Citation

Ahmed Salman, Ghalib and Arif, Arif and Mansor, Sarina (2026) Minimum Extraction of Sub-ROI for Near-Lossless Compression on Medical DICOM Image. The International Arab Journal of Information Technology, 23 (3). ISSN 2309-4524

Text Minimum Extraction of Sub-ROI for Near-Lossless Compression on Medical DICOM Image.pdf - Published Version Restricted to Repository staff only Download (744kB)

Abstract

Medical image compression recorded increasing importance over recent decades due to the widely adoption of TeleMedicine application. Besides the non-ignorable size of produced medical images, some Medical Imaging Devices (MID) such as Digital Imaging and Communication in Medicine (DICOM) produce serial of medical images for each single patient. In other words, to tele-diagnose a patient case, the whole series of images must be transmitted, which causes a huge total size of image. Generally, all types of serial-type medical images contain correlated images due to their similarity of image details. In DICOM images, there are three major parts of each image, non-related parts generated by the imaging device, Region of Interest (ROI), and sub ROI. The main idea of this paper consists of two concepts, firstly to focus on the correlation between successive images to find the differences between them increasing the Compression Performance (CP). The second concept focuses on the sub ROI in lossless compression to preserve the medical details and compressing other parts with lossy methods under acceptable level of Peak Signal to Noise Ratio (PSNR). This provides higher CP and without corrupting sensitive details. Due to similarity between successive images, they are subtracted to produce large serial of zeros within corresponding similar parts and other differences within other areas. Depending on long series of zeros produced in subtraction process, this work adopted Run Length Encoding (RLE) to compress image-subtraction result. The compressed form RLE is re-compressed using Arithmetic Coding Technique (ACT) as an effective compression method. The order of combining RLE & ACT is significant due to the nature of compressed data. The proposed compression scheme recorded superior performance (cp=55.7) as benchmarking with other published works in medical image compression field, where it records (1.1) as an enhancement from the nearest performance. This performance is under the best circumstances, where the highest performance in some circumstances was where cp=59.4.

Item Type:	Article
Uncontrolled Keywords:	Medical image compression, Sub-ROI
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 Sep 2026 06:28
Last Modified:	04 Sep 2026 06:28
URII:	http://shdl.mmu.edu.my/id/eprint/16722

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