Analysis of the Effects of Discrete Wavelet Compression on Automated Mammographic Mass Shape Classification

Document Type

Conference Proceeding

Publication Date

1999

Publication Title

Image Processing: Medical Imaging 1999: Proceedings of SPIE

Publisher

SPIE

Volume

3661

First page number:

1190

Last page number:

1195

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.

Keywords

Classification--Computer programs; Diagnostic imaging; Image analysis; Image processing; Wavelets (Mathematics)

Disciplines

Electrical and Computer Engineering | Engineering | Signal Processing | Systems and Communications

Language

English

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

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