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Histogram-based Image Quality Checking

Many medical image analysis algorithms make assumptions concerning the image formation process, the structure of the intensity histogram, or other statistical properties of the input data. Application of such algorithms to image data that do not fit these assumptions will produce unreliable results. This paper describes a technique for the automatic identification of images that do not have histogram structure consistent with that expected. The approach is based upon a component analysis followed by statistical testing. Experiments validate its use in the identification of quantisation problems and unexpected image structure. It is intended that this test will form one component of a quality control assessment, to aid in the use of sophisticated statistical image analysis software by non-expert users.