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Abstract #0429

Generating Synthetic MR Spectroscopic Imaging using MRI and Single-voxel MR Spectroscopy

Shuki Maruyama1 and Hidenori Takeshima2
1Imaging Modality Group, Advanced Technology Research Department, Research and Development Center, Canon Medical Systems Corporation, Tochigi, Japan, 2Imaging Modality Group, Advanced Technology Research Department, Research and Development Center, Canon Medical Systems Corporation, Kanagawa, Japan

Synopsis

Keywords: Machine Learning/Artificial Intelligence, SpectroscopyThe authors proposed new methods to generate synthetic proton MR spectroscopic imaging (MRSI) data. The proposed methods were derived from Image-to-Image Translation with Conditional Adversarial Networks (pix2pix), taking MRI data or MRI and single-voxel MR spectroscopy (SVS) data as inputs. To integrate the features of MRI and SVS data, additional encoder and decoder networks were incorporated. The experimental results demonstrated that the proposed methods generated metabolite ratio maps with same resolution as MRI data. The synthetic maps generated from MRI+SVS were more consistent with the reference ones than those generated from MRI alone.

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