Imaging particle analysis: Difference between revisions

Revision as of 23:01, 13 January 2019

Revision as of 01:52, 22 January 2020

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# A gray scale [[Thresholding (image processing)|thresholding]] process is used to perform [[Image segmentation#Thresholding|image segmentation]], segregating out the particles from the background, creating a [[binary image]] of each particle.<ref name=Gonzalez>{{cite book|last=Gonzalez|first=Rafael C.|title=Digital Image Processing|year=2002|publisher=Pearson Education|isbn=978-8178086293|pages=595–611|author2=Woods, Richard E.}}</ref><ref name="Sankur2004">{{cite journal|last1=Sankur|first1=Bulent|title=Survey over image thresholding techniques and quantitative performance evaluation|journal=Journal of Electronic Imaging|volume=13|issue=1|year=2004|pages=146|issn=1017-9909|doi=10.1117/1.1631315|bibcode = 2004JEI....13..146S }}</ref><ref>{{cite journal|title=A Threshold Selection Method from Gray-Level Histograms|journal=IEEE Transactions on Systems, Man, and Cybernetics|volume=9|issue=1|year=1979|pages=62–66|issn=0018-9472|doi=10.1109/TSMC.1979.4310076|last1=Otsu|first1=Nobuyuki}}</ref>

# [[Digital image processing]] techniques are used to perform [[image analysis]] operations, resulting in morphological and grey-scale measurements to be stored for each particle.<ref name="CarterYan2005">{{cite journal|last1=Carter|first1=R M|last2=Yan|first2=Y|title=Measurement of particle shape using digital imaging techniques|journal=Journal of Physics: Conference Series|volume=15|issue=1|year=2005|pages=177–182|issn=1742-6588|doi=10.1088/1742-6596/15/1/030|bibcode = 2005JPhCS..15..177C }}</ref>

# The measurements saved for each particle are then used to generate image population statistics,<ref>{{cite web|last=Pouli|first=T.|title=Image Statistics and their Applications in Computer Graphics (2010)|url=http://www.cs.bris.ac.uk/~reinhard/papers/eg2010_tania.pdf|publisher=Eurographics, State of the Art|accessdate=2 January 2014|author2=Cunningham, D |author3=Reinhard, E.}}{{Dead link|date=January 2020 |bot=InternetArchiveBot |fix-attempted=yes }}</ref> or as inputs to algorithms for filtering and sorting the particles into groups of similar types. In some systems, sophisticated [[pattern recognition]] techniques<ref name="Rosenfeld1981">{{cite journal|last1=Rosenfeld|first1=A.|title=Image pattern recognition|journal=Proceedings of the IEEE|volume=69|issue=5|year=1981|pages=596–605|issn=0018-9219|doi=10.1109/PROC.1981.12027}}</ref><ref>{{cite book|last=Young|first=T. Y.|title=Handbook of Pattern Recognition and Image Processing|year=1986|publisher=Academic Press|isbn=978-0127745602}}</ref> may also be employed in order to separate different particle types contained in a heterogeneous sample.

Imaging particle analyzers can be subdivided into two distinct types, static and dynamic, based upon the image acquisition methods. While the basic principles are the same, the methods of image acquisition are different in nature, and each has advantages and disadvantages.

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In static image acquisition only one field of view image is captured at a time. If the user wishes to image other portions of the same sample on the slide, they can use the X-Y positioning hardware (typically composed of two [[linear stage]]s on the microscope to move to a different area of the slide. Care must be taken to insure that two images do not overlap so as not to count and measure the same particles more than once.

The major drawback to static image acquisition is that it is time consuming, both in sample preparation (getting the sample onto the slide with proper dilution if necessary), and in multiple movements of the stage in order to be able to acquire a statistically significant number of particles to count/measure. Computer-controlled X-Y positioning stages are sometimes used in these systems to speed the process up and to reduce the amount of operator intervention, but it is still a time consuming process, and the motorized stages can be expensive due to the level of precision required when working at high magnification.<ref name=Brown>{{cite web|last=Brown|first=L.|title=Dynamic Versus Static Image Acquisition in Particle Imaging|url=http://www.particleimaging.com/dynamic-versus-static-image-acquisition-in-particle-imaging/|work=www.particleimaging.com|accessdate=2 January 2014|archive-url=https://web.archive.org/web/20140103060115/http://www.particleimaging.com/dynamic-versus-static-image-acquisition-in-particle-imaging/|archive-date=3 January 2014|url-status=dead}}</ref>

The major advantages to static particle imaging systems are the use of standard microscope systems and simplicity of [[depth of field]] considerations. Since these systems can be made from any standard optical microscope, they may be a lower cost approach for people who already have microscopes. More important, though, is that microscope-based systems have less depth of field issues generally versus dynamic imaging systems. This is because the sample is placed on a microscope slide, and then usually covered with a [[cover slip]], thus limiting the plane containing the particles relative to the [[optical axis]]. This means that more particles will be in acceptable focus at high magnifications.<ref name=Brown />