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Proceedings Paper

Analysis of the trade-offs between manual and computer-based stereology/classification
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Paper Abstract

Estimation of volume or area of tissue types in an image requires both mensuration and classification. The former is achieved through stereology -- a set of techniques that estimate such parameters as area, volume, surface area, length, and number. Classification is achieved by extracting features that capture the discriminating information about tissue type. Both stereology and classification can be performed either manually or by computer. Manual techniques for the combination are based on coarse point counting (low resolution), but assumed perfect pixel classification. Computer-based methods, on the other hand, rely on very fine point counting but in general suffer from imperfect pixel classification. This paper examines the interaction between manual and image processing-based approaches; in particular, we present a measure that combines the classification and measurement errors. Estimation of the variance is used to define the conditions under which each method is and is not advantageous despite its underlying error. This allows the user to choose a method that optimizes overall performance, given the human and machine capabilities available. Illustrations are given of cases in which each method can be preferable, as measured by the variance of the estimate of the performance that was inferred from the measurement.

Paper Details

Date Published: 15 May 2003
PDF: 11 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481911
Show Author Affiliations
Zvi Markowitz, George Washington Univ. (United States)
Murray H. Loew, George Washington Univ. (United States)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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