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Abstract #3871

Real-time dynamic image reconstruction using Compressed Sensing and Principal Component Analysis (CS-PCA)

Bryson Dietz1, Eugene Yip1, Jihyun Yun2, Gino Fallone1,2, and Keith Wachowicz1,2

1Oncology, University of Alberta, Edmonton, AB, Canada, 2Medical Physics, Cross Cancer Institute, Edmonton, AB, Canada

An online real-time reconstruction technique that combines compressed sensing with principal component analysis (CS-PCA) was developed for the purpose of adaptive radiotherapy using our Linac-MR system. Our technique uses a database of images, acquired prior to an incoherently accelerated acquisition, to fill in the missing lines of k-space using PCA. Our technique can reconstruct images ranging from 5-20 frames per second with minimal artefacts.

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