Title :
Optimal locally adjustable filtering of PET images by a genetic algorithm
Author :
Hadar, Eitan ; Ben-Tal, Aharon
Author_Institution :
Minerva Optimization Center, Technion-Israel Inst. of Technol., Haifa, Israel
Abstract :
Images produced from positron emission tomography (PET) data sources are important for detecting tumors. To improve the resolution of images produced by PET scanners we develop a procedure (optimal locally adjustable filtering OLAF) where the parameters of filters (eg, Metz, Gauss) are adjusted "optimally" at each point of the reconstructed image in terms of a global objective function, which combines goodness-of-fit, and entropy terms The optimization problem is solved by a specialized genetic algorithm. The approach was tested on several PET data sets (simulated and clinical) (Levkovitz et al., 1998) and has demonstrated that OLAF improves both contrast and uniformity, compared to usual fixed post-processing filtering methods
Keywords :
digital filters; entropy; genetic algorithms; image reconstruction; image resolution; medical image processing; positron emission tomography; tumours; Gauss filter; Metz filter; OLAF; PET Images; contrast; entropy; filter parameters; genetic algorithm; global objective function; goodness-of-fit; image resolution; optimal locally adjustable filtering; optimization; positron emission tomography; reconstructed image; tumors; uniformity; Entropy; Filtering; Filters; Gaussian processes; Genetic algorithms; Image reconstruction; Image resolution; Neoplasms; Positron emission tomography; Testing;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958496
