BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

187 related articles for article (PubMed ID: 32164532)

  • 1. A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis.
    Fanizzi A; Basile TMA; Losurdo L; Bellotti R; Bottigli U; Dentamaro R; Didonna V; Fausto A; Massafra R; Moschetta M; Popescu O; Tamborra P; Tangaro S; La Forgia D
    BMC Bioinformatics; 2020 Mar; 21(Suppl 2):91. PubMed ID: 32164532
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Breast microcalcifications detection based on fusing features with DTCWT.
    Wang Z; Xin J; Zhang Q; Gao S; Ma C; Ren J; Zhang H; Qian W; Zhu W; Zhang X; Liu J
    J Xray Sci Technol; 2020; 28(2):197-218. PubMed ID: 31985483
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Breast cancer diagnosis: analyzing texture of tissue surrounding microcalcifications.
    Karahaliou AN; Boniatis IS; Skiadopoulos SG; Sakellaropoulos FN; Arikidis NS; Likaki EA; Panayiotakis GS; Costaridou LI
    IEEE Trans Inf Technol Biomed; 2008 Nov; 12(6):731-8. PubMed ID: 19000952
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A swarm optimized neural network system for classification of microcalcification in mammograms.
    Dheeba J; Selvi ST
    J Med Syst; 2012 Oct; 36(5):3051-61. PubMed ID: 21947904
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A novel approach for detection and classification of mammographic microcalcifications using wavelet analysis and extreme learning machine.
    Malar E; Kandaswamy A; Chakravarthy D; Giri Dharan A
    Comput Biol Med; 2012 Sep; 42(9):898-905. PubMed ID: 22871899
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A novel machine learning approach on texture analysis for automatic breast microcalcification diagnosis classification of mammogram images.
    Sarvestani ZM; Jamali J; Taghizadeh M; Dindarloo MHF
    J Cancer Res Clin Oncol; 2023 Aug; 149(9):6151-6170. PubMed ID: 36680580
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces.
    Chan HP; Sahiner B; Lam KL; Petrick N; Helvie MA; Goodsitt MM; Adler DD
    Med Phys; 1998 Oct; 25(10):2007-19. PubMed ID: 9800710
    [TBL] [Abstract][Full Text] [Related]  

  • 8. SVM based system for classification of microcalcifications in digital mammograms.
    Singh S; Kumar V; Verma HK; Singh D
    Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():4747-50. PubMed ID: 17945853
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Quantitative comparison of clustered microcalcifications in for-presentation and for-processing mammograms in full-field digital mammography.
    Wang J; Nishikawa RM; Yang Y
    Med Phys; 2017 Jul; 44(7):3726-3738. PubMed ID: 28477395
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Decision support system for breast cancer detection using mammograms.
    Ganesan K; Acharya RU; Chua CK; Min LC; Mathew B; Thomas AK
    Proc Inst Mech Eng H; 2013 Jul; 227(7):721-32. PubMed ID: 23636749
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform.
    Jian W; Sun X; Luo S
    Biomed Eng Online; 2012 Dec; 11():96. PubMed ID: 23253202
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Segmentation for the enhancement of microcalcifications in digital mammograms.
    Milosevic M; Jankovic D; Peulic A
    Technol Health Care; 2014; 22(5):701-15. PubMed ID: 25059254
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network.
    Chan HP; Sahiner B; Petrick N; Helvie MA; Lam KL; Adler DD; Goodsitt MM
    Phys Med Biol; 1997 Mar; 42(3):549-67. PubMed ID: 9080535
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Global parenchymal texture features based on histograms of oriented gradients improve cancer development risk estimation from healthy breasts.
    Pérez-Benito FJ; Signol F; Pérez-Cortés JC; Pollán M; Pérez-Gómez B; Salas-Trejo D; Casals M; Martínez I; LLobet R
    Comput Methods Programs Biomed; 2019 Aug; 177():123-132. PubMed ID: 31319940
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Texture analysis of tissue surrounding microcalcifications on mammograms for breast cancer diagnosis.
    Karahaliou A; Skiadopoulos S; Boniatis I; Sakellaropoulos P; Likaki E; Panayiotakis G; Costaridou L
    Br J Radiol; 2007 Aug; 80(956):648-56. PubMed ID: 17621604
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Analysis of framelets for breast cancer diagnosis.
    Thivya KS; Sakthivel P; Venkata Sai PM
    Technol Health Care; 2016; 24(1):21-9. PubMed ID: 26409529
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Breast mass detection and diagnosis using fused features with density.
    Wang Z; Huang Y; Li M; Zhang H; Li C; Xin J; Qian W
    J Xray Sci Technol; 2019; 27(2):321-342. PubMed ID: 30856154
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fuzzy technique for microcalcifications clustering in digital mammograms.
    Vivona L; Cascio D; Fauci F; Raso G
    BMC Med Imaging; 2014 Jun; 14():23. PubMed ID: 24961885
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Microcalcification detection in full-field digital mammograms: A fully automated computer-aided system.
    Basile TMA; Fanizzi A; Losurdo L; Bellotti R; Bottigli U; Dentamaro R; Didonna V; Fausto A; Massafra R; Moschetta M; Tamborra P; Tangaro S; La Forgia D
    Phys Med; 2019 Aug; 64():1-9. PubMed ID: 31515007
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.