Analysis of the effects of discrete wavelet compression on automated mammographic mass shape classification

Lori Mann Bruce; Ravi Kalluri

doi:10.1117/12.348513

21 May 1999 Analysis of the effects of discrete wavelet compression on automated mammographic mass shape classification

Lori Mann Bruce, Ravi Kalluri

Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999) https://doi.org/10.1117/12.348513
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

This pilot study investigates the effect of discrete wavelet compression on automated mammographic mass shape classification. Commonly used shape features are extracted from masses for uncompressed and compressed images. These features include radial distance mean, standard deviation, entropy, zero-crossing count, roughness index, area-ratio, and compactness. The effects of the compression on these features are analyzed. Next, linear discriminant analysis is used to appropriately weight the features, and a minimum Euclidean distance classifier is used to separate the mass shapes into three classes: round, nodular, and stellate. The classification results are compared between the uncompressed and compressed images.

Citation Download Citation

Lori Mann Bruce and Ravi Kalluri "Analysis of the effects of discrete wavelet compression on automated mammographic mass shape classification", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348513

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