Abstract
The ECAT High Resolution Research Tomograph (HRRT) (CTI PET Systems, Knoxville, TN, USA) is the state-of-the-art positron emission tomography (PET) scanner in the nuclear medicine imaging field. The gantry of the HRRT PET scanner has detector-free regions. These regions between the detector blocks introduce missing parts to the acquired PET data. Without the estimation of the missing parts of the sinogram data, the methods which require full sinogram dataset give undesired results. Previously, we proposed the iterative discrete cosine transform (DCT) domain gap-filling method which gave better quantitative and visual results than the previously published gap-filling methods. The gap-filling methods published so far estimate the missing parts only on the transaxial slices while they are ignoring the information from the neighboring transaxial slices. In this study, we propose a non-iterative gap-filling method for the compensation of the HRRT PET sinogram data by using the slices in the direction of radial samples. We compared the results of this new method with the results of the improved version of the DCT domain gap-filling approach. We used 3D numerical phantom sinogram at eight different Poisson noise levels for checking the regional quantitative results. For visual assessment, we employed a [ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sup> C]-raclopride human brain study. After the missing parts were estimated, we applied 2D filtered backprojection which obligates full sinogram dataset. The results showed that the non-iterative interpolation by using the slices in the direction of radial samples gave similar results as the DCT domain data estimation method. Its simplicity and the short processing time over the DCT domain gap-filling method are the notable advantageous properties of this non-iterative gap-filling approach.
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