Automatic Diagnosing of Infant Hip Dislocation Based on Neural Network

In this paper, we propose an automatic diagnosismethod based on neural network to detect the infant hip joint dislocation from its ultrasonic images. The proposed method consists of two procedures including pre-processing of the infant hip joint ultrasonic images and diagnosing via neural network. Pre-processing focuses on extracting regions of interest from the ultrasound images. Then, the extracted result is fed to the trained neural network. Finally, the output of the neural network divides the infant hip into two categories, that is, dislocation or non-dislocation. Experimental results show that our method reaches an accuracy of 97% in total, 100% in specificity and 86% in sensitivitywhich proves that it is capable of clinical detection of infant hip dislocation.