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Abstract #3212

Initial study of elastic modulus estimation method using deep learning in MR elastography

Takanori Aoki1 and Mikio Suga1,2
1Graduate School of Science and Engineering, Chiba University, Chiba, Japan, 2Center for frontier Medical Engineering, Chiba University, Chiba, Japan


MRE is a method for non-invasively and quantitatively estimating the stiffness of biological tissues. Although many estimation methods have been proposed, such as LFE, DI, and MMDI, there is a problem that both quantitativeness and spatial resolution cannot be achieved. In this study, we developed an elastic modulus estimation method by deep learning and compared its robustness to noise, quantitativeness, and spatial resolution with existing methods by numerical simulation. Compared with the conventional method (LFE), the proposed method has the same level of noise robustness, higher spatial resolution, and better quantitative performance in the case of high elastic modulus.

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