TY  - JOUR
T1  - Performance Analysis of Hybrid Lossless Compression for MRI Brain Images
AU - Ramkumar, D. AU - Raglend, I. Jacob AU - Batri, K. 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 5
SP  - 260
EP  - 266
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.260.266
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.260.266
KW  - :Medical diagnostic imaging
KW  -lossless image compression
KW  -medical images
KW  -JPEG-LS
KW  -JPEG2000
KW  -lossless hybrid
KW  -near-lossless medical image compression
KW  -data compression
AB  - 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.
ER  -