METHOD AND SYSTEM OF MULTIVARIATE ANALYSIS ON SLICE-WISE DATA OF REFERENCE STRUCTURE NORMALIZED IMAGES FOR IMPROVED QUALITY IN POSITRON EMISSION TOMOGRAPHY STUDIES

摘要

A method and system are provided for improving the quality in positron emission tomography (PET) images. Image quality may be improved by pre-normalizing dynamic PET images and then applying a multivariate analysis tool on the images to generate improved quality dynamic PET images. The dynamic PET images are the images reconstructed from the raw dynamic PET data in the image domain of the PET study. A first normalization method is a data treatment (also referred to as noise pre-normalization) for the negative values that may result from the image reconstruction and/or from random variations in detector readings. A second normalization method is background noise pre-normalization where background pixel values are masked. A third normalization method is kinetic pre-normalization where the contrast is improved to allow greater visualization of the activity in the image. Multivariate analysis such as PCA may then be applied to each slice of the dynamic PET images.