| Automatic recognition of five types of white blood cells in peripheral blood. | |
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MedLine Citation:
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PMID: 21300521 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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This paper proposes image processing algorithms to recognize five types of white blood cells in peripheral blood automatically. First, a method based on Gram-Schmidt orthogonalization is proposed along with a snake algorithm to segment nucleus and cytoplasm of the cells. Then, a variety of features are extracted from the segmented regions. Next, most discriminative features are selected using a Sequential Forward Selection (SFS) algorithm and performances of two classifiers, Artificial Neural Network (ANN) and Support Vector Machine (SVM), are compared. The results demonstrate that the proposed methods are accurate and sufficiently fast to be used in hematological laboratories. |
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Authors:
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Seyed Hamid Rezatofighi; Hamid Soltanian-Zadeh |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-2-5 |
Journal Detail:
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Title: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Volume: - ISSN: 1879-0771 ISO Abbreviation: - Publication Date: 2011 Feb |
Date Detail:
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Created Date: 2011-2-8 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8806104 Medline TA: Comput Med Imaging Graph Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2011 Elsevier Ltd. All rights reserved. |
Affiliation:
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Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran 14395-515, Iran. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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