Abstract
In the screening mammographic examination of large parts of populations thousands of mammograms are analysed. The Computer Aided Diagnosis methods available still tend to produce too many false positive (FP) detections with respect to the number of true positive (TP) detections, which makes it impractical to use such methods to support the human observer in the analysis of mammograms. In this paper an attempt has been made to decrease the number of FP errors in the hierarchical correlation-based cancerous mass detection method by eliminating the images of linear structures (LSs) from the mammograms. The LSs were detected with an accumulationbased line detector and the image intensity function in the regions of the LSs was interpolated with an anisotropic membrane. Examples of images representing typical detection problems caused by the LSs selected from the MIAS database suggest the feasibility of the proposed approach.
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Bator, M., Chmielewski, L.J. (2007). Elimination of Linear Structures as an Attempt to Improve the Specificity of Cancerous Mass Detection in Mammograms. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_75
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DOI: https://doi.org/10.1007/978-3-540-75175-5_75
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