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Abstract #1177

Time Domain Principal Component Analysis for Rapid, Real-Time MRI Reconstruction from Undersampled Data

Mark Wright1, Bryson Dietz1, Jihyun Yun1,2, Eugene Yip2, B Gino Fallone1,2, and Keith Wachowicz1,2
1Oncology, University of Alberta, Edmonton, AB, Canada, 2Medical Physics, Cross Cancer Institute, Edmonton, AB, Canada

A real-time acceleration method using Principal Component Analysis (PCA) was developed for use on hybrid MR-radiotherapy machines. Using principal components representative of the temporal changes of k-space in combination with incoherently undersampled data from past dynamic frames, the missing data from the current undersampled frame can be filled in. This allows for real-time fully-reconstructed images. Retrospective analysis on 15 fully-sampled lung cancer patients was used to test the method. Using metrics such as NMSE, pSNR and SSIM, image quality and temporal-robustness was assessed. Dice coefficient, centroid displacement and Hausdorff distance were used to test auto-contouring capabilities for target tracking effectiveness.

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