Determination of Intensity Thresholds via Shape Gradients

Shape analysis is a vital aspect of medical imaging. The shapes of objects in an image provide high-level information that is essential for many image processing tasks. Accurate analysis of medical images is often dependent upon an appropriate greyscale thresholding of the image for reliable feature extraction. The determination of object thresholds can be a time-consuming task because the thresholds can vary greatly depending upon the quality and type of image. Thus, an efficient method for determining suitable thresholds is highly desirable. This paper presents a method that uses shape information to accurately determine the intensity ranges of objects present in a greyscale image. The technique introduced is based on the computation of the shape gradient, a numerical value for the difference in shape. In this case, the difference in shape is caused by the change in threshold value applied to the image. The use of this gradient allows us to determine significant shape change events in the evolution of object forms as the threshold varies. The gradient is computed using Union of Circles matching, a method previously shown to be effective in computing shape differences. We show the results of applying this method to artificially computed images and to real medical images. The quality of these results shows that the method is potentially viable in practical applications.