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• W2040689334 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." @default.
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• W2040689334 date "2013-09-01" @default.
• W2040689334 modified "2023-10-18" @default.
• W2040689334 title "Correlation Modeling for Compression of Computed Tomography Images" @default.
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• W2040689334 doi "https://doi.org/10.1109/jbhi.2013.2264595" @default.
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