BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

706 related articles for article (PubMed ID: 30119844)

  • 1. Radiomics based detection and characterization of suspicious lesions on full field digital mammograms.
    Sapate SG; Mahajan A; Talbar SN; Sable N; Desai S; Thakur M
    Comput Methods Programs Biomed; 2018 Sep; 163():1-20. PubMed ID: 30119844
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.
    Zyout I; Czajkowska J; Grzegorzek M
    Comput Med Imaging Graph; 2015 Dec; 46 Pt 2():95-107. PubMed ID: 25795630
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Detection of breast masses in mammograms by density slicing and texture flow-field analysis.
    Mudigonda NR; Rangayyan RM; Desautels JE
    IEEE Trans Med Imaging; 2001 Dec; 20(12):1215-27. PubMed ID: 11811822
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-aided diagnosis of masses with full-field digital mammography.
    Li L; Clark RA; Thomas JA
    Acad Radiol; 2002 Jan; 9(1):4-12. PubMed ID: 11918357
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A method to test the reproducibility and to improve performance of computer-aided detection schemes for digitized mammograms.
    Zheng B; Gur D; Good WF; Hardesty LA
    Med Phys; 2004 Nov; 31(11):2964-72. PubMed ID: 15587648
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Computer-aided detection systems for breast masses: comparison of performances on full-field digital mammograms and digitized screen-film mammograms.
    Wei J; Hadjiiski LM; Sahiner B; Chan HP; Ge J; Roubidoux MA; Helvie MA; Zhou C; Wu YT; Paramagul C; Zhang Y
    Acad Radiol; 2007 Jun; 14(6):659-69. PubMed ID: 17502255
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An approach to the detection of lesions in mammograms using fuzzy image processing.
    Bayram B; Acar U
    J Int Med Res; 2007; 35(6):790-5. PubMed ID: 18034992
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.
    Sakai A; Onishi Y; Matsui M; Adachi H; Teramoto A; Saito K; Fujita H
    Radiol Phys Technol; 2020 Mar; 13(1):27-36. PubMed ID: 31686300
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computerized detection of breast tissue asymmetry depicted on bilateral mammograms: a preliminary study of breast risk stratification.
    Wang X; Lederman D; Tan J; Wang XH; Zheng B
    Acad Radiol; 2010 Oct; 17(10):1234-41. PubMed ID: 20619697
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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; CorrĂȘa Silva A; de Paiva AC; Gattass M
    Comput Methods Programs Biomed; 2018 Mar; 156():191-207. PubMed ID: 29428071
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving performance of computer-aided detection of masses by incorporating bilateral mammographic density asymmetry: an assessment.
    Wang X; Li L; Xu W; Liu W; Lederman D; Zheng B
    Acad Radiol; 2012 Mar; 19(3):303-10. PubMed ID: 22173323
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Computer-aided diagnosis: automatic detection of malignant masses in digitized mammograms.
    MĂ©ndez AJ; Tahoces PG; Lado MJ; Souto M; Vidal JJ
    Med Phys; 1998 Jun; 25(6):957-64. PubMed ID: 9650186
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Computer-aided detection; the effect of training databases on detection of subtle breast masses.
    Zheng B; Wang X; Lederman D; Tan J; Gur D
    Acad Radiol; 2010 Nov; 17(11):1401-8. PubMed ID: 20650667
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.
    Patel BK; Ranjbar S; Wu T; Pockaj BA; Li J; Zhang N; Lobbes M; Zhang B; Mitchell JR
    Eur J Radiol; 2018 Jan; 98():207-213. PubMed ID: 29279165
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comparison study of image features between FFDM and film mammogram images.
    Jing H; Yang Y; Wernick MN; Yarusso LM; Nishikawa RM
    Med Phys; 2012 Jul; 39(7):4386-94. PubMed ID: 22830771
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Improving performance of computer-aided detection scheme by combining results from two machine learning classifiers.
    Park SC; Pu J; Zheng B
    Acad Radiol; 2009 Mar; 16(3):266-74. PubMed ID: 19201355
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A concentric morphology model for the detection of masses in mammography.
    Eltonsy NH; Tourassi GD; Elmaghraby AS
    IEEE Trans Med Imaging; 2007 Jun; 26(6):880-9. PubMed ID: 17679338
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 36.