These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

160 related articles for article (PubMed ID: 37720330)

  • 1. Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction.
    Liu J; Hao J; Lin H; Pan W; Yang J; Feng Y; Wang G; Li J; Jin Z; Zhao Z; Liu Z
    Patterns (N Y); 2023 Sep; 4(9):100825. PubMed ID: 37720330
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification.
    Jang TJ; Yun HS; Hyun CM; Kim JE; Lee SH; Seo JK
    Med Image Anal; 2024 Apr; 93():103096. PubMed ID: 38301347
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Accuracy of deep learning-based integrated tooth models by merging intraoral scans and CBCT scans for 3D evaluation of root position during orthodontic treatment.
    Lee SC; Hwang HS; Lee KC
    Prog Orthod; 2022 May; 23(1):15. PubMed ID: 35527317
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Automatic tooth roots segmentation of cone beam computed tomography image sequences using U-net and RNN.
    Li Q; Chen K; Han L; Zhuang Y; Li J; Lin J
    J Xray Sci Technol; 2020; 28(5):905-922. PubMed ID: 32986647
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Reliability and validity of miniscrews as references in cone-beam computed tomography and intraoral scanner digital models: study on goat heads.
    Jiang Y; Chen G
    BMC Oral Health; 2019 Nov; 19(1):259. PubMed ID: 31771579
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. A progressive framework for tooth and substructure segmentation from cone-beam CT images.
    Tan M; Cui Z; Zhong T; Fang Y; Zhang Y; Shen D
    Comput Biol Med; 2024 Feb; 169():107839. PubMed ID: 38150887
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Novel Procedure for Automatic Registration between Cone-Beam Computed Tomography and Intraoral Scan Data Supported with 3D Segmentation.
    Kim YJ; Ahn JH; Lim HK; Nguyen TP; Jha N; Kim A; Yoon J
    Bioengineering (Basel); 2023 Nov; 10(11):. PubMed ID: 38002450
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Monitoring of typodont root movement via crown superimposition of single cone-beam computed tomography and consecutive intraoral scans.
    Lee RJ; Pham J; Choy M; Weissheimer A; Dougherty HL; Sameshima GT; Tong H
    Am J Orthod Dentofacial Orthop; 2014 Mar; 145(3):399-409. PubMed ID: 24582031
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Convolutional neural network for automated tooth segmentation on intraoral scans.
    Wang X; Alqahtani KA; Van den Bogaert T; Shujaat S; Jacobs R; Shaheen E
    BMC Oral Health; 2024 Jul; 24(1):804. PubMed ID: 39014389
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Replacement of the Distorted Dentition of the Cone-Beam Computed Tomography Scans for Orthognathic Surgery Planning.
    Almutairi T; Naudi K; Nairn N; Ju X; Whitters J; Ayoub A
    J Oral Maxillofac Surg; 2018 Jul; 76(7):1561.e1-1561.e8. PubMed ID: 29572134
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Comparison of intraoral scanning and CBCT to generate digital and 3D-printed casts by fused deposition modeling and digital light processing.
    de Freitas BN; Mendonça LM; Cruvinel PB; de Lacerda TJ; Leite FGJ; Oliveira-Santos C; Tirapelli C
    J Dent; 2023 Jan; 128():104387. PubMed ID: 36496106
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning-based tooth segmentation methods in medical imaging: A review.
    Chen X; Ma N; Xu T; Xu C
    Proc Inst Mech Eng H; 2024 Feb; 238(2):115-131. PubMed ID: 38314788
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Impacts of Thresholds of Gray Value for Cone-Beam Computed Tomography 3D Reconstruction on the Accuracy of Image Matching with Optical Scan.
    Park SW; Yoon RG; Lee H; Lee HJ; Choi YD; Lee DH
    Int J Environ Res Public Health; 2020 Sep; 17(17):. PubMed ID: 32882986
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Digital three-dimensional visualization of intrabony periodontal defects for regenerative surgical treatment planning.
    Palkovics D; Mangano FG; Nagy K; Windisch P
    BMC Oral Health; 2020 Dec; 20(1):351. PubMed ID: 33261592
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.
    Amirian M; Montoya-Zegarra JA; Herzig I; Eggenberger Hotz P; Lichtensteiger L; Morf M; Züst A; Paysan P; Peterlik I; Scheib S; Füchslin RM; Stadelmann T; Schilling FP
    Med Phys; 2023 Oct; 50(10):6228-6242. PubMed ID: 36995003
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.