| Home > Articles > Published articles > Correlation modeling for compression of computed tomography images |
| Date: | 2013 |
| Abstract: | Abstract-Computed Tomography (CT) is a noninvasive medical test obtained via a series of X-ray exposures resulting in 3D images that aid medical diagnosis. Previous approaches for coding such 3D images propose to employ multi-component transforms to exploit correlation among CT slices, but these approaches do not always improve coding performance with respect to a simpler slice-by-slice coding approach. In this work, we propose a novel analysis which accurately predicts when the use of a multi-component transform is profitable. This analysis models the correlation coefficient r based on image acquisition parameters readily available at acquisition time. Extensive experimental results from multiple image sensors suggest that multi-component transforms are appropriate for images with correlation coefficient r in excess of 0. 87. |
| Grants: | European Commission 250420 Ministerio de Ciencia e Innovación TIN-2009-14426-C02-01 Ministerio de Economía y Competitividad TIN-2012-38102-C03-03 Agència de Gestió d'Ajuts Universitaris i de Recerca 2009/SGR-1224 |
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| Language: | Anglès |
| Document: | Article ; recerca ; Versió sotmesa a revisió |
| Subject: | Computed tomography image compression ; Correlation modeling ; Multi-component transforms ; JPEG2000 coding standard ; DICOM protocol |
| Published in: | IEEE Journal of Biomedical and Health Informatics, Vol. 17, Issue 5 (Set. 2013) , p. 928-935, ISSN 2168-2194 |
Pre-print 9 p, 460.6 KB |