Title

Cancer diagnosis by nuclear morphometry using spatial information (.)

Date of Original Version

6-1-2014

Type

Article

PubMed ID

24910485

Abstract or Description

Methods for extracting quantitative information regarding nuclear morphology from histopathology images have been long used to aid pathologists in determining the degree of differentiation in numerous malignancies. Most methods currently in use, however, employ the naïve Bayes approach to classify a set of nuclear measurements extracted from one patient. Hence, the statistical dependency between the samples (nuclear measurements) is often not directly taken into account. Here we describe a method that makes use of statistical dependency between samples in thyroid tissue to improve patient classification accuracies with respect to standard naïve Bayes approaches. We report results in two sample diagnostic challenges.

DOI

10.1016/j.patrec.2014.02.008

 

Published In

Pattern Recognition Letters, 42, 115-121.