239 related articles for article (PubMed ID: 20335440)
1. Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis.
Karahaliou A; Vassiou K; Arikidis NS; Skiadopoulos S; Kanavou T; Costaridou L
Br J Radiol; 2010 Apr; 83(988):296-309. PubMed ID: 20335440
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. Classification of breast mass lesions using model-based analysis of the characteristic kinetic curve derived from fuzzy c-means clustering.
Chang YC; Huang YH; Huang CS; Chang PK; Chen JH; Chang RF
Magn Reson Imaging; 2012 Apr; 30(3):312-22. PubMed ID: 22245697
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification.
Agner SC; Soman S; Libfeld E; McDonald M; Thomas K; Englander S; Rosen MA; Chin D; Nosher J; Madabhushi A
J Digit Imaging; 2011 Jun; 24(3):446-63. PubMed ID: 20508965
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Breast DCE-MRI: influence of postcontrast timing on automated lesion kinetics assessments and discrimination of benign and malignant lesions.
Partridge SC; Stone KM; Strigel RM; DeMartini WB; Peacock S; Lehman CD
Acad Radiol; 2014 Sep; 21(9):1195-203. PubMed ID: 24998690
[TBL] [Abstract][Full Text] [Related]
10. Performance evaluation of texture analysis based on kinetic parametric maps from breast DCE-MRI in classifying benign from malignant lesions.
Jiang Z; Yin J
J Surg Oncol; 2020 Jun; 121(8):1181-1190. PubMed ID: 32167588
[TBL] [Abstract][Full Text] [Related]
11. MRI-detected suspicious breast lesions: predictive values of kinetic features measured by computer-aided evaluation.
Wang LC; DeMartini WB; Partridge SC; Peacock S; Lehman CD
AJR Am J Roentgenol; 2009 Sep; 193(3):826-31. PubMed ID: 19696298
[TBL] [Abstract][Full Text] [Related]
12. Quantitative analysis of lesion morphology and texture features for diagnostic prediction in breast MRI.
Nie K; Chen JH; Yu HJ; Chu Y; Nalcioglu O; Su MY
Acad Radiol; 2008 Dec; 15(12):1513-25. PubMed ID: 19000868
[TBL] [Abstract][Full Text] [Related]
13. Computerized breast lesions detection using kinetic and morphologic analysis for dynamic contrast-enhanced MRI.
Chang YC; Huang YH; Huang CS; Chen JH; Chang RF
Magn Reson Imaging; 2014 Jun; 32(5):514-22. PubMed ID: 24582545
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Combined use of T2-weighted MRI and T1-weighted dynamic contrast-enhanced MRI in the automated analysis of breast lesions.
Bhooshan N; Giger M; Lan L; Li H; Marquez A; Shimauchi A; Newstead GM
Magn Reson Med; 2011 Aug; 66(2):555-64. PubMed ID: 21523818
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Multi-parametric MRI lesion heterogeneity biomarkers for breast cancer diagnosis.
Tsarouchi MI; Vlachopoulos GF; Karahaliou AN; Vassiou KG; Costaridou LI
Phys Med; 2020 Dec; 80():101-110. PubMed ID: 33137621
[TBL] [Abstract][Full Text] [Related]
18. Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.
Wu J; Gong G; Cui Y; Li R
J Magn Reson Imaging; 2016 Nov; 44(5):1107-1115. PubMed ID: 27080586
[TBL] [Abstract][Full Text] [Related]
19. Use of dynamic phase subtraction (DPS) map in dynamic contrast-enhanced MRI of the breast.
Ogura A; Hayakawa K; Yoshida S; Maeda F; Saeki F; Syukutani A
J Comput Assist Tomogr; 2011; 35(6):749-52. PubMed ID: 22082548
[TBL] [Abstract][Full Text] [Related]
20. Malignant-lesion segmentation using 4D co-occurrence texture analysis applied to dynamic contrast-enhanced magnetic resonance breast image data.
Woods BJ; Clymer BD; Kurc T; Heverhagen JT; Stevens R; Orsdemir A; Bulan O; Knopp MV
J Magn Reson Imaging; 2007 Mar; 25(3):495-501. PubMed ID: 17279534
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
