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Proceedings Paper

Compression of digital mammograms with region-of-interest coding evaluated on a CAD system
Author(s): Kjersti Engan; Martin Ruoff Lillo; Thor Ole Gulsrud
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Paper Abstract

Screening programs produce large amount of mammographic data, and good compression schemes would be beneficial for both storage and transmission purposes. In medical data it is crucial that diagnostic important information is preserved. In this work we have implemented two different region-of-interest (ROI) coding methods together with a Set Partitioning in Hierarchical Trees (SPIHT) scheme to be used for compression of mammograms. Region-of-interest coding allows a region of the image to be compressed with higher fidelity than the rest of the image. This is useful in medical data to be able to compress a region containing a possibly cancer area with very high fidelity, but still manage an overall good compression ratio. Both the ROI methods, the basic SPIHT method as well as JPEG compression standard, the latter two without possibility of ROI coding, are evaluated by studying the results from a Computer Aided Detection (CAD) system for microcalcifications tested on the original and the compressed mammograms. In addition a visual inspection is performed as well as Peak Signal-to-Noise-Ratio (PSNR) calculations. Mammograms from the MIAS database is used. We show that mammograms can be compressed to less than 0.5 (0.3) bpp without any visual degradation and without significantly influence on the performance of the CAD system.

Paper Details

Date Published: 29 April 2005
PDF: 10 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.593329
Show Author Affiliations
Kjersti Engan, Univ. of Stavanger (Norway)
Martin Ruoff Lillo, Univ. of Stavanger (Norway)
Thor Ole Gulsrud, Univ. of Stavanger (Norway)

Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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