117 related articles for article (PubMed ID: 37553029)
1. Denoised encoder-based residual U-net for precise teeth image segmentation and damage prediction on panoramic radiographs.
Almalki SA; Alsubai S; Alqahtani A; Alenazi AA
J Dent; 2023 Oct; 137():104651. PubMed ID: 37553029
[TBL] [Abstract][Full Text] [Related]
2. Teeth U-Net: A segmentation model of dental panoramic X-ray images for context semantics and contrast enhancement.
Hou S; Zhou T; Liu Y; Dang P; Lu H; Shi H
Comput Biol Med; 2023 Jan; 152():106296. PubMed ID: 36462370
[TBL] [Abstract][Full Text] [Related]
3. Robust automated teeth identification from dental radiographs using deep learning.
Xu M; Wu Y; Xu Z; Ding P; Bai H; Deng X
J Dent; 2023 Sep; 136():104607. PubMed ID: 37422206
[TBL] [Abstract][Full Text] [Related]
4. Segmentation of teeth in panoramic dental X-ray images using U-Net with a loss function weighted on the tooth edge.
Nishitani Y; Nakayama R; Hayashi D; Hizukuri A; Murata K
Radiol Phys Technol; 2021 Mar; 14(1):64-69. PubMed ID: 33398671
[TBL] [Abstract][Full Text] [Related]
5. Coarse-to-fine prior-guided attention network for multi-structure segmentation on dental panoramic radiographs.
Tian Y; Zhang Z; Zhao B; Liu L; Liu X; Feng Y; Tian J; Kou D
Phys Med Biol; 2023 Oct; 68(21):. PubMed ID: 37816372
[No Abstract] [Full Text] [Related]
6. Enhancing teeth segmentation using multifusion deep neural net in panoramic X-ray images.
Arora S; Gupta R; Srivastava R
J Xray Sci Technol; 2023; 31(5):1145-1161. PubMed ID: 37483058
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Comparison of Multi-Label U-Net and Mask R-CNN for panoramic radiograph segmentation to detect periodontitis.
Widyaningrum R; Candradewi I; Aji NRAS; Aulianisa R
Imaging Sci Dent; 2022 Dec; 52(4):383-391. PubMed ID: 36605859
[TBL] [Abstract][Full Text] [Related]
9. Transformer-Based Deep Learning Network for Tooth Segmentation on Panoramic Radiographs.
Sheng C; Wang L; Huang Z; Wang T; Guo Y; Hou W; Xu L; Wang J; Yan X
J Syst Sci Complex; 2023; 36(1):257-272. PubMed ID: 36258771
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.
Lee JH; Han SS; Kim YH; Lee C; Kim I
Oral Surg Oral Med Oral Pathol Oral Radiol; 2020 Jun; 129(6):635-642. PubMed ID: 31992524
[TBL] [Abstract][Full Text] [Related]
12. A multiple-channel and atrous convolution network for ultrasound image segmentation.
Zhang L; Zhang J; Li Z; Song Y
Med Phys; 2020 Dec; 47(12):6270-6285. PubMed ID: 33007105
[TBL] [Abstract][Full Text] [Related]
13. Tufts Dental Database: A Multimodal Panoramic X-Ray Dataset for Benchmarking Diagnostic Systems.
Panetta K; Rajendran R; Ramesh A; Rao S; Agaian S
IEEE J Biomed Health Inform; 2022 Apr; 26(4):1650-1659. PubMed ID: 34606466
[TBL] [Abstract][Full Text] [Related]
14. A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs.
Bayrakdar IS; Orhan K; Çelik Ö; Bilgir E; Sağlam H; Kaplan FA; Görür SA; Odabaş A; Aslan AF; Różyło-Kalinowska I
Biomed Res Int; 2022; 2022():7035367. PubMed ID: 35075428
[TBL] [Abstract][Full Text] [Related]
15. Feature-guided attention network for medical image segmentation.
Zhou H; Sun C; Huang H; Fan M; Yang X; Zhou L
Med Phys; 2023 Aug; 50(8):4871-4886. PubMed ID: 36746870
[TBL] [Abstract][Full Text] [Related]
16. CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.
Liu Z; Yuan H; Wang H
Med Phys; 2022 Aug; 49(8):5294-5303. PubMed ID: 35609213
[TBL] [Abstract][Full Text] [Related]
17. SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography.
Wang J; Lv P; Wang H; Shi C
Comput Methods Programs Biomed; 2021 Sep; 208():106268. PubMed ID: 34274611
[TBL] [Abstract][Full Text] [Related]
18. RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.
Li YZ; Wang Y; Huang YH; Xiang P; Liu WX; Lai QQ; Gao YY; Xu MS; Guo YF
Comput Methods Programs Biomed; 2023 Apr; 231():107437. PubMed ID: 36863157
[TBL] [Abstract][Full Text] [Related]
19. Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs.
Leite AF; Gerven AV; Willems H; Beznik T; Lahoud P; Gaêta-Araujo H; Vranckx M; Jacobs R
Clin Oral Investig; 2021 Apr; 25(4):2257-2267. PubMed ID: 32844259
[TBL] [Abstract][Full Text] [Related]
20. Deep learning for automatic mandible segmentation on dental panoramic x-ray images.
Machado LF; Watanabe PCA; Rodrigues GA; Junior LOM
Biomed Phys Eng Express; 2023 Mar; 9(3):. PubMed ID: 36724498
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
