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

fYear

2011

fDate

5-8 June 2011

Firstpage

2293

Lastpage

2299

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2011 IEEE Congress on

Conference_Location

New Orleans, LA

ISSN

Pending

Print_ISBN

978-1-4244-7834-7

Type

conf

DOI

10.1109/CEC.2011.5949900

Filename

5949900