BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

142 related articles for article (PubMed ID: 15125150)

  • 21. Location of mammograms ROI's and reduction of false-positive.
    Salazar-Licea LA; Pedraza-Ortega JC; Pastrana-Palma A; Aceves-Fernandez MA
    Comput Methods Programs Biomed; 2017 May; 143():97-111. PubMed ID: 28391823
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Automatic Detection of Pectoral Muscle Region for Computer-Aided Diagnosis Using MIAS Mammograms.
    Yoon WB; Oh JE; Chae EY; Kim HH; Lee SY; Kim KG
    Biomed Res Int; 2016; 2016():5967580. PubMed ID: 27847817
    [TBL] [Abstract][Full Text] [Related]  

  • 23. 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]  

  • 24. Automatic breast region extraction from digital mammograms for PACS and telemammography applications.
    Lou SL; Lin HD; Lin KP; Hoogstrate D
    Comput Med Imaging Graph; 2000; 24(4):205-20. PubMed ID: 10842045
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Dual system approach to computer-aided detection of breast masses on mammograms.
    Wei J; Chan HP; Sahiner B; Hadjiiski LM; Helvie MA; Roubidoux MA; Zhou C; Ge J
    Med Phys; 2006 Nov; 33(11):4157-68. PubMed ID: 17153394
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Screening mammography-detected cancers: sensitivity of a computer-aided detection system applied to full-field digital mammograms.
    Yang SK; Moon WK; Cho N; Park JS; Cha JH; Kim SM; Kim SJ; Im JG
    Radiology; 2007 Jul; 244(1):104-11. PubMed ID: 17507722
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A fully automated scheme for mammographic segmentation and classification based on breast density and asymmetry.
    Tzikopoulos SD; Mavroforakis ME; Georgiou HV; Dimitropoulos N; Theodoridis S
    Comput Methods Programs Biomed; 2011 Apr; 102(1):47-63. PubMed ID: 21306782
    [TBL] [Abstract][Full Text] [Related]  

  • 28. [Application of a computer-aided detection (CAD) system to digitalized mammograms for identifying microcalcifications].
    Bazzocchi M; Facecchia I; Zuiani C; Londero V; Smania S; Bottigli U; Delogu P
    Radiol Med; 2001 May; 101(5):334-40. PubMed ID: 11438784
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Pectoral muscle segmentation: a review.
    Ganesan K; Acharya UR; Chua KC; Min LC; Abraham KT
    Comput Methods Programs Biomed; 2013 Apr; 110(1):48-57. PubMed ID: 23270962
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Computer-aided detection of breast masses on full field digital mammograms.
    Wei J; Sahiner B; Hadjiiski LM; Chan HP; Petrick N; Helvie MA; Roubidoux MA; Ge J; Zhou C
    Med Phys; 2005 Sep; 32(9):2827-38. PubMed ID: 16266097
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A probabilistic approach for breast boundary extraction in mammograms.
    Habibi Aghdam H; Puig D; Solanas A
    Comput Math Methods Med; 2013; 2013():408595. PubMed ID: 24324523
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Computer aided detection of clusters of microcalcifications on full field digital mammograms.
    Ge J; Sahiner B; Hadjiiski LM; Chan HP; Wei J; Helvie MA; Zhou C
    Med Phys; 2006 Aug; 33(8):2975-88. PubMed ID: 16964876
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Computer-aided detection in full-field digital mammography in a clinical population: performance of radiologist and technologists.
    van den Biggelaar FJ; Kessels AG; van Engelshoven JM; Boetes C; Flobbe K
    Breast Cancer Res Treat; 2010 Apr; 120(2):499-506. PubMed ID: 19418215
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Review of recent advances in segmentation of the breast boundary and the pectoral muscle in mammograms.
    Mustra M; Grgic M; Rangayyan RM
    Med Biol Eng Comput; 2016 Jul; 54(7):1003-24. PubMed ID: 26546074
    [TBL] [Abstract][Full Text] [Related]  

  • 35. False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification.
    Dhahbi S; Barhoumi W; Kurek J; Swiderski B; Kruk M; Zagrouba E
    Comput Methods Programs Biomed; 2018 Jul; 160():75-83. PubMed ID: 29728249
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Computer-aided detection system performance on current and previous digital mammograms in patients with contralateral metachronous breast cancer.
    Kim SJ; Moon WK; Cho N; Chang JM
    Acta Radiol; 2012 May; 53(4):376-81. PubMed ID: 22403080
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A completely automated CAD system for mass detection in a large mammographic database.
    Bellotti R; De Carlo F; Tangaro S; Gargano G; Maggipinto G; Castellano M; Massafra R; Cascio D; Fauci F; Magro R; Raso G; Lauria A; Forni G; Bagnasco S; Cerello P; Zanon E; Cheran SC; Lopez Torres E; Bottigli U; Masala GL; Oliva P; Retico A; Fantacci ME; Cataldo R; De Mitri I; De Nunzio G
    Med Phys; 2006 Aug; 33(8):3066-75. PubMed ID: 16964885
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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]  

  • 39. Breast mass contour segmentation algorithm in digital mammograms.
    Berber T; Alpkocak A; Balci P; Dicle O
    Comput Methods Programs Biomed; 2013 May; 110(2):150-9. PubMed ID: 23273502
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Potential contribution of computer-aided detection to the sensitivity of screening mammography.
    Warren Burhenne LJ; Wood SA; D'Orsi CJ; Feig SA; Kopans DB; O'Shaughnessy KF; Sickles EA; Tabar L; Vyborny CJ; Castellino RA
    Radiology; 2000 May; 215(2):554-62. PubMed ID: 10796939
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.