Applied Vision Lab - Content-based compression of mammograms with

Journal article

H. Chan, H. Sari-Sarraf, Brad Grinstead, S. Gleason
2004

Cite

APA Click to copy
Chan, H., Sari-Sarraf, H., Grinstead, B., & Gleason, S. (2004). Content-based compression of mammograms with fractal-based segmentation and a modified JPEG2000.

Chicago/Turabian Click to copy
Chan, H., H. Sari-Sarraf, Brad Grinstead, and S. Gleason. “Content-Based Compression of Mammograms with Fractal-Based Segmentation and a Modified JPEG2000” (2004).

MLA Click to copy
Chan, H., et al. Content-Based Compression of Mammograms with Fractal-Based Segmentation and a Modified JPEG2000. 2004.

BibTeX Click to copy

@article{h2004a,
  title = {Content-based compression of mammograms with fractal-based segmentation and a modified JPEG2000},
  year = {2004},
  author = {Chan, H. and Sari-Sarraf, H. and Grinstead, Brad and Gleason, S.}
}

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.