Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

Erich Pelikan; Frank Vogelsang; Thomas Tolxdorff

doi:10.1117/12.237924

16 April 1996 Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

Erich Pelikan, Frank Vogelsang, Thomas Tolxdorff

Author Affiliations +

Proceedings Volume 2710, Medical Imaging 1996: Image Processing; (1996) https://doi.org/10.1117/12.237924
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

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Erich Pelikan, Frank Vogelsang, and Thomas Tolxdorff "Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237924

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