Significance of ROI Coding using MAXSHIFT Scaling applied on MRI Images in Teleradiology-Telemedicine

Pervez Akhtar, Muhammad Bhatti, Tariq Ali, Muhammad Muqeet

BME Department, SSUET.
EPE Department, NUST.
ISD Department, IT Division, AKU.

DOI: 10.4236/jbise.2008.12018                

Abstract

Within the expanding paradigm of medical imaging in Teleradiology-Telemedicine there is increasing demand for transmitting diagnostic medical imagery. These are usually rich in radiological contents and the associated file sizes are large which must be compressed with minimal file size to minimize transmission time and robustly coded to withstand required network medium. It has been reinforced through extensive research that the diagnostically important regions of medical images, the Region of Interest (ROI), must be compressed by lossless or near lossless algorithm while on the other hand, the background region be compressed with some loss of information but still recognizable using JPEG 2000 standard. We develop a compression model and present its application on MRI images. Applying on MRI images achieved higher compression ratio 16:1, analogously minimum transmission time, using MAXSHIFT method proved diagnostically significant and effective both objectively and subjectively.

Keywords

Image compression, MRI, ROI, MAXSHIFT

Conflicts of Interest

The authors declare no conflicts of interest.

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