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Temporal Scalability of Dynamic Volume Data Using Mesh Compensated Wavelet Lifting.

Wolfgang Schnurrer, Niklas Pallast, Thomas Richter

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |October 14, 2017
    PubMed
    Summary

    This study introduces a compensated wavelet lifting method for scalable medical imaging. It improves the quality of down-scaled dynamic CT and MR volumes for teleradiology.

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    Area of Science:

    • Medical Imaging
    • Signal Processing
    • Teleradiology

    Background:

    • Dynamic computed tomography (CT) and magnetic resonance (MR) volumes are large, posing challenges for teleradiologic applications.
    • Lossless scalable representation is needed for efficient previewing and on-demand full-resolution data transmission.
    • Wavelet transform offers scalability, but high quality of the low-pass sub-band is critical for down-scaled representations.

    Purpose of the Study:

    • To develop a high-quality scalable representation for dynamic 2D+t and 3D+t CT and MR volumes.
    • To address the challenge of tissue displacement in dynamic volumes using mesh compensation.
    • To optimize mesh compensation parameters for improved low-pass sub-band quality.

    Main Methods:

    • Utilized compensated wavelet lifting for scalable representation of dynamic medical volumes.

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  • Employed mesh compensation to model tissue expansion and contraction in dynamic scans.
  • Optimized mesh compensation parameter estimation within the lifting structure, incorporating motion compensation inversion.

    • Main Results:

    • Achieved a very high-quality scalable representation for dynamic CT and MR volumes.
    • Improved low-pass sub-band quality by 0.63 dB for CT and 0.43 dB for MR on average.
    • Slightly increased data rate by 2.4% for CT and 1.2% for MR.

    Conclusions:

    • The proposed compensated wavelet lifting approach effectively generates high-quality scalable representations for dynamic medical imaging.
    • Optimized mesh compensation significantly enhances the quality of down-scaled representations crucial for teleradiology.
    • This method offers a practical solution for managing large dynamic CT and MR datasets in remote diagnostic settings.