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Conference proceeding
Rapid segmentation of calcification clusters using multi-resolution guided fuzzy c-means and wavelet processing
Digital Mammography: IWDM2002: 6th International Workshop on Digital Mammography: Proceedings of the Workshop June 22-25,2002, Bremen, Germany, pp.414-416
International Workshop on Digital Mammography (Bremen, Germany, 06/22/2002–06/25/2002)
2003
Abstract
Work presented here focuses on employing wavelets, multi-resolution guided fuzzy c-means (FCM), and coarse-to-fine feature analysis for rapid detection of microcalcification clusters in uncropped images. FCM segmentation is guided through a multi-resolution approach to rapidly distinguish medically relevant tissue from background. Sets of overlapping sub images, containing only relevant tissue, are extracted from the image for further high-resolution analysis. A minimum number of features are used in a simple fuzzy system to
detect candidate microcalcifications. This coarse detection is shown to provide high detection rates while minimizing the data points requiring further feature analysis. Feature extraction and classification is performed with a radial basis function (RBF) neural network. Cluster analysis provides final detection.
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Details
- Title
- Rapid segmentation of calcification clusters using multi-resolution guided fuzzy c-means and wavelet processing
- Publication Details
- Digital Mammography: IWDM2002: 6th International Workshop on Digital Mammography: Proceedings of the Workshop June 22-25,2002, Bremen, Germany, pp.414-416
- Resource Type
- Conference proceeding
- Conference
- International Workshop on Digital Mammography (Bremen, Germany, 06/22/2002–06/25/2002)
- Contributors
- Heinz-Otto Peitgen (Editor)
- Publisher
- Springer-Verlag; Berlin, Germany
- Copyright
- Springer- Verlag Berlin Heidelberg 2003
- Identifiers
- 99380090648006600
- Academic Unit
- Public Health; Usha Kundu, MD College of Health
- Language
- English