Intelligent CAD workstation for breast imaging using similarity to known lesions and multiple visual prompt aids

While investigators have been successful in developing methods for the computerized analysis of mammograms and ultrasound images, optimal output strategies for the effective and efficient use of such computer analyses are still undetermined. We have incorporated our computerized mass classification method into an intelligent workstation interface that displays known malignant and benign cases similar to lesions in question using a color-coding scheme that allows instant visual feedback to the radiologist. The probability distributions of the malignant and benign cases in the known database are also graphically displayed along with the graphical "location" of the unknown case relative to these two distributions. The effect of the workstation on radiologists' performance was demonstrated with two preliminary studies. In each study, participants were asked to interpret cases without and with the computer output as an aid for diagnosis. Results from our demonstration studies indicate that radiologists' performance, especially specificity, increases with the use of the aid.

Duke Scholars

Author Li Lan Molecular Genetics and Microbiology