Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis

Abstract

A fully automated method for computerized detection of pulmonary embolism in spiral computed tomography angiography was developed based on volumetric image analysis. The detection method is based on segmentation of pulmonary vessels to limit the search space, and analysis of several three-dimensional features inside segmented vessel volume. The features utilized are vascular size, local contrast based on mathematical morphology, degree of curvilinearity based on second derivatives, and geometric features such as volume and length. Detection results were obtained for 19 clinical data sets and the performance of the method was evaluated. Using the number and locations of thrombi diagnosed by radiologists as the gold standard, 100% sensitivity was achieved with 7.7 false positives per case, and 85% sensitivity was obtained with 2.6 false positives. For identification of all the positive cases as positive, i.e., detection of at least one thrombus per positive case, 1.9 false positives per case were obtained. These preliminary results suggest that the method has potential for fully automated detection of pulmonary embolism.