Improving PET-Based Physiological Quantification Through Methods of Wavelet Denoising

The goal of this study was to evaluate methods of multidimensional wavelet denoising on restoring the fidelity of biological signals hidden within dynamic positron emission tomography (PET) images. A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via redundant multiscale representations. In analyzing dynamic PET data of healthy volunteers, a multiscale method improved the estimate-to-error ratio of flows fivefold without loss of detail. This technique also maintained accuracy of flow estimates in comparison with the "gold standard," using dynamic PET with O15-water. In addition, in studies of coronary disease patients, flow patterns were preserved and infarcted regions were well differentiated from normal regions. The results show that a wavelet-based noise-suppression method produced reliable approximations of salient underlying signals and led to an accurate quantification of myocardial perfusion. The described protocol can be generalized to other temporal biomedical imaging modalities including functional magnetic resonance imaging and ultrasound

SUBMITTED TO IEEE TRANSACTIONS ON IMAGE PROCESSING 1 Multiresolution Moment Filters: Theory and Applications

Abstract We introduce local weighted geometric moments that are computed from an image within a sliding window at multiple scales. When the window function satisfies a two-scale relation, we prove that lower order moments can be computed efficiently at dyadic scales by using a multiresolution waveletlike algorithm. We show that B-splines are well suited window functions because, in addition to being refinable, they are positive, symmetric, separable, and very nearly isotropic (Gaussian shape). We present three applications of these multi-scale local moments. The first is a feature extraction method for detecting and characterizing elongated structures in images. The second is a noise reduction method which can be viewed as a multi-scale extension of Savitzky-Golay filtering. The third is a multi-scale optical flow algorithm that uses a local affine model for the motion field, extending the Lucas-Kanade optical flow method. The results obtained in all cases are promising

Motion Correction and Pharmacokinetic Analysis in Dynamic Positron Emission Tomography

This thesis will focus on two important aspects of dynamic Positron Emission Tomography (PET): (i) Motion-compensation , and (ii) Pharmacokinetic analysis (also called parametric imaging) of dynamic PET images. Both are required to enable fully quantitative PET imaging which is increasingly finding applications in the clinic. Motion-compensation in Dynamic Brain PET Imaging: Dynamic PET images are degraded by inter-frame and intra-frame motion artifacts that can a ffect the quantitative and qualitative analysis of acquired PET data. We propose a Generalized Inter-frame and Intra-frame Motion Correction (GIIMC) algorithm that uni fies in one framework the inter-frame motion correction capability of Multiple Acquisition Frames and the intra-frame motion correction feature of (MLEM)-type deconvolution methods. GIIMC employs a fairly simple but new approach of using time-weighted average of attenuation sinograms to reconstruct dynamic frames. Extensive validation studies show that GIIMC algorithm outperforms conventional techniques producing images with superior quality and quantitative accuracy. Parametric Myocardial Perfusion PET Imaging: We propose a novel framework of robust kinetic parameter estimation applied to absolute flow quantification in dynamic PET imaging. Kinetic parameter estimation is formulated as nonlinear least squares with spatial constraints problem where the spatial constraints are computed from a physiologically driven clustering of dynamic images, and used to reduce noise contamination. The proposed framework is shown to improve the quantitative accuracy of Myocardial Perfusion (MP) PET imaging, and in turn, has the long-term potential to enhance capabilities of MP PET in the detection, staging and management of coronary artery disease