Tailoring Image Compression Algorithms for Optimal PSNR and Compression Ratio in Medical Diagnostic Imaging
DOI:
https://doi.org/10.48047/0z8xcd97Keywords:
Image Compression, PSNR, Compression Ratio, Medical Imaging, JPEG, Deep Learning.Abstract
Medical diagnostic imaging his primary importance in healthcare, in terms of identifying and analyzing various condition. As the volume of medical imaging data is growing, efficient image compression is necessary to minimize time required for transmission, storage and access while maintaining image quality. In this paper we examine how to these image compression algorithms can be tailored to achieve the maximal PSNR vs. compression ratio balance for medical diagnostic images. In this work, we utilize a novel approach that combines both lossless and lossy compression techniques to achieve high quality image with a considerable reduction in data size
Downloads
References
. Bhawesh Joshi, & Dr.Gurveen Vaseer. (2024). Advancements in Medical Imaging: A Comprehensive Analysis of Hybrid Compression Techniques Across Various Clinical Applications. Journal of Applied Optics, 45, 192–209. Retrieved from https://appliedopticsjournal.net/index.php/JAO/article/view/144
. G. Pilikos, L. Horchens, K. J. Batenburg, T. van Leeuwen and F. Lucka, "Deep data compression for apprwoximate ultrasonic image formation," 2020 IEEE International Ultrasonics Symposium (IUS), Las Vegas, NV, USA, 2020, pp. 1-4, doi: 10.1109/IUS46767.2020.9251753.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
