Time separation technique using prior knowledge for dynamic liver perfusion imaging

Abstract

The perfusion imaging using C-arm CT could be used intraoperatively for liver cancer treatment planning and evaluation. To deal with undersampled data due to slow C-arm CT rotation and pause between the rotations, we applied model-based reconstruction methods. Recent works using the time separation technique with an analytical basis function set have led to a significant improvement in the quality of C-arm CT perfusion maps. In this work we apply the time separation technique with a prior knowledge basis function set extracted using singular value decomposition from CT perfusion reconstructions. On C-arm CT liver perfusion scan simulated based on the real CT liver perfusion scan we show that the bases extracted from only two CT perfusion scans are capable of modeling the C-arm CT data correctly.

Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique

“…The selected subsection of SVD vectors formed the basis function set, and the functions were fitted to the projections and were reconstructed (i.e. reconstructing fitted coefficients) with a slice thickness of 1 The research was carried out in compliance with European Directive 2010/63/EU and German animal welfare legislation (TierSchG). All experiments were approved by the local animal ethic committee (Lower Saxony State Office for Consumer Protection and Food Safety, LAVES 18/2809).…”

“…The basis set consisted of five basis functions. The analysis and discussion of the right number of SVD vectors is carried out in [9]. The general scheme of the described approach is depicted in Fig.…”

“…This results in temporal undersampling and demands for a modelbased reconstruction approach to be utilised. So far, for liver perfusion, the time separation technique (TST) [1] emerges as the preferred choice over the straightforward reconstruction. Instead of treating all projections of one rotation to be acquired at the same time point (i.e.…”