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 *

114 related articles for article (PubMed ID: 38921942)

  • 1. Breast Cancer Diagnosis Method Based on Cross-Mammogram Four-View Interactive Learning.
    Wen X; Li J; Yang L
    Tomography; 2024 Jun; 10(6):848-868. PubMed ID: 38921942
    [TBL] [Abstract][Full Text] [Related]  

  • 2. RAMS: Remote and automatic mammogram screening.
    Cogan T; Cogan M; Tamil L
    Comput Biol Med; 2019 Apr; 107():18-29. PubMed ID: 30771549
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Bilateral analysis based false positive reduction for computer-aided mass detection.
    Wu YT; Wei J; Hadjiiski LM; Sahiner B; Zhou C; Ge J; Shi J; Zhang Y; Chan HP
    Med Phys; 2007 Aug; 34(8):3334-44. PubMed ID: 17879797
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Fusion of k-Gabor features from medio-lateral-oblique and craniocaudal view mammograms for improved breast cancer diagnosis.
    Sasikala S; Ezhilarasi M
    J Cancer Res Ther; 2018; 14(5):1036-1041. PubMed ID: 30197344
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.
    Jones MA; Sadeghipour N; Chen X; Islam W; Zheng B
    Med Phys; 2023 Dec; 50(12):7670-7683. PubMed ID: 37083190
    [TBL] [Abstract][Full Text] [Related]  

  • 6. FSE-Net: feature selection and enhancement network for mammogram classification.
    Liao C; Wen X; Qi S; Liu Y; Cao R
    Phys Med Biol; 2023 Sep; 68(19):. PubMed ID: 37712226
    [No Abstract]   [Full Text] [Related]  

  • 7. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.
    Heidari M; Khuzani AZ; Hollingsworth AB; Danala G; Mirniaharikandehei S; Qiu Y; Liu H; Zheng B
    Phys Med Biol; 2018 Jan; 63(3):035020. PubMed ID: 29239858
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Towards improved breast mass detection using dual-view mammogram matching.
    Yan Y; Conze PH; Lamard M; Quellec G; Cochener B; Coatrieux G
    Med Image Anal; 2021 Jul; 71():102083. PubMed ID: 33979759
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Mammogram mass segmentation and classification based on cross-view VAE and spatial hidden factor disentanglement.
    Ma Y; Peng Y
    Phys Eng Sci Med; 2024 Mar; 47(1):223-238. PubMed ID: 38150059
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Geometry-Based Pectoral Muscle Segmentation From MLO Mammogram Views.
    Taghanaki SA; Liu Y; Miles B; Hamarneh G
    IEEE Trans Biomed Eng; 2017 Nov; 64(11):2662-2671. PubMed ID: 28129144
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. Joint two-view information for computerized detection of microcalcifications on mammograms.
    Sahiner B; Chan HP; Hadjiiski LM; Helvie MA; Paramagul C; Ge J; Wei J; Zhou C
    Med Phys; 2006 Jul; 33(7):2574-85. PubMed ID: 16898462
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis.
    Mazurowski MA; Lo JY; Harrawood BP; Tourassi GD
    J Biomed Inform; 2011 Oct; 44(5):815-23. PubMed ID: 21554985
    [TBL] [Abstract][Full Text] [Related]  

  • 15. New convolutional neural network model for screening and diagnosis of mammograms.
    Zhang C; Zhao J; Niu J; Li D
    PLoS One; 2020; 15(8):e0237674. PubMed ID: 32790772
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A bilateral analysis scheme for false positive reduction in mammogram mass detection.
    Li Y; Chen H; Yang Y; Cheng L; Cao L
    Comput Biol Med; 2015 Feb; 57():84-95. PubMed ID: 25544726
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A new idea for visualization of lesions distribution in mammogram based on CPD registration method.
    Pan X; Qi B; Yu H; Wei H; Kang Y
    Technol Health Care; 2017 Jul; 25(S1):459-467. PubMed ID: 28582934
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Computer-aided detection of breast masses on mammograms: dual system approach with two-view analysis.
    Wei J; Chan HP; Sahiner B; Zhou C; Hadjiiski LM; Roubidoux MA; Helvie MA
    Med Phys; 2009 Oct; 36(10):4451-60. PubMed ID: 19928076
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.
    Pérez NP; Guevara López MA; Silva A; Ramos I
    Artif Intell Med; 2015 Jan; 63(1):19-31. PubMed ID: 25555756
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.