Abstract
Osteoporosis is known as a disease of bone. Visual screening using Computed Radiography (CR) images is an effective method for osteoporosis; however, there are many diseases that exhibit similar state of low bone mass. In this paper, we propose an automatic identification method of osteoporosis from phalanges CR images. As the proposed method, we implement a classifier based on Deep Convolutional Neural Network (DCNN) to identify unknown CR images as normal or abnormal. For training and evaluating of DCNN, we use pseudo color images. The pseudo color images are generated by assigning three types of ROI to R, G, and B channels after extracting the ROI from inside the phalange region of the three kinds of images created from the CR image. In the experiment, we apply our proposal method to 101 cases and True Positive Rate of 75.5 [%] and False Positive Rate of 13.9 [%] were obtained.
