Content-based compression of mammograms for telecommunication and archiving

Brad Grinstead, Hamed Sari-Sarraf, Shaun Gleason, Sunanda Mitra

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish
Pages (from-to)37-42
Number of pages6
JournalProceedings of the IEEE Symposium on Computer-Based Medical Systems
StatePublished - 2000

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