Found: 12
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Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple‐Negative Breast Cancer.
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- Journal of Magnetic Resonance Imaging, 2022, v. 56, n. 6, p. 1901, doi. 10.1002/jmri.28219
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- Article
Functional Tumor Volume by Fast Dynamic Contrast‐Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple‐Negative Breast Cancer.
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- Journal of Magnetic Resonance Imaging, 2021, v. 54, n. 1, p. 251, doi. 10.1002/jmri.27557
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- Article
Fast spin-echo triple-echo dixon (fTED) technique for efficient T<sub>2</sub>-weighted water and fat imaging.
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- Magnetic Resonance in Medicine, 2007, v. 58, n. 1, p. 103, doi. 10.1002/mrm.21268
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- Article
Multiparametric MRI–based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-66220-9
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- Article
Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC).
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- Breast Cancer Research & Treatment, 2021, v. 185, n. 1, p. 1, doi. 10.1007/s10549-020-05917-7
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- Article
Fat-suppressed three-dimensional dual echo dixon technique for contrast agent enhanced MRI.
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- Journal of Magnetic Resonance Imaging, 2006, v. 23, n. 1, p. 36, doi. 10.1002/jmri.20470
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- Article
Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
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- Frontiers in Oncology, 2023, p. 1, doi. 10.3389/fonc.2023.1264259
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- Article
Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
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- Frontiers in Oncology, 2023, p. 1, doi. 10.3389/fonc.2023.1264259
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- Article
A flexible fast spin echo triple-echo Dixon technique.
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- Magnetic Resonance in Medicine, 2017, v. 77, n. 3, p. 1049, doi. 10.1002/mrm.26186
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- Article
An improved region growing algorithm for phase correction in MRI.
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- Magnetic Resonance in Medicine, 2016, v. 76, n. 2, p. 519, doi. 10.1002/mrm.25892
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- Article
Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-27518-2
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- Article
Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer.
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- Cancers, 2023, v. 15, n. 19, p. 4829, doi. 10.3390/cancers15194829
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- Article