Abstract
Computed tomography (CT) is a noninvasive medical test obtained via a series of X-ray exposures resulting in 3-D images that aid medical diagnosis. Previous approaches for coding such 3-D images propose to employ multicomponent 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 paper, we propose a novel analysis which accurately predicts when the use of a multicomponent 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 multicomponent transforms are appropriate for images with correlation coefficient r in excess of 0.87. © 2013 IEEE.
Original language | English |
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Article number | 6517882 |
Pages (from-to) | 928-935 |
Journal | IEEE Journal of Biomedical and Health Informatics |
Volume | 17 |
Issue number | 5 |
DOIs | |
Publication status | Published - 18 Sept 2013 |
Keywords
- Computed tomography (CT) image compression
- JPEG2000 coding standard
- correlation modeling
- digital imaging and communications in medicine (DICOM) protocol
- multicomponent transforms