Literature DB >> 12609728

Assessing technician effects when extracting quantities from microscope images.

D Webb1, M A Hamilton, G J Harkin, S Lawrence, A K Camper, Z Lewandowski.   

Abstract

Consider an experiment where the response is based on an image; e.g., an image captured to a computer file by a digital camera mounted on a microscope. Suppose relevant quantitative measures are extracted from the images so that results can be analyzed by conventional statistical methods. The steps involved in extracting the measures may require that the technicians, who are processing the images, perform some subjective manipulations. In this case, it is important to determine the bias and variability, if any, attributable to the technicians' decisions. This paper describes the experimental design and statistical analyses that are useful for those determinations. The design and analysis are illustrated by application to two biofilm research projects that involved quantitative image analysis. In one investigation, the technician was required to choose a threshold level, then the image analysis program automatically extracted relevant measures from the resulting black and white image. In the other investigation, the technician was required to choose fiducial points in each of two images collected on different microscopes; then the image analysis program registered the images by stretching, rotating, and overlaying them, so that their quantitative features could be correlated. These investigations elucidated the effects of the technicians' decisions, thereby helping us to assess properly the statistical uncertainties in the conclusions for the primary experiments.

Mesh:

Year:  2003        PMID: 12609728     DOI: 10.1016/s0167-7012(02)00228-2

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  5 in total

Review 1.  Quantitative imaging of protein interactions in the cell nucleus.

Authors:  Ty C Voss; Ignacio A Demarco; Richard N Day
Journal:  Biotechniques       Date:  2005-03       Impact factor: 1.993

2.  Tissue microarrays as a tool in the discovery and validation of predictive biomarkers.

Authors:  Stephen M Hewitt
Journal:  Methods Mol Biol       Date:  2012

3.  Quantitative methods to analyze subnuclear protein organization in cell populations with varying degrees of protein expression.

Authors:  Ty C Voss; Ignacio A Demarco; Cynthia F Booker; Richard N Day
Journal:  J Biomed Opt       Date:  2005 Mar-Apr       Impact factor: 3.170

4.  Simulation of bright-field microscopy images depicting pap-smear specimen.

Authors:  Patrik Malm; Anders Brun; Ewert Bengtsson
Journal:  Cytometry A       Date:  2015-01-08       Impact factor: 4.355

5.  A model of the spatial tumour heterogeneity in colorectal adenocarcinoma tissue.

Authors:  Violeta N Kovacheva; David Snead; Nasir M Rajpoot
Journal:  BMC Bioinformatics       Date:  2016-06-24       Impact factor: 3.169

  5 in total

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