| Unsupervised classification of cell images using pyramid node linking. | |
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MedLine Citation:
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PMID: 2191915 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In this communication we describe a segmentation technique which combines two properties in an iterative and hierarchial matter to correctly segment and classify the given cell images. The technique is applied to digital images taken from microscope slides of cultured rat liver cells, and the goal is to classify these cells into one of three possible classes. The first class cells (I) are morphologically normal and stain the darkest. The second class cells (II) are slightly damaged showing both nuclear and cytoplasmic swelling with resultant lessening of staining affinity. The third class cells (III) are markedly damaged as demonstrated by the presence of cytoplasmic vacuolization, or are completely disintegrated. First class cells are classified by taking advantage of their staining affinity; the original gray level image is segmented into four gray levels. The darkest is then classified as type I. Type III cells are classified by using high business as a characteristic; the standard deviation of the original image is segmented into four business levels. The highest level is classified as type III cell. Assuming only the three cell types are present in any given image, the remaining non-background unclassified pixels are determined to belong to type II cells. |
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Authors:
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F Arman; J A Pearce |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S. |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: 37 ISSN: 0018-9294 ISO Abbreviation: IEEE Trans Biomed Eng Publication Date: 1990 Jun |
Date Detail:
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Created Date: 1990-07-24 Completed Date: 1990-07-24 Revised Date: 2009-11-11 |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: UNITED STATES |
Other Details:
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Languages: eng Pagination: 647-50 Citation Subset: IM |
Affiliation:
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Department of Electrical and Computer Engineering, University of Texas at Austin 78712. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Animals Cells, Cultured Cytological Techniques* Image Processing, Computer-Assisted / methods* Liver / cytology, ultrastructure Rats |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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