TY  - JOUR
T1  - Automated ROI-Based Compression on Brain Images Using
Principal Component Analysis
AU - Bin Abdul Manap, Nurulfajar AU - Ting Lim, Sin 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 14
SP  - 5961
EP  - 5970
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.5961.5970
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.5961.5970
KW  - Medical image compression
KW  -ROI
KW  -automated segmentation
KW  -compression
KW  -important
KW  -PCA
AB  - 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.
ER  -