Analysis of Intravesical Prostatic Protrusion Ultrasound Image

Traditional ultrasound images are interpreted manually. However, we proposed a formulaic approach for processing ultrasound images and interpreting ultrasound images through computer vision image analysis. We determined the depression index to assess the condition of the prostate protruding into the bladder. The identification methods included noise elimination, edge detection, dynamic threshold, morphology, and shortest distance evaluation. Additionally, we employed the principal component analysis (PCA) and vertical distance. By eliminating noise and determining relative positions, regularization, threshold comparison, segmentation and merging, and elliptical approximation of bladder contours were inferred to diagnose the intravesical prostatic protrusion (IPP) using bladder ultrasound images. By utilizing elliptical approximation, we reconstructed the original appearance of the bladder from the ultrasound images.