A Novel Kernel-Based Regularization Technique for PET Image Reconstruction
AbstractPositron emission tomography (PET) is an imaging technique that generates 3D detail of physiological processes at the cellular level. The technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of “image reconstruction from projection”. This paper proposes a novel kernel-based regularization technique for maximum-likelihood expectation-maximization (
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Boudjelal, A.; Messali, Z.; Elmoataz, A. A Novel Kernel-Based Regularization Technique for PET Image Reconstruction. Technologies 2017, 5, 37.
Boudjelal A, Messali Z, Elmoataz A. A Novel Kernel-Based Regularization Technique for PET Image Reconstruction. Technologies. 2017; 5(2):37.Chicago/Turabian Style
Boudjelal, Abdelwahhab; Messali, Zoubeida; Elmoataz, Abderrahim. 2017. "A Novel Kernel-Based Regularization Technique for PET Image Reconstruction." Technologies 5, no. 2: 37.
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