PMID: 9547752Apr 21, 1998Paper

Optimization of PET image quality by means of 3D data acquisition and iterative image reconstruction

Nuklearmedizin. Nuclear Medicine
J DollG Brix

Abstract

In the recent past, several algorithms have been developed in order to transform 3D sinograms acquired at volume PET systems into 2D data sets. These methods offer the possibility to combine the high sensitivity of the 3D measurement with the advantages of iterative 2D image reconstruction. The purpose of our study was the assessment of this approach by using phantom measurements and patient examinations. The experiments were performed at the latest-generation whole-body PET system ECAT EXACT HR+. For 2D data acquisition, a collimator of thin tungsten septa was positioned in the field-of-view. Prior to image reconstruction, the measured 3D data were sorted into 2D sinograms by suing the Fourier rebinning (FORE) algorithm developed by M. Defrise. The standard filtered backprojection (FBP) method and an optimized ML/EM algorithm with overrelaxation for accelerated convergence were employed for image reconstruction. The spatial resolution of both methods as well as the convergence and noise properties of the ML/EM algorithm were studied in phantom measurements. Furthermore, patient data were acquired in the 2D mode as well as in the 3D mode and reconstructed with both techniques. At the same spatial resolution, the ML/EM-reconstru...Continue Reading

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