Improved low-count quantitative PET reconstruction with an iterative neural network

5 Jun 2019Hongki LimIl Yong ChunYuni K. DewarajaJeffrey A. Fessler

Image reconstruction in low-count PET is particularly challenging because gammas from natural radioactivity in Lu-based crystals cause high random fractions that lower the measurement signal-to-noise-ratio (SNR). In model-based image reconstruction (MBIR), using more iterations of an unregularized method may increase the noise, so incorporating regularization into the image reconstruction is desirable to control the noise... (read more)

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