Diagnostic imaging--evaluating image quality using visual grading characteristic (VGC) analysis.
Radiologists are regularly faced with the task of comparing image quality obtained using different imaging systems or settings. Visual grading techniques can be used to evaluate the quality of images by grading the clarity of reproduction of anatomical or pathological structures. The methods, which include "visual grading analysis (VGA)" and the "image criteria (IC) study", are characterised by their attractive simplicity and reliability. Non-parametric rank-invariant statistical methods are suitable techniques for statistical analysis of VGA-data. Båth and Månsson (2007) introduced such a method and termed it "visual grading characteristics (VGC) analysis". This paper gives an overview of the principle together with an example of its use in veterinary radiology. The aim of this review article is to encourage veterinary researchers to apply this method which has proven valuable in the human field. Basically, the method can also be applied for the analysis of other categories of images (e.g. histological sections, cytological smears) in cases where the task is to evaluate features subjectively on the basis of a score, allowing some degree of freedom of decision. Furthermore, the aim of the investigation is not necessarily restricted to quality aspects. Other questions such as the effects of treatment options on the appearance of certain structures can be compared as well.
Ludewig
Eberhard
E
Department of Small Animal Medicine, Faculty of Veterinary Medicine, University of Leipzig, An den Tierkliniken 23, 04103, Leipzig, Germany. ludewig@vetmed.uni-leipzig.de
Richter
Andreas
A
Frame
Mairi
M
D000704:Analysis of Variance; D000818:Animals; D003627:Data Interpretation, Statistical; D003952:Diagnostic Imaging / Q000379:methods / Q000592:standards / Q000662:veterinary*; D007089:Image Enhancement / Q000592:standards; D015588:Observer Variation
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