@article{MAKHILLAJIT201615236558,
    title = {Investigations and Analysis of a Fast and Efficient Coding Technique for
Medical Images Using Contourlet Transform},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {23},
    pages = {4875-4883},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.4875.4883},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.4875.4883},
    author = {M. and},
    keywords = {Contourlet,directional filter Banks,DWT,EZW,PSNR,region of interest,performance measure},
    abstract = {The proposed algorithm presents a new coding technique based on image compression using
contourlet transform used in different modalities of medical imaging. Recent reports on natural image
compression have shown superior performance of contourlet transform, a new extension to the wavelet
transform in two dimensions using nonseparable and directional filter banks. As far as medical images are
concerned the diagnosis part (ROI) is of much important compared to other regions. Therefore, those portions
are segmented from the whole image using Fuzzy C-Means (FCM) clustering technique. Contourlet transform
is then applied to ROI portion which performs Laplacian Pyramid (LP) and directional filter banks. The region
of less significance are compressed using discrete wavelet Transform and finally modified embedded zerotree
wavelet algorithm is applied which uses six symbols instead of four symbols used in Shapiro’s EZW to the
resultant image which shows better PSNR and high compression ratio. Finally Huffman coding is applied to
get the compressed image.}
    }