JPEG-XL based Compression of DICOM Images for Reduced Storage and Transmission Costs

Abstract

Medical images are largely available in the form of DICOM. These files occupy large disk space and take much time to be transferred for diagnoses purposes. Compression algorithms help in reducing the file size and the data transfer rate. Some common DICOM compression algorithms are: Joint Photographic Experts Group (JPEG), a lossy compression algorithm, JPEG 2000 and Run-length encoding (RLE). With the recent emergence of JPEG XL, the algorithm’s performance outperforms the existing algorithms and is aimed to replace them. JPEG XL can compress in both lossless as well as lossy. This paper provides a comparative analysis of Image Quality Metrics like RMSE, PSNR, SSIM within the lossy and lossless modes of JPEG XL algorithms as well as a comparison between the compression ratios of JPEG XL and RLE algorithms. Hence, this paper suggests an emerging Lossless compression algorithm for a universal replacement for medical file size reduction.