Image feature extraction for mass detection in digital mammography: effects of wavelet analysis

Lihua Li; Wei Qian; Laurence P. Clarke

doi:10.1117/12.310843

24 June 1998 Image feature extraction for mass detection in digital mammography: effects of wavelet analysis

Lihua Li, Wei Qian, Laurence P. Clarke

Author Affiliations +

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310843
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

Multiresolution and multiorientation wavelet transforms (WTs), as the key CAD modules, were used in our previous study of CAD mass detection. The objective of this paper is to evaluate the roles of these WTs modules in the proposed CAD approach. A statistical analysis of the effects of WTs on image feature extraction for mass detection is taken including the effects of WTs on mass segmentation and a comparative study of discrimination ability of features extracted with WTs based and non-WTs based segmentation method. Three indexes are proposed to asses the segmentation. The effects of WTs on feature extraction are evaluated using ROC analysis of the feature discrimination ability. The statistical analysis demonstrates that the use of WTs modules results in a significant improvement in feature extraction for the previously proposed CAD mass detection method. The improvement, however, depends on the feature characteristics, large for boundary-related features while small for intensity-related features.

Citation Download Citation

Lihua Li, Wei Qian, and Laurence P. Clarke "Image feature extraction for mass detection in digital mammography: effects of wavelet analysis", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310843

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