Novel approach to computer-aided diagnosis of mammographic images

摘要

This is a work-in-progress report of a research endeavor that deals with the design and development of a novel approach to computer-aided diagnosis (CAD) of mammographic images. With the initial emphasis being on the analysis of microcalcifications, the proposed approach defines a synergistic paradigm that utilizes new methodologies together with previously developed techniques. The new paradigm is intended to promote a higher degree of accuracy in CAD of mammograms with an increased overall throughput. The process of accomplishing these goals is initiated by the fractal encoding of the input image, which gives rise to the generation of focus-of-attention regions (FARs), that is, regions that contain anomalies. The primary thrust of this work is to demonstrate that by considering FARs, rather than the entire input image, the performances of the ensuing processes (i.e., segmentation, feature extraction, and classification) are enhanced in terms of accuracy and speed. After presenting the proposed approach to CAD of mammographic images, the paper describes the generation of FARs. Furthermore, an experimental study is included that demonstrates the impact of this front-end procedure on the process of microcalcification segmentation. Specifically, the experimentation reveals a dramatic decrease (increase) in the amount of input data (throughput), as well as a reduction in the number of false detections.