An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography
Physics in Medicine and Biology
This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose-reduction in X-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical industrial film/screen-system (KODAK Min-R 2000/2190) . The first part of the paper deals with the simulation of dose reduction for film-screen mammography, based on a physical model of the imaging process. More sensitive film
... l results in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results to ground truth images obtained under the supervision of an expert radiologist allows to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on the detection rates. For moderate smoothing, a dose reduction by 25% has no serious influence on the detection results, whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasise the impact of more sensitive film material and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.