1 / 1

Analysis of the stability of the Varian OBI® system flat panel detector

Analysis of the stability of the Varian OBI® system flat panel detector. Ariel Jefferson, Dandan Zheng, Jun Lu, Jeffrey Williamson Department of Biomedical Engineering and Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, USA. Data Analysis and Results. Purpose.

trilby
Télécharger la présentation

Analysis of the stability of the Varian OBI® system flat panel detector

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Analysis of the stability of the Varian OBI® system flat panel detector Ariel Jefferson, Dandan Zheng, Jun Lu, Jeffrey Williamson Department of Biomedical Engineering and Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, USA Data Analysis and Results Purpose Methods and Materials To investigate the stability of the flat panel detector (FPD) in a widely used cone beam CT (CBCT) system in terms of gain, offset, and pixel fluctuations over time, and to assess their effects on image quality and establish the minimum required frequency of FPD calibration. • Hardware • Varian Trilogy® OBI • Normalization Phantom • Catphan 600 phantom • Software • Varian Software • Matlab • Excel • ImageJ • Statistical analyses of the number of defective pixels and the pixel to pixel offset values were performed in Excel. Discussion • The FPD electrical components are subject to fluctuations in behavior. Such slight fluctuations did not affect the CBCT image reconstruction in this study. • Future work can be performed to establish an absolute minimum frequency of FPD calibration. • In the gain map analysis, histograms of the results were obtained, and all of them exhibit a Gaussian distribution around 1. Varian Trilogy® Linear Accelerator with On-Board Imager Catphan 600 phantom • Standard Image Acquisition • Signals from the channels are read out in dual gain mode which employs a high gain readout and a low gain readout. • Acquire one flood-field, one normalization, and two dark-field images. • From these images, generate gain maps, offset maps, and defect maps using manufacturer-supplied software • As a control, one CBCT image of a Catphan phantom was acquired. A CBCT image is a 3D volumetric representation of the object. Background Information As the use of LINAC- integrated CBCT imaging systems becomes more prevalent in image guided radiation therapy (IGRT), it demands sufficient attention to quality assurance (QA) of the systems to ensure optimal performance. The system investigated here has an FPD with a 2048x1536 grid of digital channels to detect transmitted x-ray signals. The channels produce variations that necessitate calibration. Conclusion • For the studied CBCT system, a monthly calibration frequency is sufficient to maintain a 98.1% level of stability indicated by the fluctuations in defective pixels. • Compare the gray values (Hounsfield Units) of known materials to analyze CT reconstruction. References Schmidgunst C, Ritter D, Lang E. “Calibration Model of a dual gain flat panel detector for 2D and 3D x-ray imaging.” Journal of Medical Physics, Volume 34, Issue 9, pp. 3649-64, September 2007 Matsinos E. “Current status of the CBCT project at Varian Medical Systems.” Medical Imaging 2005: Physics of Medical Imaging, edited by Michael J. Flynn, Proceedings of SPIE, Volume 5745, pp. 340-51 Example of a reconstructed CBCT slice of the Catphan

More Related