Nurulfajar  Bin Abdul Manap, Sin  Ting Lim, 
    Automated ROI-Based Compression on Brain Images Using
Principal Component Analysis,
    Journal of Engineering and Applied Sciences,
    Volume 13,Issue 14,
    2018,
    Pages 5961-5970,
    ISSN 1816-949x,
    jeasci.2018.5961.5970,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2018.5961.5970)
    Abstract: Medical image contains diagnostically important regions that shall not be subjected to lossy
compression. In order to increase compression rate for higher transmission and storage capability, a partial
compression scheme based on ROI and non-ROI was employed. A manual segmentation technique to separate
ROI and non-ROI for thousands of images are impractical, hence in this study an automated brain segmentation
technique was developed to work with a PCA compression scheme. Non-ROI region will be compressed by
PCA compression while ROI region will be preserved. The segmentation technique specifically tailored for
brain segmentation has successfully separate ROI and non-ROI regions and results indicate that image quality
is higher for image undergo the proposed model compared with image without ROI segmentation.
    Keywords: Medical image compression;ROI;automated segmentation;compression;important;PCA