Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms

Robert M. Nishikawa; John Papaioannou; Stephen A. Collins

doi:10.1117/12.237942

16 April 1996 Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms

Robert M. Nishikawa, John Papaioannou, Stephen A. Collins

Author Affiliations +

Proceedings Volume 2710, Medical Imaging 1996: Image Processing; (1996) https://doi.org/10.1117/12.237942
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

Computer-aided diagnosis can be defined as a diagnosis made by a radiologist who takes into account the computerized analysis of the radiograph. The potential advantage of this approach is that errors by human observers that are caused by intra-observer variation, can be caught by the computer, which performs a thorough, methodical search of the image. However, if the input image to computer comes from a digitized radiograph, then the process of digitization introduces variability into the computer analysis of the image. Because the film digitizer samples the image, re-digitization will not necessarily produce the exact same digital image, and subsequently, the computerized scheme may produce different results on the different samples of the original image. The purpose of this study was to examine the amount of variability introduced by film digitization by measuring the reproducibility of our computerized scheme for the detection of clustered microcalcifications on mammograms when the mammogram is digitized a number of times. We have found in general that if the detected cluster (either a true or false cluster) corresponds to some obvious anatomical structure, then the cluster will be re-detected upon re-digitization. If, however, the cluster corresponds to low contrast objects within the breast, including image noise, then the cluster is not likely to be re- detected. As a result, true clusters tend to be much more reproducible than false-positive clusters. In the future, when direct digital radiographs are used as input to the computerized schemes, problems with reproducibility will not exist.

Citation Download Citation

Robert M. Nishikawa, John Papaioannou, and Stephen A. Collins "Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237942

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