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[[Image:Microscope with stained slide.jpg|thumb|A stained histologic specimen, sandwiched between a glass [[microscope slide]] and coverslip, mounted on the stage of a light microscope.]]
[[Image:Emphysema H and E.jpg|thumb|Microscopic view of a histologic specimen of human [[lung]] tissue stained with [[hematoxylin]] and [[eosin]].]]
'''Automated tissue image analysis''' or '''histopathology image analysis''' ('''HIMA''') is a process by which computer-controlled [[automatic test equipment]] is used to evaluate [[tissue (biology)|tissue]] samples, using computations to derive quantitative measurements from an image to avoid subjective errors.
In a typical application, automated tissue image analysis could be used to measure the aggregate activity of [[cancer cell]]s in a [[biopsy]] of a [[cancer]]ous [[tumor]] taken from a patient. In [[breast cancer]] patients, for example, automated tissue image analysis may be used to test for high levels of [[proteins]] known to be present in more aggressive forms of breast cancers.
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|doi=10.1109/TBME.1985.325587
|pmid=4054933
|s2cid=30050996
}}</ref> or improve the prediction rate of recurrence of some cancers.<ref name="Teverovskiy_2004">
{{cite book
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|last9=Fogarasi |first9=S.
|last10=Saidi |first10=O.
|s2cid=8724168
}}</ref><ref>{{cite journal
|journal=IEEE Transactions on Medical Imaging
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|author6=Angeliki Kotsianti
|author7=Olivier Saidi
|s2cid=14673541
|url=http://claymore.rfmh.org/~atabesh/papers/tabesh_tmi07_final.pdf
|access-date=2010-09-04
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==Processes==
The [[United States of America|United States]] [[Food and Drug Administration]] classifies these systems as [[medical device]]s, under the general instrumentation category of [[automatic test equipment]].<ref>{{cite book|url=https://books.google.com/books?id=nEHLxh9wxZIC
ATIS have seven basic processes (sample preparation, image acquisition, image analysis, results reporting, data storage, network communication, and self-system diagnostics) and realization of these functions highly accurate hardware and well-integrated, complex, and expensive software.<ref>{{cite journal|doi=10.1016/j.aca.2005.11.083 |pmid=17723364 |title=Analytica Chimica Acta - Advances in cancer tissue microarray technology: Towards improved understanding and diagnostics|volume=564 |issue=1 |journal=Analytica Chimica Acta |pages=74–81|pmc=2583100|year=2006 |last1=Chen |first1=W. |last2=Foran |first2=D. J. }}</ref>
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===Analysis===
[[Image analysis]] involves complex computer algorithms which identify and characterize cellular color, shape, and quantity of the tissue sample using image pattern recognition technology based on [[vector quantization]]. Vector representations of objects in the image, as opposed to bitmap representations, have superior zoom-in ability. Once the sample image has been acquired and resident in the computer's random access memory as a large array of 0's and 1's, a programmer knowledgeable in cellular architecture can develop deterministic [[algorithms]] applied to the entire memory space to detect cell patterns from previously defined cellular structures and formations known to be significant.<ref name="han12cell">{{cite journal| author=Han, J.W.| author2=Breckon, T.P.| author3=Randell, D.A.| author4=Landini, G.| title=The Application of Support Vector Machine Classification to Detect Cell Nuclei for Automated Microscopy| journal=Machine Vision and Applications| year=2012| volume=23| pages=15–24| publisher=Springer| doi=10.1007/s00138-010-0275-y| issue=1| s2cid=12446454}}</ref>
==See also==
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