A neural-network-based approach to white blood cell classification

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Title:	A neural-network-based approach to white blood cell classification
Authors:	蘇木春;Su, Mu-Chun;Wang, Pa-Chun;Cheng, Chun-Yen
Contributors:	資訊電機學院資訊工程學系
Keywords:	Accuracy;Algorithms;Automation;Blood;Bone marrow;Classification;Color;Flow cytometry;Humans;Identification and classification;Leukemia;Leukocytes;Leukocytes - classification;Methods;Neural networks;Neural Networks (Computer);Principal components analysis;Wavelet transforms
Date:	2014-01-01
Issue Date:	2026-04-23 13:06:14 (UTC+8)
Publisher:	Hindawi Limited;Cairo, Egypt: Hindawi Publishing Corporation
Abstract:	摘要： This paper presents a new white blood cell classification system for the recognition of five types of white blood cells. We propose a new segmentation algorithm for the segmentation of white blood cells from smear images. The core idea of the proposed segmentation algorithm is to find a discriminating region of white blood cells on the HSI color space. Pixels with color lying in the discriminating region described by an ellipsoidal region will be regarded as the nucleus and granule of cytoplasm of a white blood cell. Then, through a further morphological process, we can segment a white blood cell from a smear image. Three kinds of features (i.e., geometrical features, color features, and LDP-based texture features) are extracted from the segmented cell. These features are fed into three different kinds of neural networks to recognize the types of the white blood cells. To test the effectiveness of the proposed white blood cell classification system, a total of 450 white blood cells images were used. The highest overall correct recognition rate could reach 99.11% correct. Simulation results showed that the proposed white blood cell classification system was very competitive to some existing systems. 其他題名： ScientificWorldJournal 出版者： Cairo, Egypt: Hindawi Publishing Corporation 出版日期： 2014-01-01 出處： TheScientificWorld, 2014-01, Vol.2014 (2014), p.1-9 資源來源： Agricultural & Environmental Science Collection 版權： Copyright © 2014 Mu-Chun Su et al. 版權： COPYRIGHT 2014 John Wiley & Sons, Inc. 版權： COPYRIGHT 2014 Hindawi Limited 版權： Copyright © 2014 Mu-Chun Su et al. Mu-Chun Su et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 版權： Copyright © 2014 Mu-Chun Su et al. 2014 識別號： ISSN: 2356-6140 識別號： ISSN: 1537-744X 識別號： EISSN: 1537-744X 識別號： DOI: 10.1155/2014/796371 識別號： PMID: 24672374
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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