Development of a software based automatic exposure control system for use in image guided radiation therapy
| dc.contributor.author | Morton, Daniel R | |
| dc.contributor.supervisor | Jirasek, Andrew | |
| dc.contributor.supervisor | Beckham, Wayne | |
| dc.date.accessioned | 2013-08-12T21:02:15Z | |
| dc.date.available | 2013-08-12T21:02:15Z | |
| dc.date.copyright | 2013 | en_US |
| dc.date.issued | 2013-08-12 | |
| dc.degree.department | Department of Physics and Astronomy | |
| dc.degree.level | Master of Science M.Sc. | en_US |
| dc.description.abstract | Modern image guided radiation therapy involves the use of an isocentrically mounted imaging system to take radiographs of a patient's position before the start of each treatment. Image guidance helps to minimize errors associated with a patients setup, but the radiation dose received by patients from imaging must be managed to ensure no additional risks. The Varian On-Board Imager (OBI) (Varian Medical Systems, Inc., Palo Alto, CA) does not have an automatic exposure control system and therefore requires exposure factors to be manually selected. Without patient specific exposure factors, images may become saturated and require multiple unnecessary exposures. A software based automatic exposure control system has been developed to predict optimal, patient specific exposure factors. The OBI system was modelled in terms of the x-ray tube output and detector response in order to calculate the level of detector saturation for any exposure situation. Digitally reconstructed radiographs are produced via ray-tracing through the patients' volumetric datasets that are acquired for treatment planning. The ray-trace determines the attenuation of the patient and subsequent x-ray spectra incident on the imaging detector. The resulting spectra are used in the detector response model to determine the exposure levels required to minimize detector saturation. Images calculated for various phantoms showed good agreement with the images that were acquired on the OBI. Overall, regions of detector saturation were accurately predicted and the detector response for non-saturated regions in images of an anthropomorphic phantom were calculated to generally be within 5 to 10 % of the measured values. Calculations were performed on patient data and found similar results as the phantom images, with the calculated images being able to determine detector saturation with close agreement to images that were acquired during treatment. Overall, it was shown that the system model and calculation method could potentially be used to predict patients' exposure factors before their treatment begins, thus preventing the need for multiple exposures. | en_US |
| dc.description.proquestcode | 0760 | en_US |
| dc.description.proquestcode | 0574 | en_US |
| dc.description.proquestcode | 0756 | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/4734 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights.temp | Available to the World Wide Web | en_US |
| dc.subject | X-ray imaging | en_US |
| dc.subject | Automatic exposure control | en_US |
| dc.subject | image guided radiation therapy | en_US |
| dc.subject | medical physics | en_US |
| dc.subject | on-board imaging | en_US |
| dc.subject | digitially reconstructed radiographs | en_US |
| dc.title | Development of a software based automatic exposure control system for use in image guided radiation therapy | en_US |
| dc.type | Thesis | en_US |