Calculation of contrast and signal-to-noise degradation factors for digital detectors in chest and breast imaging
2003 (English)Report (Other academic)
The Monte Carlo model of an x-ray imaging system, used in the EU 5th framework project by the Linköping and London partner to study chest and breast imaging, was developed jointly by the London and Linköping partners. It incorporates a model of the x-ray imaging system (x-ray tube, filtration, anti-scatter device and image receptor etc.) and the patient by using a voxel phantom of an adult male. Validation and calibration experiments have been performed for both the chest (Ullman et al 2003b) and the breast model.
The model allows inclusion of anatomical or pathological details at particular positions in the anatomy and is able to calculate measures of image quality such as contrast and signal-to-noise ratio and measures of radiation risk for example entrance air kerma and effective dose. It allows alteration of imaging system settings such as tube voltage, filtration, beam size and position, choice of anti-scatter device and choice of image detector etc. The model is a useful tool for optimisations since it has been shown that in chest and lumbar spine radiography is able to predict clinical image quality as assessed by a group of radiologists.
In the Monte Carlo model (MC-model) the image quality measures are calculated assuming a perfectly sharp imaging system and correction factors need to be applied to the computed data in order to make the image quality measures agree on an absolute scale. The calculation of correction factors for contrast and signal-tonoises are described in this report. A similar report focusing on analogue screen-film chest and lumbar spine radiography was completed some years ago and some of the concepts and methods are similar.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2003. , 21 p.
Radiology, Nuclear Medicine and Medical Imaging
IdentifiersURN: urn:nbn:se:liu:diva-57855ISRN: LIU-RAD-R-093OAI: oai:DiVA.org:liu-57855DiVA: diva2:328134