153 related articles for article (PubMed ID: 38373915)
1. 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]
2. 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]
3. BreastDM: A DCE-MRI dataset for breast tumor image segmentation and classification.
Zhao X; Liao Y; Xie J; He X; Zhang S; Wang G; Fang J; Lu H; Yu J
Comput Biol Med; 2023 Sep; 164():107255. PubMed ID: 37499296
[TBL] [Abstract][Full Text] [Related]
4. Cross-Parametric Generative Adversarial Network-Based Magnetic Resonance Image Feature Synthesis for Breast Lesion Classification.
Fan M; Huang G; Lou J; Gao X; Zeng T; Li L
IEEE J Biomed Health Inform; 2023 Nov; 27(11):5495-5505. PubMed ID: 37656652
[TBL] [Abstract][Full Text] [Related]
5. Hierarchical alignment of breast DCE-MR images by groupwise registration and robust feature matching.
Kim M; Wu G; Shen D
Med Phys; 2012 Jan; 39(1):353-66. PubMed ID: 22225305
[TBL] [Abstract][Full Text] [Related]
6. Multi-Modal Brain Tumor Data Completion Based on Reconstruction Consistency Loss.
Jiang Y; Zhang S; Chi J
J Digit Imaging; 2023 Aug; 36(4):1794-1807. PubMed ID: 36856903
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Total variation based DCE-MRI decomposition by separating lesion from background for time-intensity curve estimation.
Liu H; Zheng Y; Liang D; Tang P; Ren F; Zhang L; Zhao Z
Med Phys; 2017 Jun; 44(6):2321-2331. PubMed ID: 28370063
[TBL] [Abstract][Full Text] [Related]
9. Integration of dynamic contrast-enhanced magnetic resonance imaging and T2-weighted imaging radiomic features by a canonical correlation analysis-based feature fusion method to predict histological grade in ductal breast carcinoma.
Fan M; Liu Z; Xie S; Xu M; Wang S; Gao X; Li L
Phys Med Biol; 2019 Oct; 64(21):215001. PubMed ID: 31470420
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Renal compartment segmentation in DCE-MRI images.
Yang X; Le Minh H; Tim Cheng KT; Sung KH; Liu W
Med Image Anal; 2016 Aug; 32():269-80. PubMed ID: 27236222
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. SwinHR: Hemodynamic-powered hierarchical vision transformer for breast tumor segmentation.
Zhao Z; Du S; Xu Z; Yin Z; Huang X; Huang X; Wong C; Liang Y; Shen J; Wu J; Qu J; Zhang L; Cui Y; Wang Y; Wee L; Dekker A; Han C; Liu Z; Shi Z; Liang C
Comput Biol Med; 2024 Feb; 169():107939. PubMed ID: 38194781
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. A novel framework for evaluating the image accuracy of dynamic MRI and the application on accelerated breast DCE MRI.
Le Y; Nickel MD; Kannengiesser S; Kiefer B; Spottiswoode B; Dale B; Soon V; Lin C
MAGMA; 2018 Apr; 31(2):309-320. PubMed ID: 28894997
[TBL] [Abstract][Full Text] [Related]
17. Self-Supervised Multi-Modal Hybrid Fusion Network for Brain Tumor Segmentation.
Fang F; Yao Y; Zhou T; Xie G; Lu J
IEEE J Biomed Health Inform; 2022 Nov; 26(11):5310-5320. PubMed ID: 34478389
[TBL] [Abstract][Full Text] [Related]
18. Breast Tumor Segmentation in DCE-MRI With Tumor Sensitive Synthesis.
Wang S; Sun K; Wang L; Qu L; Yan F; Wang Q; Shen D
IEEE Trans Neural Netw Learn Syst; 2023 Aug; 34(8):4990-5001. PubMed ID: 34874872
[TBL] [Abstract][Full Text] [Related]
19. Image manifold revealing for breast lesion segmentation in DCE-MRI.
Hu L; Cheng Z; Wang M; Song Z
Biomed Mater Eng; 2015; 26 Suppl 1():S1353-60. PubMed ID: 26405896
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
