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Items: 1 to 20 of 130

1.

Training the ACRIN 6666 Investigators and effects of feedback on breast ultrasound interpretive performance and agreement in BI-RADS ultrasound feature analysis.

Berg WA, Blume JD, Cormack JB, Mendelson EB.

AJR Am J Roentgenol. 2012 Jul;199(1):224-35. doi: 10.2214/AJR.11.7324.

2.

Interpretation of positron emission mammography and MRI by experienced breast imaging radiologists: performance and observer reproducibility.

Narayanan D, Madsen KS, Kalinyak JE, Berg WA.

AJR Am J Roentgenol. 2011 Apr;196(4):971-81. doi: 10.2214/AJR.10.5081.

3.
4.

Differentiating benign from malignant solid breast masses: value of shear wave elastography according to lesion stiffness combined with greyscale ultrasound according to BI-RADS classification.

Evans A, Whelehan P, Thomson K, Brauer K, Jordan L, Purdie C, McLean D, Baker L, Vinnicombe S, Thompson A.

Br J Cancer. 2012 Jul 10;107(2):224-9. doi: 10.1038/bjc.2012.253. Epub 2012 Jun 12.

5.

Observer variability of Breast Imaging Reporting and Data System (BI-RADS) for breast ultrasound.

Lee HJ, Kim EK, Kim MJ, Youk JH, Lee JY, Kang DR, Oh KK.

Eur J Radiol. 2008 Feb;65(2):293-8. Epub 2007 May 24.

PMID:
17531417
6.

A comparison of logistic regression analysis and an artificial neural network using the BI-RADS lexicon for ultrasonography in conjunction with introbserver variability.

Kim SM, Han H, Park JM, Choi YJ, Yoon HS, Sohn JH, Baek MH, Kim YN, Chae YM, June JJ, Lee J, Jeon YH.

J Digit Imaging. 2012 Oct;25(5):599-606.

7.

Quantitative shear wave ultrasound elastography: initial experience in solid breast masses.

Evans A, Whelehan P, Thomson K, McLean D, Brauer K, Purdie C, Jordan L, Baker L, Thompson A.

Breast Cancer Res. 2010;12(6):R104. doi: 10.1186/bcr2787. Epub 2010 Dec 1.

8.

Observer agreement using the ACR Breast Imaging Reporting and Data System (BI-RADS)-ultrasound, First Edition (2003).

Park CS, Lee JH, Yim HW, Kang BJ, Kim HS, Jung JI, Jung NY, Kim SH.

Korean J Radiol. 2007 Sep-Oct;8(5):397-402.

9.

Lesion detection and characterization in a breast US phantom: results of the ACRIN 6666 Investigators.

Berg WA, Blume JD, Cormack JB, Mendelson EB, Madsen EL; ACRIN 6666 Investigators.

Radiology. 2006 Jun;239(3):693-702. Epub 2006 Apr 26.

PMID:
16641344
10.

Clinical application of qualitative assessment for breast masses in shear-wave elastography.

Gweon HM, Youk JH, Son EJ, Kim JA.

Eur J Radiol. 2013 Nov;82(11):e680-5. doi: 10.1016/j.ejrad.2013.08.004. Epub 2013 Aug 14.

PMID:
23988689
11.

Bayesian probability of malignancy with BI-RADS sonographic features.

Bouzghar G, Levenback BJ, Sultan LR, Venkatesh SS, Cwanger A, Conant EF, Sehgal CM.

J Ultrasound Med. 2014 Apr;33(4):641-8. doi: 10.7863/ultra.33.4.641.

12.

Interobserver variability of ultrasound elastography: how it affects the diagnosis of breast lesions.

Yoon JH, Kim MH, Kim EK, Moon HJ, Kwak JY, Kim MJ.

AJR Am J Roentgenol. 2011 Mar;196(3):730-6. doi: 10.2214/AJR.10.4654.

PMID:
21343520
13.

Nonmasslike enhancement at breast MR imaging: the added value of mammography and US for lesion categorization.

Thomassin-Naggara I, Trop I, Chopier J, David J, Lalonde L, Darai E, Rouzier R, Uzan S.

Radiology. 2011 Oct;261(1):69-79. doi: 10.1148/radiol.11110190. Epub 2011 Jul 19.

PMID:
21771958
14.

Comparison of conventional and automated breast volume ultrasound in the description and characterization of solid breast masses based on BI-RADS features.

Kim H, Cha JH, Oh HY, Kim HH, Shin HJ, Chae EY.

Breast Cancer. 2014 Jul;21(4):423-8. doi: 10.1007/s12282-012-0419-1. Epub 2012 Oct 20.

PMID:
23086698
15.

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. doi: 10.1177/0284185114528835. Epub 2014 Mar 28.

PMID:
24682405
16.

Interobserver variability of ultrasound elastography and the ultrasound BI-RADS lexicon of breast lesions.

Park CS, Kim SH, Jung NY, Choi JJ, Kang BJ, Jung HS.

Breast Cancer. 2015 Mar;22(2):153-60. doi: 10.1007/s12282-013-0465-3. Epub 2013 Apr 13.

PMID:
23584596
17.

Targeted ultrasound in women younger than 30 years with focal breast signs or symptoms: outcomes analyses and management implications.

Loving VA, DeMartini WB, Eby PR, Gutierrez RL, Peacock S, Lehman CD.

AJR Am J Roentgenol. 2010 Dec;195(6):1472-7. doi: 10.2214/AJR.10.4396.

PMID:
21098212
18.

Computer aided classification system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS).

Shen WC, Chang RF, Moon WK.

Ultrasound Med Biol. 2007 Nov;33(11):1688-98. Epub 2007 Aug 3.

PMID:
17681678
19.

Three-dimensional shear-wave elastography for differentiating benign and malignant breast lesions: comparison with two-dimensional shear-wave elastography.

Youk JH, Gweon HM, Son EJ, Chung J, Kim JA, Kim EK.

Eur Radiol. 2013 Jun;23(6):1519-27. doi: 10.1007/s00330-012-2736-3. Epub 2012 Dec 2.

PMID:
23212276
20.

Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features.

Grimm LJ, Ghate SV, Yoon SC, Kuzmiak CM, Kim C, Mazurowski MA.

Med Phys. 2014 Mar;41(3):031909. doi: 10.1118/1.4866379.

PMID:
24593727
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