105 related articles for article (PubMed ID: 29512495)
1. Spatiotemporal features of DCE-MRI for breast cancer diagnosis.
Banaie M; Soltanian-Zadeh H; Saligheh-Rad HR; Gity M
Comput Methods Programs Biomed; 2018 Mar; 155():153-164. PubMed ID: 29512495
[TBL] [Abstract][Full Text] [Related]
2. Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI.
Lee SH; Kim JH; Cho N; Park JS; Yang Z; Jung YS; Moon WK
Med Phys; 2010 Aug; 37(8):3940-56. PubMed ID: 20879557
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.
Milenković J; Dalmış MU; Žgajnar J; Platel B
Med Phys; 2017 Sep; 44(9):4652-4664. PubMed ID: 28622412
[TBL] [Abstract][Full Text] [Related]
5. Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.
Milenković J; Hertl K; Košir A; Zibert J; Tasič JF
Artif Intell Med; 2013 Jun; 58(2):101-14. PubMed ID: 23548472
[TBL] [Abstract][Full Text] [Related]
6. Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.
Bhooshan N; Giger M; Medved M; Li H; Wood A; Yuan Y; Lan L; Marquez A; Karczmar G; Newstead G
J Magn Reson Imaging; 2014 Jan; 39(1):59-67. PubMed ID: 24023011
[TBL] [Abstract][Full Text] [Related]
7. A comprehensive hierarchical classification based on multi-features of breast DCE-MRI for cancer diagnosis.
Liu H; Wang J; Gao J; Liu S; Liu X; Zhao Z; Guo D; Dan G
Med Biol Eng Comput; 2020 Oct; 58(10):2413-2425. PubMed ID: 32749555
[TBL] [Abstract][Full Text] [Related]
8. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI.
Chen W; Giger ML; Bick U; Newstead GM
Med Phys; 2006 Aug; 33(8):2878-87. PubMed ID: 16964864
[TBL] [Abstract][Full Text] [Related]
9. Computer-aided diagnosis for dynamic contrast-enhanced breast MRI of mass-like lesions using a multiparametric model combining a selection of morphological, kinetic, and spatiotemporal features.
Agliozzo S; De Luca M; Bracco C; Vignati A; Giannini V; Martincich L; Carbonaro LA; Bert A; Sardanelli F; Regge D
Med Phys; 2012 Apr; 39(4):1704-15. PubMed ID: 22482596
[TBL] [Abstract][Full Text] [Related]
10. A hybrid hemodynamic knowledge-powered and feature reconstruction-guided scheme for breast cancer segmentation based on DCE-MRI.
Lv T; Wu Y; Wang Y; Liu Y; Li L; Deng C; Pan X
Med Image Anal; 2022 Nov; 82():102572. PubMed ID: 36055051
[TBL] [Abstract][Full Text] [Related]
11. Computer-Aided Diagnosis Scheme for Distinguishing Between Benign and Malignant Masses in Breast DCE-MRI.
Honda E; Nakayama R; Koyama H; Yamashita A
J Digit Imaging; 2016 Jun; 29(3):388-93. PubMed ID: 26691512
[TBL] [Abstract][Full Text] [Related]
12. MTFN: multi-temporal feature fusing network with co-attention for DCE-MRI synthesis.
Li W; Liu J; Wang S; Feng C
BMC Med Imaging; 2024 Feb; 24(1):47. PubMed ID: 38373915
[TBL] [Abstract][Full Text] [Related]
13. A new quantitative image analysis method for improving breast cancer diagnosis using DCE-MRI examinations.
Yang Q; Li L; Zhang J; Shao G; Zheng B
Med Phys; 2015 Jan; 42(1):103-9. PubMed ID: 25563251
[TBL] [Abstract][Full Text] [Related]
14. Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification.
Fusco R; Sansone M; Filice S; Granata V; Catalano O; Amato DM; Di Bonito M; D'Aiuto M; Capasso I; Rinaldo M; Petrillo A
Biomed Res Int; 2015; 2015():237863. PubMed ID: 26339597
[TBL] [Abstract][Full Text] [Related]
15. Computer-aided diagnosis of breast DCE-MRI using pharmacokinetic model and 3-D morphology analysis.
Wang TC; Huang YH; Huang CS; Chen JH; Huang GY; Chang YC; Chang RF
Magn Reson Imaging; 2014 Apr; 32(3):197-205. PubMed ID: 24439361
[TBL] [Abstract][Full Text] [Related]
16. A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.
Lu W; Li Z; Chu J
Comput Biol Med; 2017 Apr; 83():157-165. PubMed ID: 28282591
[TBL] [Abstract][Full Text] [Related]
17. Automated localization of breast cancer in DCE-MRI.
Gubern-Mérida A; Martí R; Melendez J; Hauth JL; Mann RM; Karssemeijer N; Platel B
Med Image Anal; 2015 Feb; 20(1):265-74. PubMed ID: 25532510
[TBL] [Abstract][Full Text] [Related]
18. Automated characterization of breast lesions imaged with an ultrafast DCE-MR protocol.
Platel B; Mus R; Welte T; Karssemeijer N; Mann R
IEEE Trans Med Imaging; 2014 Feb; 33(2):225-32. PubMed ID: 24058020
[TBL] [Abstract][Full Text] [Related]
19. Application value of 3T ¹H-magnetic resonance spectroscopy in diagnosing breast tumors.
Vassiou K; Tsougos I; Kousi E; Vlychou M; Athanasiou E; Theodorou K; Arvanitis DL; Fezoulidis IV
Acta Radiol; 2013 May; 54(4):380-8. PubMed ID: 23436823
[TBL] [Abstract][Full Text] [Related]
20. Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data.
Feilke M; Bischl B; Schmid VJ; Gertheiss J
Methods Inf Med; 2016; 55(1):31-41. PubMed ID: 26577400
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
