Abstract
To establish a practical CAD (Computer-Aided Diagnosis) system to facilitate the diagnosis of microcalcifications, we propose a filter-based technique to detect microcalcifications. Via examination of an existing optimal filter-based technique, it is found that its performance on highlighting the energy of mammograms is seriously affected by artefacts and the background of breast. As a result, four methods in pre and post-processing are described in this paper to improve the optimal filtering, leading to an adaptive selection of thresholds for input mammograms. These methods have been tested by using 30 mammograms (with 25 microcalcifications) from the MIAS database and 23 mammograms from DDSM database. Comparing with the original optimal filter-based technique, our technique reduces the false detections (FD), eliminates the influence of the background in mammograms and is able to adaptively select the threshold for the detection of microcalcifications.
Keywords
- True Positive Rate
- White Spot
- Digital Mammography
- False Detection
- Optimal Filter
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2006 Springer-Verlag Berlin Heidelberg
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Wu, Z.Q., Jiang, J., Peng, Y.H., Gulsrud, T.O. (2006). A Filter-Based Approach Towards Automatic Detection of Microcalcification. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_57
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DOI: https://doi.org/10.1007/11783237_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35625-7
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