SU‐E‐I‐03: A Kinect‐Based Method of Bone and Soft Tissue Image Separation Using Object Thickness Measurement

Abstract

Purpose:Currently, dual energy subtraction is used for the separation of the soft tissue and bone. There are two methods of calculation: the filter method and the double tube voltage method. However, there are problems with these methods, such as an increase of exposure (double tube voltage method), and image quality degradation due to attenuation of x‐rays (filter method). In the present study, we have developed a new method of separating bone and soft tissue by using a single x‐ray exposure combined with object thickness measurement using the Microsoft Kinect sensor.Methods:We used a hand phantom as an object and measured the thickness of the object from a depth image obtained with the Microsoft Kinect. X‐ray images were taken at different tube voltages (40 kV, 60 kV, 80 kV), and thicknesses of the two components were calculated from x‐ray attenuation equation. A software program for an ImageJ Plugin was developed to obtain separated images, and the separated bone image was compared with the original image by visual evaluation and profile data. The thicknesses of the separated phalanx bones were also compared with those measured from CT images.Results:It was possible to obtain separated bone and soft tissue images using a single x‐ray exposure. The gray values of the bone were greatly enhanced while those of soft tissue were diminished. A comparison with the CT images showed that the bone thickness error was less than 20.0% in phalanx bones.Conclusion:It was shown that the image separation of bone and soft tissue was made possible by using a single x‐ray exposure combined with object thickness measurement. This method will be useful for the accurate evaluation of bone changes after a fracture without using any additional x‐ray exposure.