520 related articles for article (PubMed ID: 28712700)
21. Four-Dimensional Machine Learning Radiomics for the Pretreatment Assessment of Breast Cancer Pathologic Complete Response to Neoadjuvant Chemotherapy in Dynamic Contrast-Enhanced MRI.
Caballo M; Sanderink WBG; Han L; Gao Y; Athanasiou A; Mann RM
J Magn Reson Imaging; 2023 Jan; 57(1):97-110. PubMed ID: 35633290
[TBL] [Abstract][Full Text] [Related]
22. Evaluation of the efficacy of neoadjuvant chemotherapy for breast cancer using diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging.
Xu HD; Zhang YQ
Neoplasma; 2017; 64(3):430-436. PubMed ID: 28253722
[TBL] [Abstract][Full Text] [Related]
23. Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI.
Yuan Y; Giger ML; Li H; Bhooshan N; Sennett CA
Acad Radiol; 2010 Sep; 17(9):1158-67. PubMed ID: 20692620
[TBL] [Abstract][Full Text] [Related]
24. A new algorithm for automatic vascular mapping of DCE-MRI of the breast: Clinical application of a potential new biomarker.
Vignati A; Giannini V; Carbonaro LA; Bertotto I; Martincich L; Sardanelli F; Regge D
Comput Methods Programs Biomed; 2014 Dec; 117(3):482-8. PubMed ID: 25262335
[TBL] [Abstract][Full Text] [Related]
25. Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.
Ginsburg SB; Algohary A; Pahwa S; Gulani V; Ponsky L; Aronen HJ; Boström PJ; Böhm M; Haynes AM; Brenner P; Delprado W; Thompson J; Pulbrock M; Taimen P; Villani R; Stricker P; Rastinehad AR; Jambor I; Madabhushi A
J Magn Reson Imaging; 2017 Jul; 46(1):184-193. PubMed ID: 27990722
[TBL] [Abstract][Full Text] [Related]
26. Radiomic analysis of imaging heterogeneity in tumours and the surrounding parenchyma based on unsupervised decomposition of DCE-MRI for predicting molecular subtypes of breast cancer.
Fan M; Zhang P; Wang Y; Peng W; Wang S; Gao X; Xu M; Li L
Eur Radiol; 2019 Aug; 29(8):4456-4467. PubMed ID: 30617495
[TBL] [Abstract][Full Text] [Related]
27. Computer-based automated estimation of breast vascularity and correlation with breast cancer in DCE-MRI images.
Kostopoulos SA; Vassiou KG; Lavdas EN; Cavouras DA; Kalatzis IK; Asvestas PA; Arvanitis DL; Fezoulidis IV; Glotsos DT
Magn Reson Imaging; 2017 Jan; 35():39-45. PubMed ID: 27569368
[TBL] [Abstract][Full Text] [Related]
28. Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
Li Y; Chen Y; Zhao R; Ji Y; Li J; Zhang Y; Lu H
Eur Radiol; 2022 Mar; 32(3):1676-1687. PubMed ID: 34767068
[TBL] [Abstract][Full Text] [Related]
29. Early Prediction of Breast Cancer Therapy Response using Multiresolution Fractal Analysis of DCE-MRI Parametric Maps.
Machireddy A; Thibault G; Tudorica A; Afzal A; Mishal M; Kemmer K; Naik A; Troxell M; Goranson E; Oh K; Roy N; Jafarian N; Holtorf M; Huang W; Song X
Tomography; 2019 Mar; 5(1):90-98. PubMed ID: 30854446
[TBL] [Abstract][Full Text] [Related]
30. Meta-Analysis of Quantitative Dynamic Contrast-Enhanced MRI for the Assessment of Neoadjuvant Chemotherapy in Breast Cancer.
Jun W; Cong W; Xianxin X; Daqing J
Am Surg; 2019 Jun; 85(6):645-653. PubMed ID: 31267907
[TBL] [Abstract][Full Text] [Related]
31. A computer-aided diagnosis system for breast DCE-MRI at high spatiotemporal resolution.
Dalmış MU; Gubern-Mérida A; Vreemann S; Karssemeijer N; Mann R; Platel B
Med Phys; 2016 Jan; 43(1):84. PubMed ID: 26745902
[TBL] [Abstract][Full Text] [Related]
32. Evaluation of the Tumor Response After Neoadjuvant Chemotherapy in Breast Cancer Patients: Correlation Between Dynamic Contrast-enhanced Magnetic Resonance Imaging and Pathologic Tumor Cellularity.
Choi WJ; Kim WK; Shin HJ; Cha JH; Chae EY; Kim HH
Clin Breast Cancer; 2018 Feb; 18(1):e115-e121. PubMed ID: 28890184
[TBL] [Abstract][Full Text] [Related]
33. Computer-aided diagnosis of breast DCE-MRI images using bilateral asymmetry of contrast enhancement between two breasts.
Yang Q; Li L; Zhang J; Shao G; Zhang C; Zheng B
J Digit Imaging; 2014 Feb; 27(1):152-60. PubMed ID: 24043592
[TBL] [Abstract][Full Text] [Related]
34. A computer-aided diagnosis (CAD) scheme for pretreatment prediction of pathological response to neoadjuvant therapy using dynamic contrast-enhanced MRI texture features.
Giannini V; Mazzetti S; Marmo A; Montemurro F; Regge D; Martincich L
Br J Radiol; 2017 Aug; 90(1077):20170269. PubMed ID: 28707546
[TBL] [Abstract][Full Text] [Related]
35. Molecular Subtypes Recognition of Breast Cancer in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging Phenotypes from Radiomics Data.
Li W; Yu K; Feng C; Zhao D
Comput Math Methods Med; 2019; 2019():6978650. PubMed ID: 31827586
[TBL] [Abstract][Full Text] [Related]
36. A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients.
Liu S; Du S; Gao S; Teng Y; Jin F; Zhang L
BMC Cancer; 2023 Jan; 23(1):15. PubMed ID: 36604679
[TBL] [Abstract][Full Text] [Related]
37. Magnetic resonance imaging evaluation of residual tumors in breast cancer after neoadjuvant chemotherapy: surgical implications.
Zhou J; Li G; Sheng F; Qiao P; Zhang H; Xing X
Acta Radiol; 2016 May; 57(5):529-37. PubMed ID: 26231950
[TBL] [Abstract][Full Text] [Related]
38. A computerized global MR image feature analysis scheme to assist diagnosis of breast cancer: a preliminary assessment.
Yang Q; Li L; Zhang J; Shao G; Zheng B
Eur J Radiol; 2014 Jul; 83(7):1086-1091. PubMed ID: 24743001
[TBL] [Abstract][Full Text] [Related]
39. Multiparametric magnetic resonance imaging for predicting pathological response after the first cycle of neoadjuvant chemotherapy in breast cancer.
Li X; Abramson RG; Arlinghaus LR; Kang H; Chakravarthy AB; Abramson VG; Farley J; Mayer IA; Kelley MC; Meszoely IM; Means-Powell J; Grau AM; Sanders M; Yankeelov TE
Invest Radiol; 2015 Apr; 50(4):195-204. PubMed ID: 25360603
[TBL] [Abstract][Full Text] [Related]
40. Magnetic resonance imaging enhancement features before and after neoadjuvant chemotherapy in patients with breast cancer: a predictive value for responders.
Kang DK; Kim TH; Han TS; Kim KS; Yim H
J Comput Assist Tomogr; 2013; 37(3):432-9. PubMed ID: 23674017
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
