BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

165 related articles for article (PubMed ID: 32206943)

  • 1. Segmentation of Masses on Mammograms Using Data Augmentation and Deep Learning.
    Zeiser FA; da Costa CA; Zonta T; Marques NMC; Roehe AV; Moreno M; da Rosa Righi R
    J Digit Imaging; 2020 Aug; 33(4):858-868. PubMed ID: 32206943
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
    Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS
    Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.
    Al-Masni MA; Al-Antari MA; Park JM; Gi G; Kim TY; Rivera P; Valarezo E; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Apr; 157():85-94. PubMed ID: 29477437
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Convolutional neural network for automated mass segmentation in mammography.
    Abdelhafiz D; Bi J; Ammar R; Yang C; Nabavi S
    BMC Bioinformatics; 2020 Dec; 21(Suppl 1):192. PubMed ID: 33297952
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.
    Samala RK; Chan HP; Hadjiiski L; Helvie MA; Wei J; Cha K
    Med Phys; 2016 Dec; 43(12):6654. PubMed ID: 27908154
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.
    Al-Antari MA; Al-Masni MA; Kim TS
    Adv Exp Med Biol; 2020; 1213():59-72. PubMed ID: 32030663
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep Learning to Improve Breast Cancer Detection on Screening Mammography.
    Shen L; Margolies LR; Rothstein JH; Fluder E; McBride R; Sieh W
    Sci Rep; 2019 Aug; 9(1):12495. PubMed ID: 31467326
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep Convolutional Neural Networks for breast cancer screening.
    Chougrad H; Zouaki H; Alheyane O
    Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427
    [TBL] [Abstract][Full Text] [Related]  

  • 9. YOLO Based Breast Masses Detection and Classification in Full-Field Digital Mammograms.
    Aly GH; Marey M; El-Sayed SA; Tolba MF
    Comput Methods Programs Biomed; 2021 Mar; 200():105823. PubMed ID: 33190942
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated pectoral muscle identification on MLO-view mammograms: Comparison of deep neural network to conventional computer vision.
    Ma X; Wei J; Zhou C; Helvie MA; Chan HP; Hadjiiski LM; Lu Y
    Med Phys; 2019 May; 46(5):2103-2114. PubMed ID: 30771257
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.
    Bandeira Diniz JO; Bandeira Diniz PH; Azevedo Valente TL; Corrêa Silva A; de Paiva AC; Gattass M
    Comput Methods Programs Biomed; 2018 Mar; 156():191-207. PubMed ID: 29428071
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms.
    Al-Antari MA; Han SM; Kim TS
    Comput Methods Programs Biomed; 2020 Nov; 196():105584. PubMed ID: 32554139
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep convolutional neural networks for mammography: advances, challenges and applications.
    Abdelhafiz D; Yang C; Ammar R; Nabavi S
    BMC Bioinformatics; 2019 Jun; 20(Suppl 11):281. PubMed ID: 31167642
    [TBL] [Abstract][Full Text] [Related]  

  • 14. New one-step model of breast tumor locating based on deep learning.
    Tao C; Chen K; Han L; Peng Y; Li C; Hua Z; Lin J
    J Xray Sci Technol; 2019; 27(5):839-856. PubMed ID: 31306148
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network.
    Jung H; Kim B; Lee I; Yoo M; Lee J; Ham S; Woo O; Kang J
    PLoS One; 2018; 13(9):e0203355. PubMed ID: 30226841
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.
    Pérez-Benito FJ; Signol F; Perez-Cortes JC; Fuster-Baggetto A; Pollan M; Pérez-Gómez B; Salas-Trejo D; Casals M; Martínez I; LLobet R
    Comput Methods Programs Biomed; 2020 Oct; 195():105668. PubMed ID: 32755754
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Detection and classification of the breast abnormalities in digital mammograms via regional Convolutional Neural Network.
    Al-Masni MA; Al-Antari MA; Park JM; Gi G; Kim TY; Rivera P; Valarezo E; Han SM; Kim TS
    Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1230-1233. PubMed ID: 29060098
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning for mass detection in Full Field Digital Mammograms.
    Agarwal R; Díaz O; Yap MH; Lladó X; Martí R
    Comput Biol Med; 2020 Jun; 121():103774. PubMed ID: 32339095
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.
    Hinton B; Ma L; Mahmoudzadeh AP; Malkov S; Fan B; Greenwood H; Joe B; Lee V; Kerlikowske K; Shepherd J
    Cancer Imaging; 2019 Jun; 19(1):41. PubMed ID: 31228956
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep learning methods for lesion detection on mammography images: a comparative analysis.
    Ribeiro RF; Gomes-Fonseca J; Torres HR; Oliveira B; Vilhena E; Morais P; Vilaca JL
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3526-3529. PubMed ID: 36086472
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.