Title :
Novel Lossless fMRI Image Compression Based on Motion Compensation and Customized Entropy Coding
Author :
Sanchez, Victor ; Nasiopoulos, Panos ; Abugharbieh, Rafeef
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
fDate :
7/1/2009 12:00:00 AM
Abstract :
We recently proposed a method for lossless compression of 4-D medical images based on the advanced video coding standard (H.264/AVC). In this paper, we present two major contributions that enhance our previous work for compression of functional MRI (fMRI) data: (1) a new multiframe motion compensation process that employs 4-D search, variable-size block matching, and bidirectional prediction; and (2) a new context-based adaptive binary arithmetic coder designed for lossless compression of the residual and motion vector data. We validate our method on real fMRI sequences of various resolutions and compare the performance to two state-of-the-art methods: 4D-JPEG2000 and H.264/AVC. Quantitative results demonstrate that our proposed technique significantly outperforms current state of the art with an average compression ratio improvement of 13%.
Keywords :
biomedical MRI; data compression; entropy codes; image coding; image sequences; medical image processing; motion compensation; 4D medical image; 4D-JPEG2000; bidirectional prediction; context-based adaptive binary arithmetic coder; customized entropy coding; fMRI sequence; lossless fMRI image compression; motion vector data; multiframe motion compensation; residual vector data; variable-size block matching; Bidirectional prediction; context-adaptive binary arithmetic coder (CABAC); functional MRI (fMRI); lossless compression; multiframe motion compensation (MF-MC); Entropy; Head; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2009.2021159
