133 related articles for article (PubMed ID: 36494109)
1. DEEP LEARNING ALGORITHMS HAVE HIGH ACCURACY FOR AUTOMATED LANDMARK DETECTION ON 2D LATERAL CEPHALOGRAMS.
Cao L; He H; Hua F
J Evid Based Dent Pract; 2022 Dec; 22(4):101798. PubMed ID: 36494109
[TBL] [Abstract][Full Text] [Related]
2. Deep learning for cephalometric landmark detection: systematic review and meta-analysis.
Schwendicke F; Chaurasia A; Arsiwala L; Lee JH; Elhennawy K; Jost-Brinkmann PG; Demarco F; Krois J
Clin Oral Investig; 2021 Jul; 25(7):4299-4309. PubMed ID: 34046742
[TBL] [Abstract][Full Text] [Related]
3. LOW CERTAINTY OF EVIDENCE SUPPORTS THE APPLICATION OF (AI) FOR THE AUTOMATIC DETECTION OF CEPHALOMETRIC LANDMARKS WITH PROSPECTS FOR IMPROVEMENTS.
Montasser ZM; Montasser MA
J Evid Based Dent Pract; 2024 Jun; 24(2):101965. PubMed ID: 38821652
[TBL] [Abstract][Full Text] [Related]
4. Can artificial intelligence-driven cephalometric analysis replace manual tracing? A systematic review and meta-analysis.
Hendrickx J; Gracea RS; Vanheers M; Winderickx N; Preda F; Shujaat S; Jacobs R
Eur J Orthod; 2024 Aug; 46(4):. PubMed ID: 38895901
[TBL] [Abstract][Full Text] [Related]
5. DEEP LEARNING ALGORITHMS SHOW SOME POTENTIAL AS AN ADJUNCTIVE TOOL IN CARIES DIAGNOSIS.
Hegde S; Gao J
J Evid Based Dent Pract; 2022 Dec; 22(4):101772. PubMed ID: 36494110
[TBL] [Abstract][Full Text] [Related]
6. Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and
Londono J; Ghasemi S; Hussain Shah A; Fahimipour A; Ghadimi N; Hashemi S; Khurshid Z; Dashti M
Saudi Dent J; 2023 Jul; 35(5):487-497. PubMed ID: 37520606
[TBL] [Abstract][Full Text] [Related]
7. Artificial intelligence system for automated landmark localization and analysis of cephalometry.
Jiang F; Guo Y; Yang C; Zhou Y; Lin Y; Cheng F; Quan S; Feng Q; Li J
Dentomaxillofac Radiol; 2023 Jan; 52(1):20220081. PubMed ID: 36279185
[TBL] [Abstract][Full Text] [Related]
8. Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis.
Serafin M; Baldini B; Cabitza F; Carrafiello G; Baselli G; Del Fabbro M; Sforza C; Caprioglio A; Tartaglia GM
Radiol Med; 2023 May; 128(5):544-555. PubMed ID: 37093337
[TBL] [Abstract][Full Text] [Related]
9. Automated calibration system for length measurement of lateral cephalometry based on deep learning.
Jiang F; Guo Y; Zhou Y; Yang C; Xing K; Zhou J; Lin Y; Cheng F; Li J
Phys Med Biol; 2022 Nov; 67(22):. PubMed ID: 36206749
[No Abstract] [Full Text] [Related]
10. Automatic cephalometric landmark identification with artificial intelligence: An umbrella review of systematic reviews.
Polizzi A; Leonardi R
J Dent; 2024 Jul; 146():105056. PubMed ID: 38729291
[TBL] [Abstract][Full Text] [Related]
11. Personal Computer-Based Cephalometric Landmark Detection With Deep Learning, Using Cephalograms on the Internet.
Nishimoto S; Sotsuka Y; Kawai K; Ishise H; Kakibuchi M
J Craniofac Surg; 2019 Jan; 30(1):91-95. PubMed ID: 30439733
[TBL] [Abstract][Full Text] [Related]
12. Web-based fully automated cephalometric analysis by deep learning.
Kim H; Shim E; Park J; Kim YJ; Lee U; Kim Y
Comput Methods Programs Biomed; 2020 Oct; 194():105513. PubMed ID: 32403052
[TBL] [Abstract][Full Text] [Related]
13. Accuracy and clinical validity of automated cephalometric analysis using convolutional neural networks.
Kang S; Kim I; Kim YJ; Kim N; Baek SH; Sung SJ
Orthod Craniofac Res; 2024 Feb; 27(1):64-77. PubMed ID: 37326233
[TBL] [Abstract][Full Text] [Related]
14. Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi-centres.
Kim J; Kim I; Kim YJ; Kim M; Cho JH; Hong M; Kang KH; Lim SH; Kim SJ; Kim YH; Kim N; Sung SJ; Baek SH
Orthod Craniofac Res; 2021 Dec; 24 Suppl 2():59-67. PubMed ID: 33973341
[TBL] [Abstract][Full Text] [Related]
15. Clinical applicability of automated cephalometric landmark identification: Part II - Number of images needed to re-learn various quality of images.
Tanikawa C; Oka A; Lim J; Lee C; Yamashiro T
Orthod Craniofac Res; 2021 Dec; 24 Suppl 2():53-58. PubMed ID: 34145974
[TBL] [Abstract][Full Text] [Related]
16. ACCESS FLAPS MAY RESULT IN GREATER POCKET REDUCTION THAN SUBGINGIVAL DEBRIDEMENT FOR DEEP POCKETS BUT MAY NOT BE BENEFICIAL FOR SHALLOW TO MODERATELY DEEP POCKETS.
Cheng LL
J Evid Based Dent Pract; 2021 Sep; 21(3):101612. PubMed ID: 34479674
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of automated cephalometric analysis based on the latest deep learning method.
Hwang HW; Moon JH; Kim MG; Donatelli RE; Lee SJ
Angle Orthod; 2021 May; 91(3):329-335. PubMed ID: 33434275
[TBL] [Abstract][Full Text] [Related]
18. Automated identification of cephalometric landmarks:
Park JH; Hwang HW; Moon JH; Yu Y; Kim H; Her SB; Srinivasan G; Aljanabi MNA; Donatelli RE; Lee SJ
Angle Orthod; 2019 Nov; 89(6):903-909. PubMed ID: 31282738
[TBL] [Abstract][Full Text] [Related]
19. [Automated cephalometric landmark identification and location based on convolutional neural network].
Gong BW; Chang S; Zuo FF; Xie XJ; Wang SF; Wang YJ; Sun YY; Guan XC; Bai YX
Zhonghua Kou Qiang Yi Xue Za Zhi; 2023 Dec; 58(12):1249-1256. PubMed ID: 38061867
[No Abstract] [Full Text] [Related]
20. Ceph-Net: automatic detection of cephalometric landmarks on scanned lateral cephalograms from children and adolescents using an attention-based stacked regression network.
Yang S; Song ES; Lee ES; Kang SR; Yi WJ; Lee SP
BMC Oral Health; 2023 Oct; 23(1):803. PubMed ID: 37884918
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
