Automatic segmentation of phalanges regions on CR images based on MSGVF Snakes

Abstract

Rheumatoid arthritis and osteoporosis are two common orthopedic diseases. Rheumatoid arthritis is a disease that inflammation occurs in the joint, which always causes the joints are able to move freely. Osteoporosis is a disease that bone mineral content is reduced and risk of fragility fracture increases. As one of the diagnostic methods, medical imaging by photographed CR equipment has been widely accepted. However, some problems such as mass screening data sets and mis-diagnosis are still remained in visual screening. In order to solve these problems and reduce the burden to physicians, needs of an automatic diagnosis system capable of performing quantitative analysis is anticipated. In this paper, we carry out the development of a segmentation method of phalanges regions from CR images of the hand to perform a quantitative evaluation of rheumatoid arthritis and osteoporosis. The proposed method is carried out crude segmentation of phalanges regions from CR images of the hand, and extracts the detailed phalanges regions by Multi Scale Gradient Vector Flow Snakes (MSGVF) method. In our study, we performed Snakes algorithm to give an initial control points on MSGVF algorithm. We applied our method on three pairs of CR temporal images of phalanges regions, which are called as the previous images and the current images. We got the segmentation results of 5.95 [%] of false-positive rate and 92.9 [%] of true-positive rate.