A New Method of Image Reconstruction for PET Using a Combined Regularization Algorithm
Conférence : Communications avec actes dans un congrès international
Positron emission tomography (PET), is a medical imaging
technique that provides functional information about physiological pro-
cesses. The goal of PET is to reconstruct the distribution of the radioiso-
topes in the body by measuring the emitted photons. The computer
methods are designed to solve the inverse problem known as “image
reconstruction from projections.” In this paper, an iterative image recon-
struction algorithm ART was regularized by combining Tikhonov and
total variation regularizations. In the first step, combined regularization
algorithm of total variation and Tikhonov regularization was applied
to the image obtained by ART algorithm in each iteration for back-
ground noise removal with preserving edges. The quality measurements
and visual inspections show a significant improvement in image quality
compared to other algorithms.