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13th IEEE Symposium on Computer-Based Medical Systems (CBMS'00)
Content-Based Compression of Mammograms for Telecommunication and Archiving
Houston, Texas
June 23-June 24
ISBN: 0-7695-0484-1
Brad Grinstead, Texas Technical University
Hamed Sari-Sarraf, Texas Technical University
Sunanda Mitra, Texas Technical University
Shaun Gleason, Oak Ridge National Laboratory
The concept of content-based image compression (CBIC) has far reaching effects in the areas of archiving and telecommunications. The purpose of this paper is to present some pilot study results from the application of CBIC to mammography. Unlike traditional compression approaches, CBIC first analyzes the content of the data before compression takes place. In this approach, prior to compression, the data is preprocessed and is segmented into two non-overlapping regions: (1) focus-of-attention regions (FARs) that contain the “important” segments of the data, and (2) background regions. Subsequently, the former regions are compressed using a lossless compression technique (maintaining fidelity), while the latter regions are compressed with the aid of a lossy technique (attaining large reductions in data). The intended result is an optimal balance between data reduction and data fidelity. In this case, compression ratios 5-6 times greater than that of lossless compression alone can be reached while preserving the important information.
Index Terms:
mammogram compression, content based compression, fractal encoding
Citation:
Brad Grinstead, Hamed Sari-Sarraf, Sunanda Mitra, Shaun Gleason, "Content-Based Compression of Mammograms for Telecommunication and Archiving," cbms, pp.37, 13th IEEE Symposium on Computer-Based Medical Systems (CBMS'00), 2000
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