These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
141 related articles for article (PubMed ID: 37253896)
1. Weakly Supervised Breast Lesion Detection in Dynamic Contrast-Enhanced MRI. Sun R; Wei C; Jiang Z; Huang G; Xie Y; Nie S J Digit Imaging; 2023 Aug; 36(4):1553-1564. PubMed ID: 37253896 [TBL] [Abstract][Full Text] [Related]
2. Weakly supervised breast lesion detection in DCE-MRI using self-transfer learning. Sun R; Zhang X; Xie Y; Nie S Med Phys; 2023 Aug; 50(8):4960-4972. PubMed ID: 36820793 [TBL] [Abstract][Full Text] [Related]
3. Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images. Zhou J; Luo LY; Dou Q; Chen H; Chen C; Li GJ; Jiang ZF; Heng PA J Magn Reson Imaging; 2019 Oct; 50(4):1144-1151. PubMed ID: 30924997 [TBL] [Abstract][Full Text] [Related]
4. MRI-Based Breast Cancer Classification and Localization by Multiparametric Feature Extraction and Combination Using Deep Learning. Cong C; Li X; Zhang C; Zhang J; Sun K; Liu L; Ambale-Venkatesh B; Chen X; Wang Y J Magn Reson Imaging; 2024 Jan; 59(1):148-161. PubMed ID: 37013422 [TBL] [Abstract][Full Text] [Related]
5. Automatic deep learning method for detection and classification of breast lesions in dynamic contrast-enhanced magnetic resonance imaging. Gao W; Chen J; Zhang B; Wei X; Zhong J; Li X; He X; Zhao F; Chen X Quant Imaging Med Surg; 2023 Apr; 13(4):2620-2633. PubMed ID: 37064362 [TBL] [Abstract][Full Text] [Related]
6. Weakly-supervised deep learning for ultrasound diagnosis of breast cancer. Kim J; Kim HJ; Kim C; Lee JH; Kim KW; Park YM; Kim HW; Ki SY; Kim YM; Kim WH Sci Rep; 2021 Dec; 11(1):24382. PubMed ID: 34934144 [TBL] [Abstract][Full Text] [Related]
7. Assessing the performance of benign and malignant breast lesion classification with bilateral TIC differentiation and other effective features in DCE-MRI. Li H; Sun H; Liu S; Zhang W; Arukalam FM; Ma H; Qian W J Magn Reson Imaging; 2019 Aug; 50(2):465-473. PubMed ID: 30688398 [TBL] [Abstract][Full Text] [Related]
8. Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers With Partially Annotated Ultrasound Images. Wang J; Qiao L; Zhou S; Zhou J; Wang J; Li J; Ying S; Chang C; Shi J IEEE Trans Med Imaging; 2024 Jul; 43(7):2509-2521. PubMed ID: 38373131 [TBL] [Abstract][Full Text] [Related]
9. Clinical Breast MRI-based Radiomics for Distinguishing Benign and Malignant Lesions: An Analysis of Sequences and Enhanced Phases. Wang G; Guo Q; Shi D; Zhai H; Luo W; Zhang H; Ren Z; Yan G; Ren K J Magn Reson Imaging; 2024 Sep; 60(3):1178-1189. PubMed ID: 38006286 [TBL] [Abstract][Full Text] [Related]
10. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions. Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014 [TBL] [Abstract][Full Text] [Related]
11. A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI. Liu Y; Jia X; Zhao J; Peng Y; Yao X; Hu X; Cui J; Chen H; Chen X; Wu J; Hong N; Wang S; Wang Y J Magn Reson Imaging; 2024 Aug; 60(2):600-612. PubMed ID: 37933890 [TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. Transfer Learning Strategy Based on Unsupervised Learning and Ensemble Learning for Breast Cancer Molecular Subtype Prediction Using Dynamic Contrast-Enhanced MRI. Sun R; Hou X; Li X; Xie Y; Nie S J Magn Reson Imaging; 2022 May; 55(5):1518-1534. PubMed ID: 34668601 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. 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]
18. 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]
19. Weakly Supervised Deep Learning Approach to Breast MRI Assessment. Liu MZ; Swintelski C; Sun S; Siddique M; Desperito E; Jambawalikar S; Ha R Acad Radiol; 2022 Jan; 29 Suppl 1():S166-S172. PubMed ID: 34108114 [TBL] [Abstract][Full Text] [Related]
20. Lesion attention guided neural network for contrast-enhanced mammography-based biomarker status prediction in breast cancer. Qian N; Jiang W; Wu X; Zhang N; Yu H; Guo Y Comput Methods Programs Biomed; 2024 Jun; 250():108194. PubMed ID: 38678959 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]