Development of a diaphragm tracking algorithm for megavoltage cone beam CT projection data

In this work several algorithms for diaphragm detection in 2D views of cone-beam computed tomography (CBCT) raw data are developed. These algorithms are tested on 21 Siemens megavoltage CBCT scans of lungs and the result is compared against the diaphragm apex identified by human experts. Among these algorithms dynamic Hough transform is sufficiently quick and accurate for motion determination prior to radiation therapy. The diaphragm was successfully detected in all 21 data sets, even for views with poor image quality and confounding objects. Each CBCT scan analysis (200 frames) took about 38 seconds on a 2.66 GHz Intel quad-core 2 CPU. The average cranio-caudal position error was 1.707 ± 1.117 mm. Other directions were not assessed due to uncertainties in expert identification.