An objective procedure for optimisation of exposure parameters with digital equipment in conventional radiology is proposed. A method for image quality assessment based on contrast-to-noise ratio (CNR) evaluation has been worked out and compared to the methodology of contrastdetail analysis. The correspondence between these two methods is shown. Experimental setups for chest and abdomen examinations on CR and DR equipment have been considered. Image quality has been related to effective dose in order to find optimal high voltage settings. For CNR evaluation a study to identify adequate contrast materials has been carried out. For contrast-detail study the CDRAD 2.0 phantom has been used. Image evaluation has been performed automatically with the commercial software CDRAD Analyser Ver. 1.1, considering the overall image quality index IQFinv. CNR and IQFinv were well correlated throughout all the clinical and subclinical exposure range, hence justifying the use of CNR as “working” parameter for equipment optimisation. In all investigated setups, images taken at lower high voltage settings scored better CNR values at comparable dose levels, making out a case for kV reduction with respect to clinical habit.
[1]
X Liu,et al.
Comparison of an amorphous silicon/cesium iodide flat-panel digital chest radiography system with screen/film and computed radiography systems--a contrast-detail phantom study.
,
2001,
Medical physics.
[2]
D S Evans,et al.
Investigation of optimum energies for chest imaging using film-screen and computed radiography.
,
2005,
The British journal of radiology.
[3]
A E Burgess,et al.
The Rose model, revisited.
,
1999,
Journal of the Optical Society of America. A, Optics, image science, and vision.
[4]
Z. F. Lu,et al.
Comparison of computed radiography and film/screen combination using a contrast‐detail phantom
,
2003,
Journal of applied clinical medical physics.
[5]
C P Lawinski,et al.
Evaluation of a software package for automated quality assessment of contrast detail images—comparison with subjective visual assessment
,
2005,
Physics in medicine and biology.