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Results: 1 to 20 of 102

Similar articles for PubMed (Select 25159706)

1.

Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study.

Gierach GL, Li H, Loud JT, Greene MH, Chow CK, Lan L, Prindiville SA, Eng-Wong J, Soballe PW, Giambartolomei C, Mai PL, Galbo CE, Nichols K, Calzone KA, Olopade OI, Gail MH, Giger ML.

Breast Cancer Res. 2014;16(4):424. doi: 10.1186/PREACCEPT-1744229618121391. Epub 2014 Aug 23.

2.

Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms.

Li H, Giger ML, Olopade OI, Margolis A, Lan L, Chinander MR.

Acad Radiol. 2005 Jul;12(7):863-73.

PMID:
16039540
3.

Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers.

Huo Z, Giger ML, Olopade OI, Wolverton DE, Weber BL, Metz CE, Zhong W, Cummings SA.

Radiology. 2002 Nov;225(2):519-26.

PMID:
12409590
4.

Computerized analysis of mammographic parenchymal patterns on a large clinical dataset of full-field digital mammograms: robustness study with two high-risk datasets.

Li H, Giger ML, Lan L, Bancroft Brown J, MacMahon A, Mussman M, Olopade OI, Sennett C.

J Digit Imaging. 2012 Oct;25(5):591-8.

5.

Computerized analysis of mammographic parenchymal patterns for assessing breast cancer risk: effect of ROI size and location.

Li H, Giger ML, Huo Z, Olopade OI, Lan L, Weber BL, Bonta I.

Med Phys. 2004 Mar;31(3):549-55.

PMID:
15070253
6.

Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection.

Huo Z, Giger ML, Wolverton DE, Zhong W, Cumming S, Olopade OI.

Med Phys. 2000 Jan;27(1):4-12.

PMID:
10659732
7.

Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment.

Li H, Giger ML, Olopade OI, Chinander MR.

J Digit Imaging. 2008 Jun;21(2):145-52. doi: 10.1007/s10278-007-9093-9. Epub 2008 Jan 3.

8.

Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers.

Mitchell G, Antoniou AC, Warren R, Peock S, Brown J, Davies R, Mattison J, Cook M, Warsi I, Evans DG, Eccles D, Douglas F, Paterson J, Hodgson S, Izatt L, Cole T, Burgess L, Eeles R, Easton DF.

Cancer Res. 2006 Feb 1;66(3):1866-72.

9.

Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment.

Li H, Giger ML, Olopade OI, Lan L.

Acad Radiol. 2007 May;14(5):513-21.

PMID:
17434064
10.

Mammographic parenchymal patterns as an imaging marker of endogenous hormonal exposure: a preliminary study in a high-risk population.

Daye D, Keller B, Conant EF, Chen J, Schnall MD, Maidment AD, Kontos D.

Acad Radiol. 2013 May;20(5):635-46. doi: 10.1016/j.acra.2012.12.016.

11.

Mammographic features and breast cancer risk: effects with time, age, and menopause status.

Byrne C, Schairer C, Wolfe J, Parekh N, Salane M, Brinton LA, Hoover R, Haile R.

J Natl Cancer Inst. 1995 Nov 1;87(21):1622-9.

PMID:
7563205
12.

A BRCA1/2 mutation, high breast density and prominent pushing margins of a tumor independently contribute to a frequent false-negative mammography.

Tilanus-Linthorst M, Verhoog L, Obdeijn IM, Bartels K, Menke-Pluymers M, Eggermont A, Klijn J, Meijers-Heijboer H, van der Kwast T, Brekelmans C.

Int J Cancer. 2002 Nov 1;102(1):91-5. Erratum in: Int J Cancer 2002 Dec 20;102(6):665.

PMID:
12353239
13.

Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers.

Mavroforakis ME, Georgiou HV, Dimitropoulos N, Cavouras D, Theodoridis S.

Artif Intell Med. 2006 Jun;37(2):145-62. Epub 2006 May 23.

PMID:
16716579
14.

Texture features from mammographic images and risk of breast cancer.

Manduca A, Carston MJ, Heine JJ, Scott CG, Pankratz VS, Brandt KR, Sellers TA, Vachon CM, Cerhan JR.

Cancer Epidemiol Biomarkers Prev. 2009 Mar;18(3):837-45. doi: 10.1158/1055-9965.EPI-08-0631. Epub 2009 Mar 3.

15.

Assessing the usefulness of a novel MRI-based breast density estimation algorithm in a cohort of women at high genetic risk of breast cancer: the UK MARIBS study.

Thompson DJ, Leach MO, Kwan-Lim G, Gayther SA, Ramus SJ, Warsi I, Lennard F, Khazen M, Bryant E, Reed S, Boggis CR, Evans DG, Eeles RA, Easton DF, Warren RM; UK study of MRI screening for breast cancer in women at high risk (MARIBS).

Breast Cancer Res. 2009;11(6):R80. doi: 10.1186/bcr2447. Epub 2009 Nov 11.

16.

The correlation of mammographic-and histologic patterns of breast cancers in BRCA1 gene mutation carriers, compared to age-matched sporadic controls.

Kaas R, Kroger R, Peterse JL, Hart AA, Muller SH.

Eur Radiol. 2006 Dec;16(12):2842-8. Epub 2006 Aug 19.

PMID:
16924440
17.

Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces.

Chan HP, Sahiner B, Lam KL, Petrick N, Helvie MA, Goodsitt MM, Adler DD.

Med Phys. 1998 Oct;25(10):2007-19.

PMID:
9800710
18.

Genetic testing in an ethnically diverse cohort of high-risk women: a comparative analysis of BRCA1 and BRCA2 mutations in American families of European and African ancestry.

Nanda R, Schumm LP, Cummings S, Fackenthal JD, Sveen L, Ademuyiwa F, Cobleigh M, Esserman L, Lindor NM, Neuhausen SL, Olopade OI.

JAMA. 2005 Oct 19;294(15):1925-33.

PMID:
16234499
19.

Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network.

Chan HP, Sahiner B, Petrick N, Helvie MA, Lam KL, Adler DD, Goodsitt MM.

Phys Med Biol. 1997 Mar;42(3):549-67.

PMID:
9080535
20.

Genetic testing for a BRCA1 mutation: prophylactic surgery and screening behavior in women 2 years post testing.

Botkin JR, Smith KR, Croyle RT, Baty BJ, Wylie JE, Dutson D, Chan A, Hamann HA, Lerman C, McDonald J, Venne V, Ward JH, Lyon E.

Am J Med Genet A. 2003 Apr 30;118A(3):201-9.

PMID:
12673648
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