108 related articles for article (PubMed ID: 27951458)
21. Comparison of Dixon Sequences for Estimation of Percent Breast Fibroglandular Tissue.
Ledger AE; Scurr ED; Hughes J; Macdonald A; Wallace T; Thomas K; Wilson R; Leach MO; Schmidt MA
PLoS One; 2016; 11(3):e0152152. PubMed ID: 27011312
[TBL] [Abstract][Full Text] [Related]
22. Accuracy of fully automated, quantitative, volumetric measurement of the amount of fibroglandular breast tissue using MRI: correlation with anthropomorphic breast phantoms.
Wengert GJ; Pinker K; Helbich TH; Vogl WD; Spijker SM; Bickel H; Polanec SH; Baltzer PA
NMR Biomed; 2017 Jun; 30(6):. PubMed ID: 28295818
[TBL] [Abstract][Full Text] [Related]
23. Development of U-Net Breast Density Segmentation Method for Fat-Sat MR Images Using Transfer Learning Based on Non-Fat-Sat Model.
Zhang Y; Chan S; Chen JH; Chang KT; Lin CY; Pan HB; Lin WC; Kwong T; Parajuli R; Mehta RS; Chien SH; Su MY
J Digit Imaging; 2021 Aug; 34(4):877-887. PubMed ID: 34244879
[TBL] [Abstract][Full Text] [Related]
24. Impact of tamoxifen on amount of fibroglandular tissue, background parenchymal enhancement, and cysts on breast magnetic resonance imaging.
King V; Kaplan J; Pike MC; Liberman L; David Dershaw D; Lee CH; Brooks JD; Morris EA
Breast J; 2012; 18(6):527-34. PubMed ID: 23002953
[TBL] [Abstract][Full Text] [Related]
25. Generalizable attention U-Net for segmentation of fibroglandular tissue and background parenchymal enhancement in breast DCE-MRI.
Nowakowska S; Borkowski K; Ruppert CM; Landsmann A; Marcon M; Berger N; Boss A; Ciritsis A; Rossi C
Insights Imaging; 2023 Nov; 14(1):185. PubMed ID: 37932462
[TBL] [Abstract][Full Text] [Related]
26. A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI.
Lin M; Chan S; Chen JH; Chang D; Nie K; Chen ST; Lin CJ; Shih TC; Nalcioglu O; Su MY
Med Phys; 2011 Jan; 38(1):5-14. PubMed ID: 21361169
[TBL] [Abstract][Full Text] [Related]
27. MRI Background Parenchymal Enhancement Is Not Associated with Breast Cancer.
Bennani-Baiti B; Dietzel M; Baltzer PA
PLoS One; 2016; 11(7):e0158573. PubMed ID: 27379395
[TBL] [Abstract][Full Text] [Related]
28. Background Parenchymal Enhancement and Fibroglandular Tissue Proportion on Breast MRI: Correlation with Hormone Receptor Expression and Molecular Subtypes of Breast Cancer.
Öztürk M; Polat AV; Süllü Y; Tomak L; Polat AK
J Breast Health; 2017 Jan; 13(1):27-33. PubMed ID: 28331765
[TBL] [Abstract][Full Text] [Related]
29. Impact of menopausal status on background parenchymal enhancement and fibroglandular tissue on breast MRI.
King V; Gu Y; Kaplan JB; Brooks JD; Pike MC; Morris EA
Eur Radiol; 2012 Dec; 22(12):2641-7. PubMed ID: 22752463
[TBL] [Abstract][Full Text] [Related]
30. SU-E-I-70: Semi-Automatic, User-Driven Breast, Chest Wall and FGT Segmentations Based on Hough Transform, Morphology Tools and Histogram Technology.
Wang Y; Deasy J
Med Phys; 2012 Jun; 39(6Part5):3641. PubMed ID: 28517626
[TBL] [Abstract][Full Text] [Related]
31. The impact of bilateral salpingo-oophorectomy on breast MRI background parenchymal enhancement and fibroglandular tissue.
Price ER; Brooks JD; Watson EJ; Brennan SB; Comen EA; Morris EA
Eur Radiol; 2014 Jan; 24(1):162-8. PubMed ID: 23982290
[TBL] [Abstract][Full Text] [Related]
32. Effect of aromatase inhibitors on background parenchymal enhancement and amount of fibroglandular tissue at breast MR imaging.
King V; Goldfarb SB; Brooks JD; Sung JS; Nulsen BF; Jozefara JE; Pike MC; Dickler MN; Morris EA
Radiology; 2012 Sep; 264(3):670-8. PubMed ID: 22771878
[TBL] [Abstract][Full Text] [Related]
33. Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging.
Lee NA; Rusinek H; Weinreb J; Chandra R; Toth H; Singer C; Newstead G
AJR Am J Roentgenol; 1997 Feb; 168(2):501-6. PubMed ID: 9016235
[TBL] [Abstract][Full Text] [Related]
34. MRI volumetric analysis of breast fibroglandular tissue to assess risk of the spared nipple in BRCA1 and BRCA2 mutation carriers.
Baltzer HL; Alonzo-Proulx O; Mainprize JG; Yaffe MJ; Metcalfe KA; Narod SA; Warner E; Semple JL
Ann Surg Oncol; 2014 May; 21(5):1583-8. PubMed ID: 24526546
[TBL] [Abstract][Full Text] [Related]
35. Diffusion-Weighted MRI of the Breast in Women with a History of Mantle Radiation: Does Radiation Alter Apparent Diffusion Coefficient?
Bajaj P; Iacconi C; Dershaw DD; Morris EA
J Breast Imaging; 2019 Sep; 1(3):212-216. PubMed ID: 31538143
[TBL] [Abstract][Full Text] [Related]
36.
Arponen O; McLean MA; Nanaa M; Manavaki R; Baxter GC; Gill AB; Riemer F; Kennerley AJ; Woitek R; Kaggie JD; Brackenbury WJ; Gilbert FJ
Eur Radiol Exp; 2024 Jun; 8(1):75. PubMed ID: 38853182
[TBL] [Abstract][Full Text] [Related]
37. Repeatability of quantitative MRI measurements in normal breast tissue.
Aliu SO; Jones EF; Azziz A; Kornak J; Wilmes LJ; Newitt DC; Suzuki SA; Klifa C; Gibbs J; Proctor EC; Joe BN; Hylton NM
Transl Oncol; 2014 Feb; 7(1):130-7. PubMed ID: 24772216
[TBL] [Abstract][Full Text] [Related]
38. Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images.
Wei J; Chan HP; Helvie MA; Roubidoux MA; Sahiner B; Hadjiiski LM; Zhou C; Paquerault S; Chenevert T; Goodsitt MM
Med Phys; 2004 Apr; 31(4):933-42. PubMed ID: 15125012
[TBL] [Abstract][Full Text] [Related]
39. Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.
Ding H; Johnson T; Lin M; Le HQ; Ducote JL; Su MY; Molloi S
Med Phys; 2013 Dec; 40(12):122305. PubMed ID: 24320536
[TBL] [Abstract][Full Text] [Related]
40. A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI.
Lew CO; Harouni M; Kirksey ER; Kang EJ; Dong H; Gu H; Grimm LJ; Walsh R; Lowell DA; Mazurowski MA
Sci Rep; 2024 Mar; 14(1):5383. PubMed ID: 38443410
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
