BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

132 related articles for article (PubMed ID: 26409521)

  • 21. Optimizing Case-based detection performance in a multiview CAD system for mammography.
    Samulski M; Karssemeijer N
    IEEE Trans Med Imaging; 2011 Apr; 30(4):1001-9. PubMed ID: 21233045
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Computer aided detection of masses in mammograms as decision support.
    Karssemeijer N; Otten JD; Rijken H; Holland R
    Br J Radiol; 2006 Dec; 79 Spec No 2():S123-6. PubMed ID: 17209117
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Development of an automated method for detecting mammographic masses with a partial loss of region.
    Hatanaka Y; Hara T; Fujita H; Kasai S; Endo T; Iwase T
    IEEE Trans Med Imaging; 2001 Dec; 20(12):1209-14. PubMed ID: 11811821
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Computer-aided mass detection on digitized mammograms using adaptive thresholding and fuzzy entropy.
    Younesi F; Alam N; Zoroofi RA; Ahmadian A; Guiti M
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():5638-41. PubMed ID: 18003291
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Study of the effect of breast tissue density on detection of masses in mammograms.
    García-Manso A; García-Orellana CJ; González-Velasco HM; Gallardo-Caballero R; Macías-Macías M
    Comput Math Methods Med; 2013; 2013():213794. PubMed ID: 23573165
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Local Binary Patterns Descriptor Based on Sparse Curvelet Coefficients for False-Positive Reduction in Mammograms.
    Pawar MM; Talbar SN; Dudhane A
    J Healthc Eng; 2018; 2018():5940436. PubMed ID: 30356422
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms.
    Danala G; Patel B; Aghaei F; Heidari M; Li J; Wu T; Zheng B
    Ann Biomed Eng; 2018 Sep; 46(9):1419-1431. PubMed ID: 29748869
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Mass detection in digitized mammograms using two independent computer-assisted diagnosis schemes.
    Zheng B; Chang YH; Gur D
    AJR Am J Roentgenol; 1996 Dec; 167(6):1421-4. PubMed ID: 8956570
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Eigendetection of masses considering false positive reduction and breast density information.
    Freixenet J; Oliver A; Martí R; Lladó X; Pont J; Pérez E; Denton ER; Zwiggelaar R
    Med Phys; 2008 May; 35(5):1840-53. PubMed ID: 18561659
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Mass type-specific sparse representation for mass classification in computer-aided detection on mammograms.
    Kim DH; Lee SH; Ro YM
    Biomed Eng Online; 2013; 12 Suppl 1(Suppl 1):S3. PubMed ID: 24564973
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier.
    Delogu P; Evelina Fantacci M; Kasae P; Retico A
    Comput Biol Med; 2007 Oct; 37(10):1479-91. PubMed ID: 17383623
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Computer-aided detection (CAD) of breast masses in mammography: combined detection and ensemble classification.
    Choi JY; Kim DH; Plataniotis KN; Ro YM
    Phys Med Biol; 2014 Jul; 59(14):3697-719. PubMed ID: 24923292
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Combined adaptive enhancement and region-growing segmentation of breast masses on digitized mammograms.
    Petrick N; Chan HP; Sahiner B; Helvie MA
    Med Phys; 1999 Aug; 26(8):1642-54. PubMed ID: 10501064
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms.
    Gavrielides MA; Lo JY; Floyd CE
    Med Phys; 2002 Apr; 29(4):475-83. PubMed ID: 11998828
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Assessment of a novel mass detection algorithm in mammograms.
    Kozegar E; Soryani M; Minaei B; Domingues I
    J Cancer Res Ther; 2013; 9(4):592-600. PubMed ID: 24518702
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A New Breast Border Extraction and Contrast Enhancement Technique with Digital Mammogram Images for Improved Detection of Breast Cancer.
    Hazarika M; Mahanta LB
    Asian Pac J Cancer Prev; 2018 Aug; 19(8):2141-2148. PubMed ID: 30139217
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Learning contextual relationships in mammograms using a hierarchical pyramid neural network.
    Sajda P; Spence C; Pearson J
    IEEE Trans Med Imaging; 2002 Mar; 21(3):239-50. PubMed ID: 11989848
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Consistent performance measurement of a system to detect masses in mammograms based on blind feature extraction.
    García-Manso A; García-Orellana CJ; González-Velasco H; Gallardo-Caballero R; Macías MM
    Biomed Eng Online; 2013 Jan; 12():2. PubMed ID: 23305491
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Improved PAA algorithm for breast mass detection in mammograms.
    Liu W; Zeng P; Jiang J; Chen J; Chen L; Hu C; Jian W; Diao X; Wang X
    Comput Methods Programs Biomed; 2024 Jun; 251():108211. PubMed ID: 38744058
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Adaptive computer-aided diagnosis scheme of digitized mammograms.
    Zheng B; Chang YH; Gur D
    Acad Radiol; 1996 Oct; 3(10):806-14. PubMed ID: 8923899
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.