Four-dimensional compression of fMRI using JPEG2000
Author(s) -
Hariharan G. Lalgudi,
Ali Bilgin,
Michael W. Marcellin,
Ali Tabesh,
Mariappan S. Nadar,
Theodore P. Trouard
Publication year - 2005
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.595885
Subject(s) - computer science , jpeg 2000 , lossy compression , data compression , functional magnetic resonance imaging , lossless compression , artificial intelligence , image compression , redundancy (engineering) , wavelet , computer vision , pattern recognition (psychology) , image processing , image (mathematics) , neuroscience , biology , operating system
Many medical imaging techniques available today generate 4D data sets. One such technique is functional magnetic resonance imaging (fMRI) which aims to determine regions of the brain that are activated due to various cognitive and/or motor functions or sensory stimuli. These data sets often require substantial resources for storage and transmission and hence call for efficient compression algorithms. fMRI data can be seen as a time-series of 3D images of the brain. Many different strategies can be employed for compressing such data. One possibility is to treat each 2D slice independently. Alternatively, it is also possible to compress each 3D image independently. Such methods do not fully exploit the redundancy present in 4D data. In this work, methods using 4D wavelet transforms are proposed. They are compared to different 2D and 3D methods. The proposed schemes are based on JPEG2000, which is included in the DICOM standard as a transfer syntax. Methodologies to test the effects of lossy compression on the end result of fMRI analysis are introduced and used to compare different compression algorithms.
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