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Computed Tomography Image Compressibility and Limitations of Compression Ratio-Based Guidelines

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Abstract

Finding optimal compression levels for diagnostic imaging is not an easy task. Significant compressibility variations exist between modalities, but little is known about compressibility variations within modalities. Moreover, compressibility is affected by acquisition parameters. In this study, we evaluate the compressibility of thousands of computed tomography (CT) slices acquired with different slice thicknesses, exposures, reconstruction filters, slice collimations, and pitches. We demonstrate that exposure, slice thickness, and reconstruction filters have a significant impact on image compressibility due to an increased high frequency content and a lower acquisition signal-to-noise ratio. We also show that compression ratio is not a good fidelity measure. Therefore, guidelines based on compression ratio should ideally be replaced with other compression measures better correlated with image fidelity. Value-of-interest (VOI) transformations also affect the perception of quality. We have studied the effect of value-of-interest transformation and found significant masking of artifacts when window is widened.

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Acknowledgments

This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Authors and Affiliations

  1. Department of Electrical Engineering, École de Technologie Supérieure (ETS), 1100 Notre-Dame Ouest, Montréal, Québec, Canada

    Jean-François Pambrun & Rita Noumeir

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  1. Jean-François Pambrun
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  2. Rita Noumeir
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Correspondence to Jean-François Pambrun.

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Pambrun, JF., Noumeir, R. Computed Tomography Image Compressibility and Limitations of Compression Ratio-Based Guidelines. J Digit Imaging 28, 636–645 (2015). https://doi.org/10.1007/s10278-015-9791-7

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  • DOI: https://doi.org/10.1007/s10278-015-9791-7

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