Model-based reconstruction methods for CT perfusion imaging
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M1.1a | Model-based reconstruction methods for CT perfusion imaging
Funding period: Jan 2017 to Sep 2018
Researcher: Sebastian BannaschAngiography itself implies a dynamic 2D monitoring of a contrast agent's distribution right on injection into, for instance, organic tissue and vessels. The reconstruction of an accurate high-dimensional 4D computed tomography (CT) based on such temporally under-sampled 3D data (i.e. dynamically acquired / sampled 2D projections) while striving for minimal computational costs consequently constitutes the 'bottleneck' in application.
The general objective of this project was, therefore, to provide a fast and accurate algorithm for CT perfusion imaging by making use of prior knowledge.