Advanced Methods for the Computer-Aided Diagnosis of Lesions in Digital Mammograms

摘要

The objective of the proposed research is to develop computer-aided diagnosis methods for use in mammography in order to increase the diagnostic accuracy of radiologists. Specifically we have developed advanced computerized schemes for the detection spiculated lesions and architectural distortions based on the calculation of the Hough spectrum and for the detection of small, low- contrast early cancers based on gradient and circularity filters. Also, computerized classification schemes for masses using artificial neural networks, rule-based methods, and hybrid systems have been developed. We have investigated the effect of database on feature selection and classifier training. We also investigated a computerized method for including temporal change between mammographic examinations. We have also developed an intelleigent search workstation for aiding radiologist in making diagnostic decisions by providing them with both CAD output and images of known cases that are 'similar' to the case in question. The efficacy and efficiency of the CAD methods for mammography are being evaluated on a clinical workstation. The potential significance of this research project lies in the fact that if the detectability of cancers can be increased by employing a computer to aid the radiologist's diagnosis, then the treatment of patients with cancer can be initiated earlier and their chance of survival improved.