These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

120 related articles for article (PubMed ID: 28269184)

  • 21. 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]  

  • 22. Automated breast ultrasound: basic principles and emerging clinical applications.
    Zanotel M; Bednarova I; Londero V; Linda A; Lorenzon M; Girometti R; Zuiani C
    Radiol Med; 2018 Jan; 123(1):1-12. PubMed ID: 28849324
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breasts: Reader Study of Mammography-Negative and Mammography-Positive Cancers.
    Giger ML; Inciardi MF; Edwards A; Papaioannou J; Drukker K; Jiang Y; Brem R; Brown JB
    AJR Am J Roentgenol; 2016 Jun; 206(6):1341-50. PubMed ID: 27043979
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Automated Three-dimensional Breast US for Screening: Technique, Artifacts, and Lesion Characterization.
    van Zelst JCM; Mann RM
    Radiographics; 2018; 38(3):663-683. PubMed ID: 29624482
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Radiologists' performance in the detection of benign and malignant masses with 3D automated breast ultrasound (ABUS).
    Chang JM; Moon WK; Cho N; Park JS; Kim SJ
    Eur J Radiol; 2011 Apr; 78(1):99-103. PubMed ID: 21330080
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.
    Wang Y; Wang N; Xu M; Yu J; Qin C; Luo X; Yang X; Wang T; Li A; Ni D
    IEEE Trans Med Imaging; 2020 Apr; 39(4):866-876. PubMed ID: 31442972
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Automated whole breast ultrasound.
    Kaplan SS
    Radiol Clin North Am; 2014 May; 52(3):539-46. PubMed ID: 24792655
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Double reading of automated breast ultrasound with digital mammography or digital breast tomosynthesis for breast cancer screening.
    Lee JM; Partridge SC; Liao GJ; Hippe DS; Kim AE; Lee CI; Rahbar H; Scheel JR; Lehman CD
    Clin Imaging; 2019; 55():119-125. PubMed ID: 30807927
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Diagnostic performance of automated breast ultrasound as a replacement for a hand-held second-look ultrasound for breast lesions detected initially on magnetic resonance imaging.
    Chae EY; Shin HJ; Kim HJ; Yoo H; Baek S; Cha JH; Kim HH
    Ultrasound Med Biol; 2013 Dec; 39(12):2246-54. PubMed ID: 24035627
    [TBL] [Abstract][Full Text] [Related]  

  • 30. The lesion detection efficacy of deep learning on automatic breast ultrasound and factors affecting its efficacy: a pilot study.
    PhD XL; Xu M; Tang G; PhD YW; Wang N; PhD DN; PhD XL; Li AH
    Br J Radiol; 2022 Feb; 95(1130):20210438. PubMed ID: 34860574
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Computer-aided tumor detection based on multi-scale blob detection algorithm in automated breast ultrasound images.
    Moon WK; Shen YW; Bae MS; Huang CS; Chen JH; Chang RF
    IEEE Trans Med Imaging; 2013 Jul; 32(7):1191-200. PubMed ID: 23232413
    [TBL] [Abstract][Full Text] [Related]  

  • 32. 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]  

  • 33. Automated breast ultrasound: lesion detection and BI-RADS classification--a pilot study.
    Wenkel E; Heckmann M; Heinrich M; Schwab SA; Uder M; Schulz-Wendtland R; Bautz WA; Janka R
    Rofo; 2008 Sep; 180(9):804-8. PubMed ID: 18704878
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Computerized analysis of shadowing on breast ultrasound for improved lesion detection.
    Drukker K; Giger ML; Mendelson EB
    Med Phys; 2003 Jul; 30(7):1833-42. PubMed ID: 12906202
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Interpretation of automated breast ultrasound (ABUS) with and without knowledge of mammography: a reader performance study.
    Skaane P; Gullien R; Eben EB; Sandhaug M; Schulz-Wendtland R; Stoeblen F
    Acta Radiol; 2015 Apr; 56(4):404-12. PubMed ID: 24682405
    [TBL] [Abstract][Full Text] [Related]  

  • 36. 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]  

  • 37. A hierarchical model for automated breast lesion detection from ultrasound 3D data.
    Deng Y; Liu W; Jago J
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():145-8. PubMed ID: 26736221
    [TBL] [Abstract][Full Text] [Related]  

  • 38. [Characterization of sonographically detected breast lesions using three-dimensional data sets].
    Fischer T; Filimonow S; Hamm B; Slowinski T; Thomas A
    Rofo; 2006 Dec; 178(12):1224-34. PubMed ID: 17136646
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Mass Segmentation in Automated 3-D Breast Ultrasound Using Adaptive Region Growing and Supervised Edge-Based Deformable Model.
    Kozegar E; Soryani M; Behnam H; Salamati M; Tan T
    IEEE Trans Med Imaging; 2018 Apr; 37(4):918-928. PubMed ID: 29610071
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Combining CRF and multi-hypothesis detection for accurate lesion segmentation in breast sonograms.
    Hao Z; Wang Q; Seong YK; Lee JH; Ren H; Kim JY
    Med Image Comput Comput Assist Interv; 2012; 15(Pt 1):504-11. PubMed ID: 23285589
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.