Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update

TL;DR

This paper presents a novel lossless compression method for dynamic 3-D medical CT data using motion compensated wavelet lifting with denoised updates, improving compression efficiency while maintaining high-quality downscaled representations.

Contribution

It introduces a denoising technique in the wavelet lifting update step to enhance compression efficiency of motion compensated 3-D wavelet coding for medical imaging.

Findings

Reduced lowpass subband file size by up to 1.64%

Maintained high-quality downscaled sequence representation

Outperformed lossless HEVC coding in experiments

Abstract

For the lossless compression of dynamic 3-D+t volumes as produced by medical devices like Computed Tomography, various coding schemes can be applied. This paper shows that 3-D subband coding outperforms lossless HEVC coding and additionally provides a scalable representation, which is often required in telemedicine applications. However, the resulting lowpass subband, which shall be used as a downscaled representative of the whole original sequence, contains a lot of ghosting artifacts. This can be alleviated by incorporating motion compensation methods into the subband coder. This results in a high quality lowpass subband but also leads to a lower compression ratio. In order to cope with this, we introduce a new approach for improving the compression efficiency of compensated 3-D wavelet lifting by performing denoising in the update step. We are able to reduce the file size of the lowpass subband by up to 1.64\%, while the lowpass subband is still applicable for being used as a downscaled representative of the whole original sequence.