Volume 7, Issue 3, September 2019, Page: 57-65
Medical Image Compression Based on Combining Region Growing and Wavelet Transform
Elnomery Allam Zanaty, Faculty of Computers & Information, Sohag University, Sohag, Egypt
Sherif Mostafa Ibrahim, Mathimatics & Computer Science Department, Faculty of Science, South Valley University, Qena, Egypt
Received: Aug. 20, 2019;       Accepted: Sep. 17, 2019;       Published: Sep. 27, 2019
DOI: 10.11648/j.ijmi.20190703.11      View  545      Downloads  120
Medical data grows very fast and hence medical institutions need to store high volume of data about their patients. Medical images are one of the most important data types about patients. As a result, hospitals have a high volume of images that require a huge storage space and transmission bandwidth to store these images. Most of the time transmission bandwidth is not sufficient to storing and transmit all the image data with the required efficiency. Image compression is the process of encoding information using fewer bits than an un-encoded representation using specific encoding schemes. Compression is useful because it helps to reduce the consumption of expensive resources, such as storage space or transmission bandwidth (computing). In this paper, a medical image compression technique based on combining region growing and wavelets algorithms was introduced. A region growing algorithm is used to simply partitioning the image into two parts foreground and background depending on the intensity values. Then, wavelets methods applied on foreground regions including important regions. These regions are compressed lossless to keep the appearance of the image as intact while making the simplifications and the other region is lossy compressed to reduce the file size, leading to that the overall compression ratio gets better and the reconstructed image seems like the original one. To prove the capability of the proposed algorithm, different four image structures from X-Ray, Computed tomography CT and Magnetic resonance imaging MRI types are tested.
Wavelets Transform, Region Growing, SPIHT, Daubechies, Biorthogonal
To cite this article
Elnomery Allam Zanaty, Sherif Mostafa Ibrahim, Medical Image Compression Based on Combining Region Growing and Wavelet Transform, International Journal of Medical Imaging. Vol. 7, No. 3, 2019, pp. 57-65. doi: 10.11648/j.ijmi.20190703.11
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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