Content-based compression of mammograms

This thesis presents results from the content-based compression (CBC) of digitized mammograms for transmission, archiving, and, ultimately, telemammography. Unlike traditional compression techniques, CBC is a process in which the content of the data is analyzed before compression takes place. In this approach, the data is partitioned into two classes of regions and a different compression technique is performed on each class. The intended result achieves a balance between data compression and data fidelity. For mammographic images, the data is segmented into two non-overlapping regions: (1) background regions, and (2) focus-of-attention regions that contain the chnically important information. Subsequently, the former regions are compressed using a lossy technique, which attains large reductions in data, while the latter regions are compressed using a lossless technique in order to maintain the fidelity of these regions. In this case, results show that compression ratios averaging 10-20 times greater than that of lossless compression alone can be achieved, while preserving the fidehty of the clinically important information.