DICOM image compression using a hierarchy of predictors

Author

Barlas, Gerassimos ; Kostomanolakis, Stavros ; Orphanoudakis, Stelios C.

Author_Institution

Inst. of Comput. Sci., Found. for Res. & Technol.- Hellas, Crete, Greece

Volume

3

fYear

2001

fDate

2001

Firstpage

2445

Abstract

We present a new method for lossless image compression in the domain of medical imaging. The core of this method is the use of a hierarchy of predictors. In particular, for each examined pixel, a context based on appropriate quantization of neighboring pixel deltas is determined. A different predictor is used for each context allowing for a far more accurate prediction. The contexts form a hierarchy based on increasingly refined quantization of deltas. A number of variations on this basic approach are evaluated and compared with JPEG-LS.

Keywords

data compression; medical image processing; DICOM image compression; JPEG 2000 lossless standards; JPEG-LS; appropriate quantization; examined pixel; grayscale images; increasingly refined deltas quantization; medical diagnostic imaging; neighboring pixel deltas; pixel context; predictors hierarchy; Biomedical imaging; Computer science; Context; DICOM; Image coding; Image storage; Pixel; Quantization; Testing; Transform coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1017272

Filename

1017272