NDLI: MRI guided PET image filtering and partial volume correction

Content Provider	IEEE Xplore Digital Library
Author	Jianhua Yan Lim, J.C.-S. Townsend, D.W.
Copyright Year	2013
Description	Author affiliation: Clinical Imaging Res. Center, A*STAR-NUS, Singapore, Singapore (Jianhua Yan; Lim, J.C.-S.; Townsend, D.W.)
Abstract	Positron emission tomography (PET) image quantification is a challenging problem due to limited spatial resolution of acquired data and the resulting partial volume effects (PVE), which depend on the size of the structure studied in relation to the spatial resolution and which may lead to over or underestimation of the true tissue tracer concentration. Hybrid imaging devices such as PET/MRI can provide both functional PET image and higher definition morphologic image. In this study, first of all, we proposed a MRI guided PET filtering method by adapting a recently proposed local linear model and then incorporated PVE into the model to get a new partial volume correction (PVC) method without parcellation of MRI. The performance of the proposed methods were investigated with simulated dynamic FDG brain dataset and $^{18}F-FDG$ brain data of a cervical cancer patient acquired with simultaneous hybrid PET/MR scanner. The initial simulation results demonstrated that MRI guided PET image filtering can produce less noisy image than traditional Gaussian filtering (GF) and bias and coefficient of variation (COV) can be further reduced by MRI guided PET PVC . In addition, structures can be much better delineated in MRI guided PET PVC with real brain data.
Starting Page	1
Ending Page	5
File Size	413170
Page Count	5
File Format	PDF
e-ISBN	9781479905348
DOI	10.1109/NSSMIC.2013.6829058
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-27
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Positron emission tomography Filtering Magnetic resonance imaging Noise measurement Spatial resolution Noise
Content Type	Text
Resource Type	Article

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