EDGE-DETECTION IN PROSTATIC ULTRASOUND IMAGES USING INTEGRATED EDGE MAPS

Objective: We investigated an algorithm to detect grey level transitio ns with multiple scales of resolution to improve edge detection and lo calisation in ultrasound images of the prostate. Introduction: We had developed a non-analytical operator for prostate contour determination implemented with minimum and maximum filters to identify and locate e dges. We implemented a technique for improved determination of boundar y parts in prostatic ultrasound images by adjusting the edge detection parameter to signal information. Methods: First the influence of pref ilter settings and edge detection parameters is investigated in a test image and a real ultrasound image. Then, local standard deviation is used to identify more or fewer homogeneous regions that are filtered w ith course resolution, while areas with larger deviation indicate that grey level transitions occur, which should be preserved using smaller filter sizes to improve edge localisation. Results: Analysis of image s with different filter sizes indicated that areas are merged for incr easing filter sizes: less pronounced edges disappear or displace for l arger filters. Two scales of resolution lead to an improved localisati on of edges when smaller filter sizes are used in areas with an increa sed local standard deviation. Conclusions: This paper illustrates an e dge detection method suitable as pre-processing step in interpretation of medical images. By adapting input parameters to signal information , object recognition can be applied in images from different imaging m odalities. Also. disadvantages are discussed, resulting in a new appli cation combining a localisation algorithm to find the initial contour and a delineation algorithm to improve the outlining of the resulting contour. (C) 1998 Elsevier Science B.V.