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Abstract #4921

Image Quality and Quantitative Analysis of abbreviated IVIM Brain MRI With Deep Learning–Based Reconstruction

Qiongge Li1, Yayan Yin1, and Jie Lu1
1Xuanwu Hospital Capital Medical University, Beijing, China

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Diffusion/other diffusion imaging techniquesDeep learning-based reconstruction may improve the image signal to noise ratio without impacting the image contrasts. Intravoxel incoherent motion (IVIM) often require multiple b values with multiple averages that give rise to prolonged scan time. In this work, deep learning reconstruction is used to reduce the overall IVIM scan time. Based on qualitative and quantitative analysis, deep learning reconstruction may significantly improve the results of IVIM and make an abbreviated IVIM feasible.

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Keywords