463 related articles for article (PubMed ID: 9016235)
1. 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]
2. 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]
3. Using a phantom to compare MR techniques for determining the ratio of intraabdominal to subcutaneous adipose tissue.
Donnelly LF; O'Brien KJ; Dardzinski BJ; Poe SA; Bean JA; Holland SK; Daniels SR
AJR Am J Roentgenol; 2003 Apr; 180(4):993-8. PubMed ID: 12646443
[TBL] [Abstract][Full Text] [Related]
4. Knowledge-based and deep learning-based automated chest wall segmentation in magnetic resonance images of extremely dense breasts.
Verburg E; Wolterink JM; de Waard SN; Išgum I; van Gils CH; Veldhuis WB; Gilhuijs KGA
Med Phys; 2019 Oct; 46(10):4405-4416. PubMed ID: 31274194
[TBL] [Abstract][Full Text] [Related]
5. Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation.
Petridou E; Kibiro M; Gladwell C; Malcolm P; Toms A; Juette A; Borga M; Dahlqvist Leinhard O; Romu T; Kasmai B; Denton E
Clin Radiol; 2017 Jul; 72(7):565-572. PubMed ID: 28363661
[TBL] [Abstract][Full Text] [Related]
6. Estimation of the content of fat and parenchyma in breast tissue using MRI T1 histograms and phantoms.
Boston RC; Schnall MD; Englander SA; Landis JR; Moate PJ
Magn Reson Imaging; 2005 May; 23(4):591-9. PubMed ID: 15919606
[TBL] [Abstract][Full Text] [Related]
7. Using deep learning to segment breast and fibroglandular tissue in MRI volumes.
Dalmış MU; Litjens G; Holland K; Setio A; Mann R; Karssemeijer N; Gubern-Mérida A
Med Phys; 2017 Feb; 44(2):533-546. PubMed ID: 28035663
[TBL] [Abstract][Full Text] [Related]
8. Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method.
Wu S; Weinstein SP; Conant EF; Kontos D
Med Phys; 2013 Dec; 40(12):122302. PubMed ID: 24320533
[TBL] [Abstract][Full Text] [Related]
9. Quantitative correlation of breast tissue parameters using magnetic resonance and X-ray mammography.
Graham SJ; Bronskill MJ; Byng JW; Yaffe MJ; Boyd NF
Br J Cancer; 1996 Jan; 73(2):162-8. PubMed ID: 8546901
[TBL] [Abstract][Full Text] [Related]
10. Contrast-enhanced MR mammography for evaluation of the contralateral breast in patients with diagnosed unilateral breast cancer or high-risk lesions.
Pediconi F; Catalano C; Roselli A; Padula S; Altomari F; Moriconi E; Pronio AM; Kirchin MA; Passariello R
Radiology; 2007 Jun; 243(3):670-80. PubMed ID: 17446524
[TBL] [Abstract][Full Text] [Related]
11. A complete software application for automatic registration of x-ray mammography and magnetic resonance images.
Solves-Llorens JA; Rupérez MJ; Monserrat C; Feliu E; García M; Lloret M
Med Phys; 2014 Aug; 41(8):081903. PubMed ID: 25086534
[TBL] [Abstract][Full Text] [Related]
12. Subtraction of in-phase and opposed-phase images in dynamic MR mammography.
Reichenbach JR; Hopfe J; Rauscher A; Wurdinger S; Kaiser WA
J Magn Reson Imaging; 2005 May; 21(5):565-75. PubMed ID: 15834904
[TBL] [Abstract][Full Text] [Related]
13. Comparison of the artifacts caused by metallic implants in breast MRI using dual-echo dixon versus conventional fat-suppression techniques.
Le Y; Kipfer HD; Majidi SS; Holz S; Lin C
AJR Am J Roentgenol; 2014 Sep; 203(3):W307-14. PubMed ID: 25148189
[TBL] [Abstract][Full Text] [Related]
14. Breast lesion co-localisation between X-ray and MR images using finite element modelling.
Lee AW; Rajagopal V; Babarenda Gamage TP; Doyle AJ; Nielsen PM; Nash MP
Med Image Anal; 2013 Dec; 17(8):1256-64. PubMed ID: 23860392
[TBL] [Abstract][Full Text] [Related]
15. A comparison of shimming techniques for optimizing fat suppression in MR mammography.
Takatsu Y; Nishiyama K; Miyati T; Miyano H; Kajihara M; Akasaka T
Radiol Phys Technol; 2013 Jul; 6(2):486-91. PubMed ID: 23728709
[TBL] [Abstract][Full Text] [Related]
16. Lobular carcinoma in situ of the breast: clinical, pathologic, and mammographic features.
Beute BJ; Kalisher L; Hutter RV
AJR Am J Roentgenol; 1991 Aug; 157(2):257-65. PubMed ID: 1853802
[TBL] [Abstract][Full Text] [Related]
17. MR Imaging as an Additional Screening Modality for the Detection of Breast Cancer in Women Aged 50-75 Years with Extremely Dense Breasts: The DENSE Trial Study Design.
Emaus MJ; Bakker MF; Peeters PH; Loo CE; Mann RM; de Jong MD; Bisschops RH; Veltman J; Duvivier KM; Lobbes MB; Pijnappel RM; Karssemeijer N; de Koning HJ; van den Bosch MA; Monninkhof EM; Mali WP; Veldhuis WB; van Gils CH
Radiology; 2015 Nov; 277(2):527-37. PubMed ID: 26110667
[TBL] [Abstract][Full Text] [Related]
18. A new contrast in MR mammography by means of chemical exchange saturation transfer (CEST) imaging at 3 Tesla: preliminary results.
Schmitt B; Zamecnik P; Zaiss M; Rerich E; Schuster L; Bachert P; Schlemmer HP
Rofo; 2011 Nov; 183(11):1030-6. PubMed ID: 22034086
[TBL] [Abstract][Full Text] [Related]
19. Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.
Sogani J; Morris EA; Kaplan JB; D'Alessio D; Goldman D; Moskowitz CS; Jochelson MS
Radiology; 2017 Jan; 282(1):63-73. PubMed ID: 27379544
[TBL] [Abstract][Full Text] [Related]
20. Magnetic resonance imaging of the human female breast. Current status and pathologic correlations.
Powell DE; Stelling CB
Pathol Annu; 1988; 23 Pt 1():159-94. PubMed ID: 2838793
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]