Mammography images undergo vendor-specific processing, which may be nonlinear, before radiologist interpretation. Therefore, to test the entire imaging chain, the effect of image processing should be included in the assessment of image quality, which is not current practice. For this purpose, model observers (MOs), in combination with anthropomorphic breast phantoms, are proposed to evaluate image quality in mammography. In this study, the nonprewhitening MO with eye filter and the channelized Hotelling observer were investigated. The goal of this study was to optimize the efficiency of the procedure to obtain the expected signal template from acquired images for the detection of a 0.25-mm diameter disk. Two approaches were followed: using acquired images with homogeneous backgrounds (approach 1) and images from an anthropomorphic breast phantom (approach 2). For quality control purposes, a straightforward procedure using a single exposure of a single disk was found adequate for both approaches. However, only approach 2 can yield templates from processed images since, due to its nonlinearity, image postprocessing cannot be evaluated using images of homogeneous phantoms. Based on the results of the current study, a phantom should be designed, which can be used for the objective assessment of image quality.
The use of model observers for image quality assessment in digital mammography is currently being considered. Model observers assign decision variables to signal present and signal absent images which, if they are independent, can be used as a measure of performance. In this study, the impact of different dependencies at pixel level between the signal present and signal absent images were studied for the detection of 0.25 mm and 2.5 mm diameter disk-shaped objects. Clinical images were acquired on an Amulet Innovality (FujiFilm, Tokio, Japan) mammography unit and modified multiple times to appear as acquired at 75% of the original dose level and to simulate different noise realizations. From these modified images, regions of interest (ROIs), with and without an embedded signal were obtained. Subsequently, detection experiments were created for which the images with and without embedded signals had: 1) exactly the same background structures, 2) the same background structures but different quantum noise realizations, and 3) completely different background structures. The ROIs were evaluated using a channelized Hotelling observer (CHO) with a dense difference of Gaussian channel set. It was found that if the background structures within the ROIs with and without signal are dependent, the CHO decision variables also show strong dependencies. However, the performance measurement of the CHO yielded values that were not affected by the dependency in pixel values. This finding is important for future developments of phantom-based image quality analysis in mammography using model observers when using a single or a limited number of anthropomorphic phantoms.
Model observers (MOs) are being investigated for image quality assessment in full-field digital mammography (FFDM). Signal templates for the non-prewhitening MO with eye filter (NPWE) were formed using acquired FFDM images. A signal template was generated from acquired images by averaging multiple exposures resulting in a low noise signal template. Noise elimination while preserving the signal was investigated and a methodology which results in a noise-free template is proposed. In order to deal with signal location uncertainty, template shifting was implemented. The procedure to generate the template was evaluated on images of an anthropomorphic breast phantom containing microcalcification-related signals. Optimal reduction of the background noise was achieved without changing the signal. Based on a validation study in simulated images, the difference (bias) in MO performance from the ground truth signal was calculated and found to be <1%. As template generation is a building stone of the entire image quality assessment framework, the proposed method to construct templates from acquired images facilitates the use of the NPWE MO in acquired images.