Content-based compression of mammograms with fractal-based segmentation and a modified JPEG2000

Hung Yam Chan, Hamed Sari-Sarraf, Bradley I. Grinstead, Shaun S. Gleason

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

We describe a strategy for the content-based compression of mammograms. In this two-step strategy, the clinically important structures are first identified via a fractal-based segmentation method. Then, a modified version of JPEG2000 is applied in such a way that lossless compression is applied to the extracted structures from the first step, while a lossy compression is applied to the remaining regions. Preliminary results demonstrate that this strategy can achieve high compression ratios (up to 50:1) without compromising the diagnostic quality of the mammograms.

Original languageEnglish
Pages (from-to)2986-2993
Number of pages8
JournalOptical Engineering
Volume43
Issue number12
DOIs
StatePublished - Dec 1 2004

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Keywords

  • Content-based compression
  • Fractal-based segmentation
  • JPEG2000
  • Mammograms
  • Region-of-interest coding

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