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Proceedings Paper

Task-oriented lossy compression of magnetic resonance images
Author(s): Mark C. Anderson; M. Stella Atkins; Jacques Vaisey
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Paper Abstract

A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

Paper Details

Date Published: 15 April 1996
PDF: 12 pages
Proc. SPIE 2707, Medical Imaging 1996: Image Display, (15 April 1996); doi: 10.1117/12.238451
Show Author Affiliations
Mark C. Anderson, ISG Technologies, Inc. (Canada)
M. Stella Atkins, Simon Fraser Univ. (Canada)
Jacques Vaisey, Simon Fraser Univ. (Canada)


Published in SPIE Proceedings Vol. 2707:
Medical Imaging 1996: Image Display
Yongmin Kim, Editor(s)

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