Detection of Proximal Caries Lesions with Deep Learning Algorithm
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Hyuntae, Kim
(Department of Pediatric Dentistry, School of Dentistry, Seoul National University)
Ji-Soo, Song (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) Teo Jeon, Shin (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) Hong-Keun, Hyun (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) Jung-Wook, Kim (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) Ki-Taeg, Jang (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) Young-Jae, Kim (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) |
1 | Pitts NB, Zero DT, Ismail A, et al. : Dental caries. Nat Rev Dis Primers, 3:17030, 2017. |
2 | Featherstone JD : The science and practice of caries prevention. J Am Dent Assoc, 131:887-899, 2000. DOI |
3 | Sheiham A : Dental caries affects body weight, growth and quality of life in pre-school children. Br Dent J, 201:625-626, 2006. DOI |
4 | Selwitz RH, Ismail AI, Pitts NB : Dental caries. Lancet, 369:51-59, 2007. DOI |
5 | Eli I, Weiss EI, Kaffe I, et al. : Interpretation of bitewing radiographs. Part 1. Evaluation of the presence of approximal lesions. J Dent, 24:379-383, 1996. DOI |
6 | Weiss EI, Tzohar A, Eli I, et al. : Interpretation of bitewing radiographs. Part 2. Evaluation of the size of approximal lesions and need for treatment. J Dent, 24:385-388, 1996. DOI |
7 | Akkaya N, Kansu O, Arslan U, et al. : Comparing the accuracy of panoramic and intraoral radiography in the diagnosis of proximal caries. Dentomaxillofac Radiol, 35:170-174, 2006. DOI |
8 | Schwendicke F, Tzschoppe M, Paris S : Radiographic caries detection: A systematic review and meta-analysis. J Dent, 43:924-933, 2015. DOI |
9 | Chan HP, Hadjiiski LM, Samala RK : Computer-aided diagnosis in the era of deep learning. Med Phys, 47:218-227, 2020. |
10 | Russel S, Norvig P : Artificial intelligence: a modern approach, 4th ed. Pearson, Hoboken, 1-5, 2021. |
11 | LeCun Y, Bengio Y, Hinton G : Deep learning. Nature, 521:436-444, 2015. DOI |
12 | Rusk N : Deep learning. Nature Methods, 13:35-35, 2016. DOI |
13 | Albawi S, Mohammed TA, Al-Zawi S : Understanding of a convolutional neural network. 2017 International Conference on Engineering and Technology (ICET), 2017:21-23, 2017. |
14 | Zaremba W, Sutskever I, Vinyals O : Recurrent neural network regularization. ArXiv, abs:1409.2329, 2014. |
15 | Howard J, Gugger S : Fastai: A Layered API for Deep Learning. Information, 11:108, 2020. |
16 | Paszke A, Gross S, Chintala S, et al. : Pytorch: An imperative style, high-performance deep learning library. Adv Neural Inf Process Syst, 32:8026-8037, 2019. |
17 | Lee JH, Kim DH, Jeong SN, Choi SH : Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent, 77:106-111, 2018. DOI |
18 | Schneiderman A, Elbaum M, Driller J, et al. : Assessment of dental caries with Digital Imaging Fiber-Optic Translllumination (DIFOTI): in vitro study. Caries Res, 31:103-110, 1997. DOI |
19 | Lussi A, Hibst R, Paulus R : DIAGNOdent: An optical method for caries detection. J Dent Res, 83:80-83, 2004. DOI |
20 | Caliskan Yanikoglu F, Ozturk F, Stookey GK, et al. : Detection of natural white spot caries lesions by an ultrasonic system. Caries Res, 34:225-232, 2000. DOI |
21 | Cantu AG, Gehrung S, Schwendicke, F, et al. : Detecting caries lesions of different radiographic extension on bitewings using deep learning. J Dent, 100:103425, 2020. |
22 | Bayraktar Y, Ayan E : Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs. Clin Oral Investig, 26:623-632, 2022. DOI |
23 | Lee S, Oh SI, Park JW, et al. : Deep learning for early dental caries detection in bitewing radiographs. Sci Rep, 11:16807, 2021. |
24 | Kamburoglu K, Kolsuz E, Ozen T, et al. : Proximal caries detection accuracy using intraoral bitewing radiography, extraoral bitewing radiography and panoramic radiography. Dentomaxillofac Radiol, 41:450-459, 2012. DOI |
25 | Muller MP, Tomlinson G, Gold WL, et al. : Can routine laboratory tests discriminate between severe acute respiratory syndrome and other causes of community-acquired pneumonia?. Clin Infect Dis, 40:1079-1086, 2005. DOI |
26 | Krois J, Garcia Cantu A, Schwendicke, F, et al. : Generalizability of deep learning models for dental image analysis. Sci Rep, 11:6102, 2021. |
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