BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

686 related articles for article (PubMed ID: 21420580)

  • 1. Computer-aided diagnosis for the classification of breast masses in automated whole breast ultrasound images.
    Moon WK; Shen YW; Huang CS; Chiang LR; Chang RF
    Ultrasound Med Biol; 2011 Apr; 37(4):539-48. PubMed ID: 21420580
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Computerized characterization of breast masses on three-dimensional ultrasound volumes.
    Sahiner B; Chan HP; Roubidoux MA; Helvie MA; Hadjiiski LM; Ramachandran A; Paramagul C; LeCarpentier GL; Nees A; Blane C
    Med Phys; 2004 Apr; 31(4):744-54. PubMed ID: 15124991
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided diagnosis based on quantitative elastographic features with supersonic shear wave imaging.
    Xiao Y; Zeng J; Niu L; Zeng Q; Wu T; Wang C; Zheng R; Zheng H
    Ultrasound Med Biol; 2014 Feb; 40(2):275-86. PubMed ID: 24268454
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Computer-aided diagnosis based on speckle patterns in ultrasound images.
    Moon WK; Lo CM; Huang CS; Chen JH; Chang RF
    Ultrasound Med Biol; 2012 Jul; 38(7):1251-61. PubMed ID: 22579548
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-aided diagnosis with textural features for breast lesions in sonograms.
    Chen DR; Huang YL; Lin SH
    Comput Med Imaging Graph; 2011 Apr; 35(3):220-6. PubMed ID: 21131178
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Intensity-Invariant Texture Analysis for Classification of BI-RADS Category 3 Breast Masses.
    Lo CM; Moon WK; Huang CS; Chen JH; Yang MC; Chang RF
    Ultrasound Med Biol; 2015 Jul; 41(7):2039-48. PubMed ID: 25843514
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Classification of breast tumors using sonographic texture analysis.
    Ardakani AA; Gharbali A; Mohammadi A
    J Ultrasound Med; 2015 Feb; 34(2):225-31. PubMed ID: 25614395
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computer-aided diagnosis of solid breast nodules: use of an artificial neural network based on multiple sonographic features.
    Joo S; Yang YS; Moon WK; Kim HC
    IEEE Trans Med Imaging; 2004 Oct; 23(10):1292-300. PubMed ID: 15493696
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A new automated method for the segmentation and characterization of breast masses on ultrasound images.
    Cui J; Sahiner B; Chan HP; Nees A; Paramagul C; Hadjiiski LM; Zhou C; Shi J
    Med Phys; 2009 May; 36(5):1553-65. PubMed ID: 19544771
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Computer-aided diagnosis for 3-d power Doppler breast ultrasound.
    Lai YC; Huang YS; Wang DW; Tiu CM; Chou YH; Chang RF
    Ultrasound Med Biol; 2013 Apr; 39(4):555-67. PubMed ID: 23384464
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Combining support vector machine with genetic algorithm to classify ultrasound breast tumor images.
    Wu WJ; Lin SW; Moon WK
    Comput Med Imaging Graph; 2012 Dec; 36(8):627-33. PubMed ID: 22939834
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Effect of a novel segmentation algorithm on radiologists' diagnosis of breast masses using ultrasound imaging.
    Tian JW; Ning CP; Guo YH; Cheng HD; Tang XL
    Ultrasound Med Biol; 2012 Jan; 38(1):119-27. PubMed ID: 22104530
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Computer-aided classification of breast masses using speckle features of automated breast ultrasound images.
    Moon WK; Lo CM; Chang JM; Huang CS; Chen JH; Chang RF
    Med Phys; 2012 Oct; 39(10):6465-73. PubMed ID: 23039681
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Malignant and benign breast masses on 3D US volumetric images: effect of computer-aided diagnosis on radiologist accuracy.
    Sahiner B; Chan HP; Roubidoux MA; Hadjiiski LM; Helvie MA; Paramagul C; Bailey J; Nees AV; Blane C
    Radiology; 2007 Mar; 242(3):716-24. PubMed ID: 17244717
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI.
    Lee SH; Kim JH; Cho N; Park JS; Yang Z; Jung YS; Moon WK
    Med Phys; 2010 Aug; 37(8):3940-56. PubMed ID: 20879557
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Computer-aided diagnosis of breast DCE-MRI using pharmacokinetic model and 3-D morphology analysis.
    Wang TC; Huang YH; Huang CS; Chen JH; Huang GY; Chang YC; Chang RF
    Magn Reson Imaging; 2014 Apr; 32(3):197-205. PubMed ID: 24439361
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Computer-assisted assessment of ultrasound real-time elastography: initial experience in 145 breast lesions.
    Zhang X; Xiao Y; Zeng J; Qiu W; Qian M; Wang C; Zheng R; Zheng H
    Eur J Radiol; 2014 Jan; 83(1):e1-7. PubMed ID: 24148563
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review.
    Jalalian A; Mashohor SB; Mahmud HR; Saripan MI; Ramli AR; Karasfi B
    Clin Imaging; 2013; 37(3):420-6. PubMed ID: 23153689
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Completely automated segmentation approach for breast ultrasound images using multiple-domain features.
    Shan J; Cheng HD; Wang Y
    Ultrasound Med Biol; 2012 Feb; 38(2):262-75. PubMed ID: 22230134
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Computer-aided lesion diagnosis in automated 3-D breast ultrasound using coronal spiculation.
    Tan T; Platel B; Huisman H; Sánchez CI; Mus R; Karssemeijer N
    IEEE Trans Med Imaging; 2012 May; 31(5):1034-42. PubMed ID: 22271831
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 35.