Observer variation in quantification of immunocytochemistry by image analysis

Jagoe R., Steel J.H., Vucicevic V., Alexander N., Van Noorden S., Wootton R. and Polak J.M. (1991) Observer variation in quantification of immunocytochemistry by image analysis. The Histochemical Journal, 23 11-12: 541-547. doi:10.1007/BF01041181

Author Jagoe R.
Steel J.H.
Vucicevic V.
Alexander N.
Van Noorden S.
Wootton R.
Polak J.M.
Title Observer variation in quantification of immunocytochemistry by image analysis
Journal name The Histochemical Journal   Check publisher's open access policy
ISSN 0018-2214
Publication date 1991-01-01
Sub-type Article (original research)
DOI 10.1007/BF01041181
Open Access Status Not yet assessed
Volume 23
Issue 11-12
Start page 541
End page 547
Total pages 7
Publisher Kluwer Academic Publishers
Language eng
Subject 2702 Anatomy
1307 Cell Biology
Abstract This paper reports the findings of a study designed to examine observer variation as a source of inaccuracy inherent in the use of computer-assisted image analysis to measure areas of stained tissue. The rat pituitary immunostained for prolactin and galanin was used as an example to estimate patterns of immunoreactivity exhibited by different cell types. Six observers, with differing experience, selected grey level threshold values on 40 fields of images of stained tissue making three repeats of each field. The 40 fields consisted of 20 serial pairs of colocalized fields, one immunostained for prolactin, the other for galanin. The 20 pairs consisted of four pairs from each of five animals. Analysis of observer variation in the selection of threshold values showed large differences in the within-and between-observer variation. Analysis of the components of variance in the estimation of the ratios of stained tissues showed that the major source of variation was the within-observer component. An additional experiment using two observers, where half of the images were compared to the original microscope images before setting threshold levels, showed that the opportunity to make a comparison did not reduce observer variation. It is suggested that any study which uses semi-automatic methods to segment regions of a digital image can benefit from an analysis of this kind so that the sources of variation can be determined to enable maximum discriminating power in future studies.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
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