130 related articles for article (PubMed ID: 38769619)
1. Novel AI-based tool for primary tooth segmentation on CBCT using convolutional neural networks: A validation study.
Elsonbaty S; Elgarba BM; Fontenele RC; Swaity A; Jacobs R
Int J Paediatr Dent; 2024 May; ():. PubMed ID: 38769619
[TBL] [Abstract][Full Text] [Related]
2. Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images - A validation study.
Fontenele RC; Gerhardt MDN; Pinto JC; Van Gerven A; Willems H; Jacobs R; Freitas DQ
J Dent; 2022 Apr; 119():104069. PubMed ID: 35183696
[TBL] [Abstract][Full Text] [Related]
3. Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography.
Verhelst PJ; Smolders A; Beznik T; Meewis J; Vandemeulebroucke A; Shaheen E; Van Gerven A; Willems H; Politis C; Jacobs R
J Dent; 2021 Nov; 114():103786. PubMed ID: 34425172
[TBL] [Abstract][Full Text] [Related]
4. Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study.
Elgarba BM; Van Aelst S; Swaity A; Morgan N; Shujaat S; Jacobs R
J Dent; 2023 Oct; 137():104639. PubMed ID: 37517787
[TBL] [Abstract][Full Text] [Related]
5. A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation study.
Shaheen E; Leite A; Alqahtani KA; Smolders A; Van Gerven A; Willems H; Jacobs R
J Dent; 2021 Dec; 115():103865. PubMed ID: 34710545
[TBL] [Abstract][Full Text] [Related]
6. A unique artificial intelligence-based tool for automated CBCT segmentation of mandibular incisive canal.
Jindanil T; Marinho-Vieira LE; de-Azevedo-Vaz SL; Jacobs R
Dentomaxillofac Radiol; 2023 Nov; 52(8):20230321. PubMed ID: 37870152
[TBL] [Abstract][Full Text] [Related]
7. Deep convolutional neural network-based automated segmentation and classification of teeth with orthodontic brackets on cone-beam computed-tomographic images: a validation study.
Ayidh Alqahtani K; Jacobs R; Smolders A; Van Gerven A; Willems H; Shujaat S; Shaheen E
Eur J Orthod; 2023 Mar; 45(2):169-174. PubMed ID: 36099419
[TBL] [Abstract][Full Text] [Related]
8. Multiclass CBCT Image Segmentation for Orthodontics with Deep Learning.
Wang H; Minnema J; Batenburg KJ; Forouzanfar T; Hu FJ; Wu G
J Dent Res; 2021 Aug; 100(9):943-949. PubMed ID: 33783247
[TBL] [Abstract][Full Text] [Related]
9. Artificial Intelligence for Fast and Accurate 3-Dimensional Tooth Segmentation on Cone-beam Computed Tomography.
Lahoud P; EzEldeen M; Beznik T; Willems H; Leite A; Van Gerven A; Jacobs R
J Endod; 2021 May; 47(5):827-835. PubMed ID: 33434565
[TBL] [Abstract][Full Text] [Related]
10. Automated detection and labelling of teeth and small edentulous regions on cone-beam computed tomography using convolutional neural networks.
Gerhardt MDN; Fontenele RC; Leite AF; Lahoud P; Van Gerven A; Willems H; Smolders A; Beznik T; Jacobs R
J Dent; 2022 Jul; 122():104139. PubMed ID: 35461974
[TBL] [Abstract][Full Text] [Related]
11. Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.
Fontenele RC; Gerhardt MDN; Picoli FF; Van Gerven A; Nomidis S; Willems H; Freitas DQ; Jacobs R
Clin Oral Implants Res; 2023 Jun; 34(6):565-574. PubMed ID: 36906917
[TBL] [Abstract][Full Text] [Related]
12. Evaluating tooth segmentation accuracy and time efficiency in CBCT images using artificial intelligence: A systematic review and Meta-analysis.
Xiang B; Lu J; Yu J
J Dent; 2024 Jul; 146():105064. PubMed ID: 38768854
[TBL] [Abstract][Full Text] [Related]
13. Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT.
Lahoud P; Diels S; Niclaes L; Van Aelst S; Willems H; Van Gerven A; Quirynen M; Jacobs R
J Dent; 2022 Jan; 116():103891. PubMed ID: 34780873
[TBL] [Abstract][Full Text] [Related]
14. Deep convolutional neural network-based automated segmentation of the maxillofacial complex from cone-beam computed tomography:A validation study.
Preda F; Morgan N; Van Gerven A; Nogueira-Reis F; Smolders A; Wang X; Nomidis S; Shaheen E; Willems H; Jacobs R
J Dent; 2022 Sep; 124():104238. PubMed ID: 35872223
[TBL] [Abstract][Full Text] [Related]
15. Deep learning for automated segmentation of the temporomandibular joint.
Vinayahalingam S; Berends B; Baan F; Moin DA; van Luijn R; Bergé S; Xi T
J Dent; 2023 May; 132():104475. PubMed ID: 36870441
[TBL] [Abstract][Full Text] [Related]
16. [Segmentation and accuracy validation of mandibular molar and pulp cavity on cone-beam CT images by U-net neural network].
Lin X; Fu YJ; Ren GQ; Wen JH; Chen YF; Zhang Q
Shanghai Kou Qiang Yi Xue; 2022 Oct; 31(5):454-459. PubMed ID: 36758590
[TBL] [Abstract][Full Text] [Related]
17. Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network.
Minnema J; van Eijnatten M; Hendriksen AA; Liberton N; Pelt DM; Batenburg KJ; Forouzanfar T; Wolff J
Med Phys; 2019 Nov; 46(11):5027-5035. PubMed ID: 31463937
[TBL] [Abstract][Full Text] [Related]
18. Deep learning driven segmentation of maxillary impacted canine on cone beam computed tomography images.
Swaity A; Elgarba BM; Morgan N; Ali S; Shujaat S; Borsci E; Chilvarquer I; Jacobs R
Sci Rep; 2024 Jan; 14(1):369. PubMed ID: 38172136
[TBL] [Abstract][Full Text] [Related]
19. Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images.
Nogueira-Reis F; Morgan N; Nomidis S; Van Gerven A; Oliveira-Santos N; Jacobs R; Tabchoury CPM
Clin Oral Investig; 2023 Mar; 27(3):1133-1141. PubMed ID: 36114907
[TBL] [Abstract][Full Text] [Related]
20. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model.
Gan Y; Xia Z; Xiong J; Zhao Q; Hu Y; Zhang J
Med Phys; 2015 Jan; 42(1):14-27. PubMed ID: 25563244
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]