Parametric image estimation using Residual simplified reference tissue model

Kyungsang Kim; Young Don Son; Jong-Hoon Kim; Quanzheng Li

doi:10.1117/12.2534958

28 May 2019 Parametric image estimation using Residual simplified reference tissue model

Kyungsang Kim, Young Don Son, Jong-Hoon Kim, Quanzheng Li

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 1107237 (2019) https://doi.org/10.1117/12.2534958
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

The simplified reference tissue model (SRTM) can provide a robust estimation of binding potential (BP) without a measured arterial blood input function. Although a voxel-wise estimation of BP (so called parametric image) is much more valuable than region of interested (ROI) based estimation of BP, it is challenging to compute it due to limited signal-to-noise ratio (SNR) in dynamic PET data. To achieve reliable parametric imaging, temporal images are commonly low-pass filtered prior to the kinetic parameter estimation, which sacrifices the resolution significantly. In this project, we propose an innovative method, the residual simplified reference tissue model (R-SRTM), to calculate parametric image with high resolution. In phantom simulation, we demonstrate that the proposed method outperforms the conventional SRTM method.

Citation Download Citation

Kyungsang Kim, Young Don Son, Jong-Hoon Kim, and Quanzheng Li "Parametric image estimation using Residual simplified reference tissue model", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 1107237 (28 May 2019); https://doi.org/10.1117/12.2534958

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