Title :
Medical image compression using region-based prediction
Author :
Qiusha Min ; Sadleir, Robert J. T.
Author_Institution :
Sch. of Electron. Eng., Dublin City Univ., Dublin, Ireland
Abstract :
This paper describes a novel technique that uses prior knowledge of anatomical information to improve the performance of medical image compression. This technique uses a series of predictors that have been optimised to deal with specific regions within medical image datasets. Instead of relying on a global prediction model, the proposed technique adaptively switches to an optimal predictor according to the characteristics of the region being compressed. Experimental results show that the proposed adaptive prediction method indeed achieves high prediction accuracy and when combined with an efficient entropy encoder, it provides a higher compression ratio than current general purpose state-of-the-art alternatives.
Keywords :
data compression; entropy; image coding; medical image processing; adaptive prediction method; anatomical information; compression ratio; entropy encoder; global prediction model; medical image compression; medical image datasets; region-based prediction; adaptive prediction; lossless compression; medical image compression; scalable compression;
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-1664-4
DOI :
10.1109/IECBES.2012.6498094