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Proceedings Paper

Pattern classification approach to segmentation of digital chest radiographs and chest CT image slices
Author(s): Michael F. McNitt-Gray; James W. Sayre; H. K. Huang; Mahmood Razavi; Denise R. Aberle
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Paper Abstract

The goal of this research was to develop a segmentation method based on a pattern classification approach. The pattern classification approach consists of classifying each pixel into one of several anatomic classes on the basis of one or more feature values. In this research, three types of locally calculated features are used: gray-level based measures, local difference measures and local texture measures. A feature selection process is performed to determine which features best discriminate between the anatomic classes. Three classifiers are used: a linear discriminant function, a k-nearest neighbor approach and a neural network. Supervised techniques train each classifier to learn the characterstics of the anatomic classes. Each classifier is trained and tested using normal images. The pattern classification approach to image segmentation has shown promise for further development. Locally calculated features are important in classifying pixels, but these alone may not be sufficient. A method for incorporating spatial information into the classification decision appears to improve the results and may be necessary for reliable segmentation. This research also shows that the pattern classification approach may be applied to images from different modalities.

Paper Details

Date Published: 11 May 1994
PDF: 12 pages
Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175080
Show Author Affiliations
Michael F. McNitt-Gray, Univ. of California/Los Angeles (United States)
James W. Sayre, Univ. of California/Los Angeles (United States)
H. K. Huang, Univ. of California/San Francisco (United States)
Mahmood Razavi, Univ. of California/Los Angeles (United States)
Denise R. Aberle, Univ. of California/Los Angeles (United States)


Published in SPIE Proceedings Vol. 2167:
Medical Imaging 1994: Image Processing
Murray H. Loew, Editor(s)

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