Ultrasonic bladder image analysis for intravesical prostatic protrusion measurement using noise-robust gradient information and adaptive contour connection

Abstract

Intravesical prostatic protrusion (IPP) measurement plays an important role in urology. It can be determined by the morphology of the bladder and the prostate gland and is helpful for the diagnosis of benign prostatic hyperplasia (BPH). In this work, an adaptive ultrasonic bladder image analysis algorithm for IPP measurement is proposed. First, to accurately extract the bladder part and the prostate gland part from an ultrasonic image, the smooth filters with adaptive thresholds are adopted. Moreover, we apply the multiscale filters with adaptive thresholding to extract the contours that are possible to be the borders of the bladder and the prostate gland. The confidence, curvature, and turning points of each contour are also determined. Then, since the contour may not be continuous, several techniques, including the curvature different, the weighted distance measurement, the confidence path, and arc extrapolation are adopted to connect the contour segments into two ellipse-like contours. These two contours are treated as the borders of the bladder part and the prostate gland part. With the proposed algorithm, the accuracy of IPP measurement can be much improved and the measuring result is more robust to the noise in the ultrasonic image.