Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update
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.
Cite
@article{arxiv.2302.01014,
title = {Compression of Dynamic Medical CT Data Using Motion Compensated Wavelet Lifting with Denoised Update},
author = {Daniela Lanz and Jürgen Seiler and Karina Jaskolka and André Kaup},
journal= {arXiv preprint arXiv:2302.01014},
year = {2023}
}
Comments
Picture Coding Symposium (PCS), San Francisco, CA, USA, 2018, pp. 56-60