Improved quantitation for PET/CT image reconstruction with system modeling and anatomical priors

Accurate quantitation of PET tracer uptake levels in small tumors remains a challenge. This work uses an improved reconstruction algorithm to reduce the quantitative errors due to limited system resolution and due to necessary image noise reduction. We propose a method for finding and using the detection system response in the projection matrix of a statistical reconstruction algorithm. In addition we use aligned anatomical information, available in PET/CT scanners, to govern the penalty term applied during each image update. These improvements are combined with FORE rebinning in a clinically feasible algorithm for reconstructing fully 3D PET data. Simulated results show improved tumor bias and variance characteristics with the new algorithm.

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