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Diagnostic Pathology
Published in: Diagnostic Pathology 1/2015

Open Access 01-12-2015 | Research

Digital imaging of colon tissue: method for evaluation of inflammation severity by spatial frequency features of the histological images

Authors: Robertas Petrolis, Rima Ramonaitė, Dainius Jančiauskas, Juozas Kupčinskas, Rokas Pečiulis, Limas Kupčinskas, Algimantas Kriščiukaitis

Published in: Diagnostic Pathology | Issue 1/2015

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Abstract

Background

The efficacy of histological analysis of colon sections used for evaluation of inflammation severity can be improved by means of digital imaging giving quantitative estimates of main diagnostic features. The aim of this study was to reveal most valuable diagnostic features reflecting inflammation severity in colon and elaborate the evaluation method for computer-aided diagnostics.

Methods

Tissue specimens from 24 BALB/c mice and 15 patients were included in the study. Chronic and acute colon inflammation in mice was induced by oral administration of dextran sulphate sodium (DSS) solution, while mice in the control group did not get DSS. Human samples of inflamed colon tissue were obtained from patients with ulcerative colitis (n = 6). Non-inflamed colon tissue of control subjects (n = 9) was obtained from patients with irritable bowel syndrome or functional obstipation. Analysis of morphological changes in mice and human colon mucosa was performed using 4-μm haematoxylin-eosin (HE) sections. The features reflecting morphological changes in the images of colon mucosa were calculated by convolution of Gabor filter bank and array of pixel values. All features were generalized by calculating mean, histogram skewness and entropy of every image response. Principal component analysis was used to construct optimal representation of morphological changes.

Results

First principal component (PC1) was representing the major part of features variation (97 % in mice and 71 % in human specimens) and was selected as a measure of inflammation severity. Validation of new measure was performed by means of custom-made software realizing double blind comparison of differences in PC1 with expert’s opinion about inflammation severity presented in two compared pictures. Overall accuracy of 80 % for mice and 67 % for human was reached.

Conclusion

Principal component analysis of spatial frequency features of histological images may provide continuous scale estimation of inflammation severity of colon tissue.
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Metadata
Title
Digital imaging of colon tissue: method for evaluation of inflammation severity by spatial frequency features of the histological images
Authors
Robertas Petrolis
Rima Ramonaitė
Dainius Jančiauskas
Juozas Kupčinskas
Rokas Pečiulis
Limas Kupčinskas
Algimantas Kriščiukaitis
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Diagnostic Pathology / Issue 1/2015
Electronic ISSN: 1746-1596
DOI
https://doi.org/10.1186/s13000-015-0389-7

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