Lossless compression algorithm of medical image based on weighted template matching prediction

Zhiwei Zhao; Lin Wan

doi:10.1117/12.3044186

27 August 2024 Lossless compression algorithm of medical image based on weighted template matching prediction

Zhiwei Zhao, Lin Wan

Author Affiliations +

Proceedings Volume 13252, Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024); 132520F (2024) https://doi.org/10.1117/12.3044186
Event: 2024 Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024), 2024, Kaifeng, China

Abstract

In order to enhance the transmission and storage efficiency of medical images, this paper proposes a lossless compression algorithm designed for medical imaging. The algorithm processes input images using an improved weighted template matching predictor, yielding error calculation results and symbol matrices. These outcomes are then entropy-encoded using PNG and Deflate encoding for the predictive results, achieving compression. Experimental verification was conducted using a test dataset comprised of cross-sectional images extracted from multiple scan sequences. The results indicate that the proposed algorithm achieves an average compression ratio of 1:3.00926, outperforming other lossless compression algorithms based on linear prediction, such as PNG and TIFF.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhiwei Zhao and Lin Wan "Lossless compression algorithm of medical image based on weighted template matching prediction", Proc. SPIE 13252, Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024), 132520F (27 August 2024); https://doi.org/10.1117/12.3044186

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