Title :
Improved reconstruction of quantized CT scans via genetic algorithms
Author :
Miller, Chris ; Moore, Frank ; Babb, Brendan ; Peterson, Michael R.
Author_Institution :
Math. Sci. Dept., Univ. of Alaska Anchorage, Anchorage, AK, USA
Abstract :
Cost-effective storage and timely transmission of medical images are very difficult technical challenges. Compression and reconstruction techniques must guarantee no significant loss of clinical information. This paper presents a convenient technique for improving the quality of reconstructed computed tomography (CT) images previously subjected to specified levels of lossy compression. Our genetic algorithm (GA) evolves novel transforms that consistently outperform state-of the-art wavelet-based schemes supported by the Digital Imaging and Communication in Medicine (DICOM) standard.
Keywords :
computerised tomography; data communication; data compression; genetic algorithms; image coding; image reconstruction; medical image processing; wavelet transforms; clinical information; compression; cost-effective storage; digital imaging and communication in medicine standard; genetic algorithms; medical image transmission; quantized CT scans; reconstructed computed tomography images; wavelet-based schemes; Computed tomography; Image coding; Image reconstruction; Multiresolution analysis; Quantization; Wavelet transforms; genetic algorithms; image reconstruction; medical imaging; quantization; wavelets;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949900
