Correlation of lesions from multiple images for CAD
The object of this research is to investigate a method for determining whether two different imaged presentations of a lesion actually represent the same abnormality. Tasks of this kind are expected to arise in numerous applications, including when interpreting multi-view mammograms or multi-modal images for breast cancer diagnosis and when comparing breast images in longitudinal studies for evaluation of disease prognosis or treatment outcome. Currently, we consider the above-stated discrimination task in two-view breast sonography. We are studying image-based feature(s) and are developing general correlation formulation that uses the identified feature(s). By using a database of 262 actual breast lesions we have obtained promising initial results that yield an Az value of 0.82 in the task of distinguishing between corresponding lesion pairs and non-corresponding lesion pairs.