Image processing of hematoxylin and eosin-stained tissues for pathological evaluation.

Abstract:

:Color and geometric characteristics of stained areas in histochemical slides are among the features pathologists assess to evaluate the severity of lesions. In this research, image processing techniques were used to perform objective quantification of these characteristics in images of H&E-stained spleen tissues. A segmentation algorithm was developed to isolate the areas of interest in microscopic tissue images. Image features important to pathological evaluation were then extracted. These features were used to build statistical and neural network models to predict pathologist scores. A linear regression model predicted the scores to an R(2)-value of 0.6, and a neural network model classified samples to an accuracy of 75%. The results show the usefulness of image processing as a tool for pathological evaluation.

journal_name

Toxicol Mech Methods

authors

Liu X,Tan J,Hatem I,Smith BL

doi

10.1080/15376520490434638

subject

Has Abstract

pub_date

2004-01-01 00:00:00

pages

301-7

issue

5

eissn

1537-6516

issn

1537-6524

journal_volume

14

pub_type

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