A Study on a Mask R-CNN-Based Diagnostic System Measuring DDH Angles on Ultrasound Scans

Abstract

Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 × 10e⁻⁴. Training was stopped when the validation loss was at the minimum. No significant difference in angle measurements was found between the model and doctor. The differences in the maxi-mum, minimum, and mean base angles were 6.93, 0, and 1.81°, respectively. The differences in the maximum, minimum, and mean α angle were 19.78, 0.01, and 3.56°, respectively. The differences in the maximum, minimum, and mean β angle were 25.92, 0.01, and 4.51°, respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room.