{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:05:05Z","timestamp":1754154305043,"version":"3.41.2"},"reference-count":16,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Unc. Fuzz. Knowl. Based Syst."],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:p> This paper aims to compress medical images while maintaining their diagnostic quality. The 2D Discrete Wavelet Transform (2D-DWT) and the Embedded Zerotree Wavelet (EZW) algorithms are combined in the method. This paper addresses the EZW algorithm for further compression. Experimentation was performed to determine the optimal keep factor for the 2D-DWT algorithm, which preserves image quality. This paper further involves applying the EZW algorithm to compress the images further. The compression ratio and bits per pixel (BPP) were measured for the final compressed images. The results show that the combination of 2D-DWT and EZW algorithms effectively compresses medical images while preserving their diagnostic quality. The optimal keep factor for 2D-DWT was found to be 50%, resulting in a compression ratio of 1.632 and a BPP of 0.839. <\/jats:p>","DOI":"10.1142\/s021848852540001x","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T04:17:01Z","timestamp":1753330621000},"page":"527-535","source":"Crossref","is-referenced-by-count":0,"title":["Efficient Medical Image Compression with 2D-DWT-EZW for Resource Optimization"],"prefix":"10.1142","volume":"33","author":[{"given":"S.","family":"Prayla Shyry","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K. 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