Developmental Hip Dysplasia segmentation of ultrasound images

Abstract

In our study, Developmental Dysplasia of the Hip (DDH) is intended to automatically segmenting the ultrasound images for diagnosis. Initially, a filter is applied to the raw images. Seven different filters (Mean, Median, Gaussian, Wiener, Perona & Malik, Lee and Frost) are applied to the images and finally the output images are evaluated. Filtered DDH images were segmented and results are evaluated in the second part of the work. In the DDH diagnosis, the ilium and femoral regions are segmented by using Active Contour Models and Circular Hough Transform methods, respectively. When the segmentation process is analyzed, it is observed that the Wiener filters manage to increase the success rate due to their ability to remove speckle noise and ilium segmentation was performed with 94%. It is observed that Wiener filter was also success, besides when applied histogram equalization after filtering success rate is determined as 96% in the femoral region.