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Sci—Fri AM: Imaging — 07: Symmetric geometric transfer matrix partial volume correction technique for emission tomography: Principle, validation, and robustness
Author(s) -
Sattarivand M,
Kusano M,
Poon I,
Caldwell C
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4740193
Subject(s) - robustness (evolution) , imaging phantom , single photon emission computed tomography , voxel , partial volume , positron emission tomography , point spread function , algorithm , tomography , image resolution , noise (video) , computer science , physics , mathematics , artificial intelligence , optics , nuclear medicine , image (mathematics) , medicine , biochemistry , chemistry , gene
Partial volume correction (PVC) is often needed to correct for limited spatial resolution in quantitative Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) studies. In conventional region‐based PVC methods, spill over between regions segmented from coregistered computed tomography (CT) or magnetic resonance (MR) images is accounted for by calculating regional spread functions (RSFs) in a geometric transfer matrix (GTM) framework. This paper describes a new analytically derived symmetric GTM (sGTM) method that considers spill over between RSFs rather than between regions. The sGTM is mathematically equivalent to Labbe's method, however it is region‐based rather than voxel‐based and it avoids handling large matrices. The sGTM method was validated using an MR‐based 3D digital brain phantom and a physical phantom containing spheres 5 mm to 30 mm in diameter. The sGTM method was compared to the GTM method in terms of accuracy, precision, noise propagation, and robustness, i.e. effects of mis‐registration or point spread function (PSF) estimation errors. The results showed that the sGTM method has accuracy similar to that of the GTM method, and within 5% of the true value. However, the sGTM method showed better precision and noise propagation than the GTM method, especially for spheres smaller than 13 mm. Moreover, the sGTM method was more robust than the GTM method when misregistration or errors in estimates of PSF occurred. In conclusion, the sGTM method was analytically derived and validated and shown to exhibit better noise characteristics and robustness compared to the GTM method.