@article{MAKHILLAJIT20141355826,
    title = {Performance Analysis of Hybrid Lossless Compression for MRI Brain Images},
    journal = {Asian Journal of Information Technology},
    volume = {13},
    number = {5},
    pages = {260-266},
    year = {2014},
    issn = {1682-3915},
    doi = {ajit.2014.260.266},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2014.260.266},
    author = {D.,I. Jacob and},
    keywords = {:Medical diagnostic imaging,lossless image compression,medical images,JPEG-LS,JPEG2000,lossless hybrid,near-lossless medical image compression,data compression},
    abstract = {Medical image compression plays a vital role in the medical 
  field where the high quality medical images require extensive storage capacity. 
  Researchers propose an efficient method for storing MRI brain images with a 
  reduced storage capacity at a lesser execution time. Researchers propose a new 
  lossless compression scheme based on Spatial Fuzzy C-Mean algorithm. The MRI 
  brain image after skull stripping is denoised using curvelet transform and segmented 
  into white, gray and Cerebro-Spinal Fluid (CSF) regions using spatial fuzzy. 
  Each segmented region is then compressed using the proposed compression technique. 
  The proposed method achieved a high compression ratio (78%) and also provides 
  an enhanced image quality after decompression.}
    }