Partial volume correction of whole body PET images using the wavelet transform

Abstract

ABSTRACT A general approach for partial volume correction of positron emission tomography (PET) images is introduced. The method is based on the merging of functional information from PET images and anatomical information using high resolution anatomical images. In order to decompose the PET and high resolution images the “a trous” algorithm was implemented. Results obtained with simulated and real patie nts images show a significant partial volume reduction and image enhancement. The relative errors in the partial volume corrected image are always less than 3,6% with respect to 16% of the original image. Keywords: Positron emission tomography, wavelet transform, partial volume correction 1. INTRODUCTION Positron emission tomography (PET) images provide important functional information however the poor spatial resolution with respect to other imaging techniques such as Computed Tomography (CT) and Magnetic Resonance (MR) images lead to partial volume effect (PVE). The net result of PVE is an incorrect measur ement of the true radiotracer concentration. As outlined by Aston et al. [1] PVE can be divided into two effects: tissue-fraction and point-spread effect. The tissue fraction effect arises from tissue heterogeneity because the region of interest (ROI) used to determine radiotracer concentration contains signals from different tissues (for exam ple gray and white matter). Th e point-spread effect arises from the finite resolution of PET scanner. The spatial resolu tion of a clinical PET tomograph is about 4-5 mm, while for example the resolution of CT, MR images is about 1-2 mm. Correction for PVE is of great importance for both semi quantitative and quantitative measurements. Typically semi-quantitative measurements involve the estimation of the Standard Uptake Value (SUV) or the tissue to background ratio (TBR). In both cases a ROI is drawn on the lesion and the mean value of the radiotracer concentration is measured. PVE typically reduces the value of the measured tracer concentration. Quantitative and more advanced approaches such as compartmental analysis are applied to measure the exchange of substances between several compartments within the human. PVE can lead to large errors in the estimated kinetic rate constants. In order to correct for PVE a wavelet based approach was proposed by Boussion et al. [2]. It allows not only PVE correction, but also images enhancement by adding high-resolution information obtained by a multi-resolution analysis of PET and high resolution (coregiste red) images. In the following a more general approach is proposed considering different methods for the merging of wavelet coefficients. The paper is organized as follow: in section 2 the necessary mathematical formalism is introduced, in section 3 the main results are presented, conclusions then follow