ROI Based Medical Image Compression

SD. Kasute¹ , M. Kolhekar²

¹ Dept. of Electronics and Telecommunication, Fr. C. Rodrigues Institute of Technology, Vashi, India.

Correspondence should be addressed to: swatikasute@gmail.com.

Section:Research Paper, Product Type: Journal
Vol.5 , Issue.1 , pp.6-11, Apr-2017

Online published on Apr 30, 2017

Copyright © SD. Kasute, M. Kolhekar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Bio-medical image processing is considered as one of the broad field as compared to other fields. It includes image forming, biomedical signal gathering, image processing, picture processing and the features extracted from images used for medical diagnosis. It contains analysis of the image, enhancement of the image and display of images captured via Ultrasound, MRI and X-Ray technologies. A Region Of Interest (ROI) is defined as a portion of an image that we want to extract from the image or perform some other operations on it. The objective of the paper is to compress the ROI in lossless manner using Set Partitioning In Hierarchical Tree (SPIHT) algorithm and Non-ROI i.e; background region in a lossy manner using Discrete Wavelet Transform (DWT). A detailed analysis is carried out by using the parameters like Compression Ratio (CR), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

Key-Words / Index Term :
Region Of Interest (ROI), X-Ray, MRI, SPIHT, DWT, CR, MSE, PSNR

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