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Med Phys ; 38(9): 5090-3, 2011 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-21978054

RESUMO

PURPOSE: According to the European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) image quality of digital mammography devices has to be assessed using human evaluation of the CDMAM contrast-detail phantom. This is accomplished by the determination of threshold thicknesses of gold disks with different diameters (0.08-2 mm) and revealed to be very time consuming. Therefore a software solution based on a nonprewhitening matched filter (NPW) model was developed at the University of Nijmegen. Factors for the conversion from automatic to human readouts have been determined by Young et al. [Proc. SPIE 614206, 1-13 (2006) and Proc. SPIE 6913, 69131C1 (2008)] using a huge amount of data of both human and automatic readouts. These factors depend on the observer groups and are purely phenomenological. The authors present an alternative approach to determine the factors by using the Rose observer model. METHODS: Their method uses the Rose theory which gives a relationship between threshold contrast, diameter of the object and number of incident photons. To estimate the conversion factors for the five diameters from 0.2 to 0.5 mm they exposed with five different current-time products which resulted in 25 equations with five unknowns. RESULTS: The theoretical conversion factors (in dependence of the diameters) amounted to be 1.61 ± 0.02 (0.2 mm diameter), 1.67 ± 0.02 (0.25 mm), 1.85 ± 0.02 (0.31 mm), 2.09 ± 0.02 (0.4 mm), and 2.28 ± 0.02 (0.5 mm). The corresponding phenomenological factors found in literature are 1.74 (0.2 mm), 1.78 (0.25 mm), 1.83 (0.31 mm), 1.88 (0.4 mm), and 1.93 (0.5 mm). CONCLUSIONS: They transferred the problem of determining the factors to a well known observer model which has been examined for many years and is also well established. This method reveals to be reproduceable and produces factors comparable to the phenomenological ones.


Assuntos
Mamografia/métodos , Automação , Ouro , Humanos , Processamento de Imagem Assistida por Computador , Imagens de Fantasmas
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