BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

212 related articles for article (PubMed ID: 30216093)

  • 1. CBCT image based segmentation method for tooth pulp cavity region extraction.
    Wang L; Li JP; Ge ZP; Li G
    Dentomaxillofac Radiol; 2019 Feb; 48(2):20180236. PubMed ID: 30216093
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Micro-Computed Tomography-Guided Artificial Intelligence for Pulp Cavity and Tooth Segmentation on Cone-beam Computed Tomography.
    Lin X; Fu Y; Ren G; Yang X; Duan W; Chen Y; Zhang Q
    J Endod; 2021 Dec; 47(12):1933-1941. PubMed ID: 34520812
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [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]  

  • 4. Refined tooth and pulp segmentation using U-Net in CBCT image.
    Duan W; Chen Y; Zhang Q; Lin X; Yang X
    Dentomaxillofac Radiol; 2021 Sep; 50(6):20200251. PubMed ID: 33444070
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Root Canal Segmentation in CBCT Images by 3D U-Net with Global and Local Combination Loss.
    Zhang J; Xia W; Dong J; Tang Z; Zhao Q
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3097-3100. PubMed ID: 34891897
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of an adaptive local thresholding method on CBCT and µCT endodontic images.
    Michetti J; Basarab A; Diemer F; Kouame D
    Phys Med Biol; 2017 Dec; 63(1):015020. PubMed ID: 28976357
    [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. Age estimation based on 3D pulp chamber segmentation of first molars from cone-beam-computed tomography by integrated deep learning and level set.
    Zheng Q; Ge Z; Du H; Li G
    Int J Legal Med; 2021 Jan; 135(1):365-373. PubMed ID: 33185706
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of the accuracy of cone-beam computed tomography image segmentation of isolated tooth roots based on the dynamic threshold method.
    Su S; Liu YM; Zhan LP; Gao SY; He C; Zhang Q; Huang XF
    BMC Oral Health; 2023 Oct; 23(1):752. PubMed ID: 37833773
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [A tooth cone beam computer tomography image segmentation method based on the local Gaussian distribution fitting].
    Liu S; Wang Y
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2019 Apr; 36(2):291-297. PubMed ID: 31016947
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A level-set based approach for anterior teeth segmentation in cone beam computed tomography images.
    Ji DX; Ong SH; Foong KW
    Comput Biol Med; 2014 Jul; 50():116-28. PubMed ID: 24853776
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. 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]  

  • 14. Evaluation of volumetric changes of teeth in a Brazilian population by using cone beam computed tomography.
    Porto LV; Celestino da Silva Neto J; Anjos Pontual AD; Catunda RQ
    J Forensic Leg Med; 2015 Nov; 36():4-9. PubMed ID: 26320003
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images.
    Pei Y; Ai X; Zha H; Xu T; Ma G
    Med Phys; 2016 Sep; 43(9):5040. PubMed ID: 27587034
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images.
    Fan Y; Beare R; Matthews H; Schneider P; Kilpatrick N; Clement J; Claes P; Penington A; Adamson C
    Dentomaxillofac Radiol; 2019 Feb; 48(2):20180261. PubMed ID: 30379569
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Root canal treatment planning by automatic tooth and root canal segmentation in dental CBCT with deep multi-task feature learning.
    Wang Y; Xia W; Yan Z; Zhao L; Bian X; Liu C; Qi Z; Zhang S; Tang Z
    Med Image Anal; 2023 Apr; 85():102750. PubMed ID: 36682153
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Age estimation based on 3D pulp segmentation of first molars from CBCT images using U-Net.
    Song Y; Yang H; Ge Z; Du H; Li G
    Dentomaxillofac Radiol; 2023 Oct; 52(7):20230177. PubMed ID: 37427595
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Dental Segmentation in Cone-beam Computed Tomography Images Using Watershed and Morphology Operators.
    Kakehbaraei S; Seyedarabi H; Zenouz AT
    J Med Signals Sens; 2018; 8(2):119-124. PubMed ID: 29928637
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.