708 related articles for article (PubMed ID: 32155611)
21. 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]
22. Background parenchymal enhancement and fibroglandular tissue on breast MRI in women with high genetic risk: Are changes before and after risk-reducing salpingo-oophorectomy associated with breast cancer risk?
Bermot C; Saint-Martin C; Malhaire C; Sebbag-Sfez D; Mouret-Fourme E; Carton M; Thibault FE
Eur J Radiol; 2018 Dec; 109():171-177. PubMed ID: 30527300
[TBL] [Abstract][Full Text] [Related]
23. The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.
Kessler DA; MacKay JW; Crowe VA; Henson FMD; Graves MJ; Gilbert FJ; Kaggie JD
Comput Med Imaging Graph; 2020 Dec; 86():101793. PubMed ID: 33075675
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Histopathologic characteristics of background parenchymal enhancement (BPE) on breast MRI.
Sung JS; Corben AD; Brooks JD; Edelweiss M; Keating DM; Lin C; Morris EA; Patel P; Robson M; Woods M; Bernstein JL; Pike MC
Breast Cancer Res Treat; 2018 Nov; 172(2):487-496. PubMed ID: 30140962
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. Association of Breast Cancer Odds with Background Parenchymal Enhancement Quantified Using a Fully Automated Method at MRI: The IMAGINE Study.
Watt GP; Thakran S; Sung JS; Jochelson MS; Lobbes MBI; Weinstein SP; Bradbury AR; Buys SS; Morris EA; Apte A; Patel P; Woods M; Liang X; Pike MC; Kontos D; Bernstein JL
Radiology; 2023 Sep; 308(3):e230367. PubMed ID: 37750771
[TBL] [Abstract][Full Text] [Related]
28. Quantitative assessment of background parenchymal enhancement in breast MRI predicts response to risk-reducing salpingo-oophorectomy: preliminary evaluation in a cohort of BRCA1/2 mutation carriers.
Wu S; Weinstein SP; DeLeo MJ; Conant EF; Chen J; Domchek SM; Kontos D
Breast Cancer Res; 2015 May; 17():67. PubMed ID: 25986460
[TBL] [Abstract][Full Text] [Related]
29. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
Tong N; Gou S; Yang S; Cao M; Sheng K
Med Phys; 2019 Jun; 46(6):2669-2682. PubMed ID: 31002188
[TBL] [Abstract][Full Text] [Related]
30. Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.
Tie X; Lam SK; Zhang Y; Lee KH; Au KH; Cai J
Med Phys; 2020 Apr; 47(4):1750-1762. PubMed ID: 32012292
[TBL] [Abstract][Full Text] [Related]
31. Breast Region Segmentation being Convolutional Neural Network in Dynamic Contrast Enhanced MRI.
Xu X; Fu L; Chen Y; Larsson R; Zhang D; Suo S; Hua J; Zhao J
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():750-753. PubMed ID: 30440504
[TBL] [Abstract][Full Text] [Related]
32. Mammographic density, MRI background parenchymal enhancement and breast cancer risk.
Pike MC; Pearce CL
Ann Oncol; 2013 Nov; 24 Suppl 8(Suppl 8):viii37-viii41. PubMed ID: 24131968
[TBL] [Abstract][Full Text] [Related]
33. Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.
Wengert GJ; Helbich TH; Woitek R; Kapetas P; Clauser P; Baltzer PA; Vogl WD; Weber M; Meyer-Baese A; Pinker K
Eur Radiol; 2016 Nov; 26(11):3917-3922. PubMed ID: 27108300
[TBL] [Abstract][Full Text] [Related]
34. Quantitative Volumetric K-Means Cluster Segmentation of Fibroglandular Tissue and Skin in Breast MRI.
Niukkanen A; Arponen O; Nykänen A; Masarwah A; Sutela A; Liimatainen T; Vanninen R; Sudah M
J Digit Imaging; 2018 Aug; 31(4):425-434. PubMed ID: 29047034
[TBL] [Abstract][Full Text] [Related]
35. Hybrid U-Net-based deep learning model for volume segmentation of lung nodules in CT images.
Wang Y; Zhou C; Chan HP; Hadjiiski LM; Chughtai A; Kazerooni EA
Med Phys; 2022 Nov; 49(11):7287-7302. PubMed ID: 35717560
[TBL] [Abstract][Full Text] [Related]
36. Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapy.
Olberg S; Zhang H; Kennedy WR; Chun J; Rodriguez V; Zoberi I; Thomas MA; Kim JS; Mutic S; Green OL; Park JC
Med Phys; 2019 Sep; 46(9):4135-4147. PubMed ID: 31309586
[TBL] [Abstract][Full Text] [Related]
37. Deep learning-based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients.
Kawahara D; Tsuneda M; Ozawa S; Okamoto H; Nakamura M; Nishio T; Nagata Y
J Appl Clin Med Phys; 2022 May; 23(5):e13579. PubMed ID: 35263027
[TBL] [Abstract][Full Text] [Related]
38. Impact of fibroglandular tissue and background parenchymal enhancement on diffusion weighted imaging of breast lesions.
Iacconi C; Thakur SB; Dershaw DD; Brooks J; Fry CW; Morris EA
Eur J Radiol; 2014 Dec; 83(12):2137-2143. PubMed ID: 25445896
[TBL] [Abstract][Full Text] [Related]
39. Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.
Qin W; Wu Y; Li S; Chen Y; Yang Y; Liu X; Zheng H; Liang D; Hu Z
Biomed Phys Eng Express; 2020 Feb; 6(2):025009. PubMed ID: 33438635
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]