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22 May 2003 MTF correction for optimizing softcopy display of digital mammograms: use of a vision model for predicting observer performance
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Abstract
The goal of this project was to develop an efficient method of optimizing CRT monitor performance for digital mammography. In this study we examined the effects on performance of processing images to compensate for limitations in the MTF of the CRT monitor. The Sarnoff JNDmetrix vision model is based on just-noticeable difference measurement and frequency-channel vision-modeling principles. Given two images as input the model returns accurate, robust estimates of their discriminability. Model predictions are then compared with human performance. Mammographic images (n = 250) with microcalcifications were viewed by six radiologists. The images were viewed once in original unprocessed form and once after processing. Results were compared with output of the model that was used to predict differences in perceptibility of calcifications using luminance data measured with a high-resolution CCD camera. Human performance was better with the MTF compensated images at all contrast levels. The JNDmetrix model predicted the same pattern of results. Correlation between human and model observer performance was very high. Using image processing methods to compensate for limitations in the MTF of CRT monitors can improve the detection performance of radiologists searching for microcalcifications.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elizabeth A. Krupinski, Hans Roehrig, Michael Engstrom, Jeffrey P. Johnson, and Jeffrey Lubin "MTF correction for optimizing softcopy display of digital mammograms: use of a vision model for predicting observer performance", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); https://doi.org/10.1117/12.479980
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