Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update
Daniela Lanz, J\"urgen Seiler, Karina Jaskolka, Andr\'e Kaup

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…
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Taxonomy
TopicsAdvanced Data Compression Techniques · Medical Imaging Techniques and Applications · Image and Signal Denoising Methods
