Universität zu Köln

Xu, Hancong, Lenz, Mirjam ORCID: 0000-0002-1630-4012, Caldeira, Liliana, Ma, Bo, Pietrzyk, Uwe, Lerche, Christoph ORCID: 0000-0003-2749-2108, Shah, N. Jon ORCID: 0000-0002-8151-6169 and Scheins, Juergen (2019). Resolution modeling in projection space using a factorized multi-block detector response function for PET image reconstruction. Phys. Med. Biol., 64 (14). BRISTOL: IOP PUBLISHING LTD. ISSN 1361-6560

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Abstract

Positron emission tomography (PET) images usually suffer from limited resolution and statistical uncertainties. However, a technique known as resolution modeling (RM) can be used to improve image quality by accurately modeling the system's detection process within the iterative reconstruction. In this study, we present an accurate RM method in projection space based on a simulated multi-block detector response function (DRF) and evaluate it on the Siemens hybrid MR-BrainPET system. The DRF is obtained using GATE simulations that consider nearly all the possible annihilation photons from the field-of-view (FOV). Intrinsically, the multi-block DRF allows the block crosstalk to be modeled. The RM blurring kernel is further generated by factorizing the blurring matrix of one line-of-response (LOR) into two independent detector responses, which can then be addressed with the DRF. Such a kernel is shift-variant in 4D projection space without any distance or angle compression, and is integrated into the image reconstruction for the BrainPET insert with single instruction multiple data (SIMD) and multi-thread support. Evaluation of simulations and measured data demonstrate that the reconstruction with RM yields significantly improved resolutions and reduced mean squared error (MSE) values at different locations of the FOV, compared with reconstruction without RM. Furthermore, the shift-variant RM kernel models the varying blurring intensity for different LORs due to the depth-of-interaction (DOI) dependencies, thus avoiding severe edge artifacts in the images. Additionally, compared to RM in single-block mode, the multi-block mode shows significantly improved resolution and edge recovery at locations beyond 10 cm from the center of BrainPET insert in the transverse plane. However, the differences have been observed to be low for patient data between single-block and multi-block mode RM, due to the brain size and location as well as the geometry of the BrainPET insert. In conclusion, the RM method proposed in this study can yield better reconstructed images in terms of resolution and MSE value, compared to conventional reconstruction without RM.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Xu, Hancong UNSPECIFIED UNSPECIFIED UNSPECIFIED Lenz, Mirjam UNSPECIFIED orcid.org/0000-0002-1630-4012 UNSPECIFIED Caldeira, Liliana UNSPECIFIED UNSPECIFIED UNSPECIFIED Ma, Bo UNSPECIFIED UNSPECIFIED UNSPECIFIED Pietrzyk, Uwe UNSPECIFIED UNSPECIFIED UNSPECIFIED Lerche, Christoph UNSPECIFIED orcid.org/0000-0003-2749-2108 UNSPECIFIED Shah, N. Jon UNSPECIFIED orcid.org/0000-0002-8151-6169 UNSPECIFIED Scheins, Juergen UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-136292
DOI:	10.1088/1361-6560/ab266b
Journal or Publication Title:	Phys. Med. Biol.
Volume:	64
Number:	14
Date:	2019
Publisher:	IOP PUBLISHING LTD
Place of Publication:	BRISTOL
ISSN:	1361-6560
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SYSTEM MODEL; MATRIX; SIMULATION; ACCURATE; VOLUME; QUANTITATION; REDUCTION; SCATTER; VARIANT; NOISE Multiple languages Engineering, Biomedical; Radiology, Nuclear Medicine & Medical Imaging Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/13629