognit Comp & Data Sci, Bengaluru, India

来源：

2018 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICELTICS): INTELLIGENT DEVICES AND COMPUTING FOR ACCELERATING INDUSTRY 4.0 AND ENRICHING SMART SOCIETIES | 2018年

关键词：

orthodontic cephalometry; 3Dimaging; smart learning; augmented reality; machine learning;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The orthodontic cephalometry which forms a quintessential radiographic examination provides a valuable diagnostic resource for everyday orthodontic diagnosis and treatment planning. The method of analyzing the lateral cephalometric radiograph (LCR) has been found to lack effective methods of landmark identification and objective validation. This drawback, with the use of augmented reality (AR) for 3D visualization and machine learning for objective validation, can be effectively incorporated into the learning of cephalometrics. The two technologies together can produce a learning platform by reducing subjective errors and its implications on treatment planning in addition to effectively eliminating dissonance in learning.

引用

页码：133 / 138

页数：6

共 50 条

[1] Content enhancement with augmented reality and machine learning
Freeman, Justin
[J]. JOURNAL OF SOUTHERN HEMISPHERE EARTH SYSTEMS SCIENCE, 2020, 70 (01): : 143 - 150
[2] Grating waveguides by machine learning for augmented reality
Chen, Xi
Lin, Dongfeng
Zhang, Tao
Zhao, Yiming
Liu, Hongwei
Cui, Yiping
Hou, Chenyang
He, Jingwen
Liang, Sheng
[J]. APPLIED OPTICS, 2023, 62 (11) : 2924 - 2935
[3] ALEEDSA: Augmented Reality for Interactive Machine Learning
Ferrario, Andrea
Weibel, Raphael
Feuerriegel, Stefan
[J]. CHI'20: EXTENDED ABSTRACTS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2020,
[4] ARsinoe (sic) - Learning Egyptian Hieroglyphs with Augmented Reality and Machine Learning
Plecher, David A.
Eichhorn, Christian
Seyam, Khaled M.
Klinker, Gudrun
[J]. ADJUNCT PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY (ISMAR-ADJUNCT 2020), 2020, : 326 - 332
[5] Improving the Learning of Mechanics Through Augmented Reality
Clarissa Hedenqvist
Mario Romero
Ricardo Vinuesa
[J]. Technology, Knowledge and Learning, 2023, 28 : 347 - 368
[6] Enhancing the Attractiveness of Learning through Augmented Reality
Iftene, Adrian
Trandabat, Diana
[J]. KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES-2018), 2018, 126 : 166 - 175
[7] Improving the Learning of Mechanics Through Augmented Reality
Hedenqvist, Clarissa
Romero, Mario
Vinuesa, Ricardo
[J]. TECHNOLOGY KNOWLEDGE AND LEARNING, 2023, 28 (01) : 347 - 368
[8] Machine Learning Schemes in Augmented Reality for Features Detection
Dandachi, Ghina
Assoum, Ammar
Elhassan, Bachar
Dornaika, Fadi
[J]. 2015 FIFTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION AND COMMUNICATION TECHNOLOGY AND ITS APPLICATIONS (DICTAP), 2015, : 101 - 105
[9] Enhancing Learning at Primary School Through Augmented Reality
Ramnarain-Seetohul, Vidasha
Nishesh, Appa
Siddish, Lobin
[J]. SMART AND SUSTAINABLE ENGINEERING FOR NEXT GENERATION APPLICATIONS, 2019, 561 : 245 - 255
[10] FOSTERING VISUALIZATION FOR THE LEARNING OF CALCULUS THROUGH AUGMENTED REALITY
Salinas, Patricia
Quintero, Eliud
Gonzalez-Mendivil, Eduardo
[J]. INTED2015: 9TH INTERNATIONAL TECHNOLOGY, EDUCATION AND DEVELOPMENT CONFERENCE, 2015, : 5039 - 5046

← 1 2 3 4 5 →