Improved lesion detection by level-dependent spatial summation

A novel signal postprocessing method has been developed for application in lesion detection. A signal distribution, directly related to the 2-dimensional envelope distribution comprising a B-mode image, is convolved with a block shaped kernel of which both base area (i.e. window size) and height are modulated by the local signal level. A theoretical analysis shows that the output includes information regarding the local mean brightness in the original image. This information can be displayed as a gray scale image. The predicted behavior agrees with experimental observations. On the basis of twenty simulated lesion images, it is demonstrated that the present algorithm is superior to the conventional L2-mean filter in lesion detection problems, whereby the performance is quantified by the area AROC under the Receiver Operating Characteristic. An improvement in the median value of AROC of the order of 0.1 was observed. Two parameters are used for adjustment. The total number of summations involved in the processing of a frame is comparable to the number required by the arithmetic mean filter, allowing real-time implementation.