Benchmark test cases for evaluation of computer-based methods for detection of setup errors: Realistic digitally reconstructed electronic portal images with known setup errors

Abstract

Purpose : The purpose of this investigation was to develop methods and software for computing realistic digitally reconstructed electronic portal images with known setup errors for use as benchmark test cases for evaluation and intercomparison of computer-based methods for image matching and detecting setup errors in electronic portal images. Methods and Materials : An existing software tool for computing digitally reconstructed radiographs was modified to compute simulated megavoltage images. An interface was added to allow the user to specify which setup parameter(s) will contain computer-induced random and systematic errors in a reference beam created during virtual simulation. Other software features include options for adding random and structured noise, Gaussian blurring to simulate geometric unsharpness, histogram matching with a “typical” electronic portal image, specifying individual preferences for the appearance of the “gold standard” image, and specifying the number of images generated. The visible male computed tomography data set from the National Library of Medicine was used as the planning image. Results : Digitally reconstructed electronic portal images with known setup errors have been generated and used to evaluate our methods for automatic image matching and error detection. Any number of different sets of test cases can be generated to investigate setup errors involving selected setup parameters and anatomic volumes. This approach has proved to be invaluable for determination of error detection sensitivity under ideal (rigid body) conditions and for guiding further development of image matching and error detection methods. Example images have been successfully exported for similar use at other sites. Conclusions : Because absolute truth is known, digitally reconstructed electronic portal images with known setup errors are well suited for evaluation of computer-aided image matching and error detection methods. High-quality planning images, such as the visible human CT scans from the National Library of Medicine, are essential for producing realistic images. Sets of test cases with systematic and random errors in seelcted setup parameters and anatomic volumes are suitable for use as standard benchmarks by the radiotherapy community. In addition to serving as an aid to research and development, benchmark images may also be useful for evaluation of commercial systems and as part of a quality assurance program for clinical systems. Test cases and software are available upon request.