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 *

144 related articles for article (PubMed ID: 33921353)

  • 1. Deep Active Learning for Automatic Segmentation of Maxillary Sinus Lesions Using a Convolutional Neural Network.
    Jung SK; Lim HK; Lee S; Cho Y; Song IS
    Diagnostics (Basel); 2021 Apr; 11(4):. PubMed ID: 33921353
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic detection and segmentation of morphological changes of the maxillary sinus mucosa on cone-beam computed tomography images using a three-dimensional convolutional neural network.
    Hung KF; Ai QYH; King AD; Bornstein MM; Wong LM; Leung YY
    Clin Oral Investig; 2022 May; 26(5):3987-3998. PubMed ID: 35032193
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.
    Abbani N; Baudier T; Rit S; Franco FD; Okoli F; Jaouen V; Tilquin F; Barateau A; Simon A; de Crevoisier R; Bert J; Sarrut D
    Med Phys; 2022 Nov; 49(11):6930-6944. PubMed ID: 36000762
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images.
    Bayrakdar IS; Elfayome NS; Hussien RA; Gulsen IT; Kuran A; Gunes I; Al-Badr A; Celik O; Orhan K
    Dentomaxillofac Radiol; 2024 Apr; 53(4):256-266. PubMed ID: 38502963
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.
    Morgan N; Van Gerven A; Smolders A; de Faria Vasconcelos K; Willems H; Jacobs R
    Sci Rep; 2022 May; 12(1):7523. PubMed ID: 35525857
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images.
    Choi H; Jeon KJ; Kim YH; Ha EG; Lee C; Han SS
    Sci Rep; 2022 Aug; 12(1):14009. PubMed ID: 35978086
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep semi-supervised learning for automatic segmentation of inferior alveolar nerve using a convolutional neural network.
    Lim HK; Jung SK; Kim SH; Cho Y; Song IS
    BMC Oral Health; 2021 Dec; 21(1):630. PubMed ID: 34876105
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles.
    Wang XR; Ma X; Jin LX; Gao YJ; Xue YJ; Li JL; Bai WX; Han MF; Zhou Q; Shi F; Wang J
    Front Neuroinform; 2022; 16():937891. PubMed ID: 36120083
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. The effect of deep learning-based lesion segmentation on failure load calculations of metastatic femurs using finite element analysis.
    Ataei A; Eggermont F; Verdonschot N; Lessmann N; Tanck E
    Bone; 2024 Feb; 179():116987. PubMed ID: 38061504
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. Comparison of 2D, 2.5D, and 3D segmentation networks for maxillary sinuses and lesions in CBCT images.
    Yoo YS; Kim D; Yang S; Kang SR; Kim JE; Huh KH; Lee SS; Heo MS; Yi WJ
    BMC Oral Health; 2023 Nov; 23(1):866. PubMed ID: 37964229
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep learning for detection and 3D segmentation of maxillofacial bone lesions in cone beam CT.
    Yeshua T; Ladyzhensky S; Abu-Nasser A; Abdalla-Aslan R; Boharon T; Itzhak-Pur A; Alexander A; Chaurasia A; Cohen A; Sosna J; Leichter I; Nadler C
    Eur Radiol; 2023 Nov; 33(11):7507-7518. PubMed ID: 37191921
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Comparison of convolutional neural network training strategies for cone-beam CT image segmentation.
    Minnema J; Wolff J; Koivisto J; Lucka F; Batenburg KJ; Forouzanfar T; van Eijnatten M
    Comput Methods Programs Biomed; 2021 Aug; 207():106192. PubMed ID: 34062493
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic segmentation of the pharyngeal airway space with convolutional neural network.
    Shujaat S; Jazil O; Willems H; Van Gerven A; Shaheen E; Politis C; Jacobs R
    J Dent; 2021 Aug; 111():103705. PubMed ID: 34077802
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. [Automated system of the determination of maxillary sinus morphometric parameters].
    Kabak SL; Karapetyan GM; Melnichenko YM; Savrasova NA; Kosik II
    Vestn Otorinolaringol; 2021; 86(2):49-53. PubMed ID: 33929152
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.