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Abstract #3101

Improving precision of myocardial T1 mapping with 3-parameter fit model using tissue characteristic-based denoising

Jihye Jang1,2, Shiro Nakamori1, and Reza Nezafat1

1Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States, 2Department of Computer Science, Technical University of Munich, Munich, Germany

For the reconstruction of pixel-wise T1 maps, 3-parameter fit model is highly accurate, but is sensitive to noise. Therefore, it is desirable to develop a robust method to reduce sensitivity to noise when 3-parameter fit model is used. In this work, we propose a robust denoising method based on tissue characteristics to improve precision of myocardial T1 mapping. In phantom and in-vivo studies, denoising filtering provided similar T1 measurements with significantly improved precision. This technique will make 3-parameter fit model more favorable by reducing sensitivity to noise and will allow for more accurate and precise myocardial T1 mapping.

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