Evaluation of 3D vs. 2D compression of medical images with set partitioning in hierarchical trees

Armando Manduca; Kenneth R. Persons; Bradley J. Erickson M.D.; Patrice M. Palisson

doi:10.1117/12.312511

26 June 1998 Evaluation of 3D vs. 2D compression of medical images with set partitioning in hierarchical trees

Armando Manduca, Kenneth R. Persons, Bradley J. Erickson M.D., Patrice M. Palisson

Proceedings Volume 3335, Medical Imaging 1998: Image Display; (1998) https://doi.org/10.1117/12.312511
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

Wavelet-based image compression is a very effective technique for medical images, giving significantly better results than the JPEG algorithm. Recent advanced wavelet techniques, such as embedded zerotree wavelet coding or set partitioning in hierarchical trees (SPIHT), have further improved compression efficiency by exploiting the natural relationship between corresponding coefficients at different scales and by progressively refining coefficient values. It is also well known that full 3-D wavelet compression of 3-D data sets is significantly more efficient than 2-D compression of individual slices, but the memory requirements are very high. We explore the extension of the SPIHT algorithm to three dimensions, and also of intermediate approaches such as the encoding of a 3-D image in 'slabs' of 16 slices at a time or simple subtraction of neighboring slices, which yield different tradeoffs between speed and memory requirements on the one hand and compression efficiency on the other for a variety of possible approaches on typical 3-D CT and MRI data sets.

Citation Download Citation

Armando Manduca, Kenneth R. Persons, Bradley J. Erickson M.D., and Patrice M. Palisson "Evaluation of 3D vs. 2D compression of medical images with set partitioning in hierarchical trees", Proc. SPIE 3335, Medical Imaging 1998: Image Display, (26 June 1998); https://doi.org/10.1117/12.312511

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KEYWORDS

Image compression

3D image processing

Wavelets

Computed tomography

Magnetic resonance imaging

Medical imaging

Computer programming

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