Imaging particle analysis: Difference between revisions

Revision as of 22:51, 13 January 2019

Revision as of 23:01, 13 January 2019

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The basic process by which imaging particle analysis is carried out is as follows:

# A digital camera captures an image of the [[field of view]] in the optical system.

# 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=8178086298978-8178086293|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. }}</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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===Micro-flow imaging===

''Micro-flow imaging (MFI)'' is a particle analysis technique that uses flow [[microscopy]] to quantify particles contained in a solution based on size. This technique is used in the [[biopharmaceutical]] industry to characterize subvisible particles from approximately 1 μm to >50 μm.<ref>{{cite journal | pmc = 2895433 | pmid=20517661 | doi=10.1208/s12248-010-9205-1 | volume=12 | issue=3 | title=Micro-flow imaging: flow microscopy applied to sub-visible particulate analysis in protein formulations | year=2010 | journal=AAPS J | pages=455–64 | last1 = Sharma | first1 = DK | last2 = King | first2 = D | last3 = Oma | first3 = P | last4 = Merchant | first4 = C}}</ref>