Meeting Banner
Abstract #2473

Comparison of Spatial Interpolation and Inpainting Methods for Estimation of Bad Fittings in Chemical Shift Imaging Data

Angel Torrado-Carvajal1, Daniel S Albrecht1, Ovidiu C Andronesi1, Eva-Maria Ratai1, Vitaly Napadow1, and Marco L Loggia1

1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States

Chemical Shift Imaging (CSI) allows for the quantification of brain metabolite concentrations across multiple voxels/slices. However, issues with model fit (e.g., suboptimal standard deviation, line width/full width at half-maximum, and/or signal-to-noise ratio) can result in the significant loss of usable voxels. Here, we show that an image restoration method called “inpainting” can be successfully used to restore poorly fitted CSI voxels. This method exhibits superior performance (lowest root-mean-square errors) compared to more traditional methods. Inpainting and similar techniques can prove particularly useful as a means of minimizing voxel loss in group voxelwise analyses in standard space.

This abstract and the presentation materials are available to members only; a login is required.

Join Here