Automatic working area classification in peripheral blood smears without cell central zone extraction

W. Xiong; J. H. Lim; S. H. Ong; N. N. Tung; J. Liu; D. Racoceanu; K. Tan; A. Chong; K. Foong

doi:10.1109/iembs.2008.4650104

Automatic working area classification in peripheral blood smears without cell central zone extraction

W. Xiong, J. H. Lim, S. H. Ong, N. N. Tung, J. Liu, D. Racoceanu, K. Tan, A. Chong, K. Foong

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

In this paper we study automatic classification of working areas in peripheral blood smears using image analysis and recognition methods. Such automatic classification can provide objective and reproducible quality control for the evaluation of smears and smear maker devices. However, research in this filed has drawn little attention. Existing methods either can not differentiate correctly different cell distributions or rely on the extraction of the central pallor zones in cells for counting, which are not always observable. In contrast, we do not rely on the pallor zone extraction thus on more general basis. We introduce two generic parameters to measure the goodness of working areas, one for the degree of overlap, and the other for the spatial occupancy. We also propose a cascading classification network for the classification of different areas. The effectiveness of our method has been tested on over 150 labeled images acquired from three malaria-infected Giemsa-stained blood smears using an oil immersion 100x objective.

Original language	English
Title of host publication	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Publisher	IEEE Computer Society
Pages	4074-4077
Number of pages	4
ISBN (Print)	9781424418152
DOIs	https://doi.org/10.1109/iembs.2008.4650104
Publication status	Published - 2008
Externally published	Yes
Event	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada Duration: 20 Aug 2008 → 25 Aug 2008

Publication series

Name	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conference

Conference	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/Territory	Canada
City	Vancouver, BC
Period	20/08/08 → 25/08/08

Keywords

Central pallor zone
Classification
Distribution
Equivalent diameter
Generic features
Occupancy
Overlap
Peripheral blood smears
Working area

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Biomedical Engineering
Health Informatics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/iembs.2008.4650104

Cite this

Xiong, W., Lim, J. H., Ong, S. H., Tung, N. N., Liu, J., Racoceanu, D., Tan, K., Chong, A., & Foong, K. (2008). Automatic working area classification in peripheral blood smears without cell central zone extraction. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 4074-4077). Article 4650104 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"). IEEE Computer Society. https://doi.org/10.1109/iembs.2008.4650104

Xiong, W. ; Lim, J. H. ; Ong, S. H. et al. / Automatic working area classification in peripheral blood smears without cell central zone extraction. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. pp. 4074-4077 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

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title = "Automatic working area classification in peripheral blood smears without cell central zone extraction",

abstract = "In this paper we study automatic classification of working areas in peripheral blood smears using image analysis and recognition methods. Such automatic classification can provide objective and reproducible quality control for the evaluation of smears and smear maker devices. However, research in this filed has drawn little attention. Existing methods either can not differentiate correctly different cell distributions or rely on the extraction of the central pallor zones in cells for counting, which are not always observable. In contrast, we do not rely on the pallor zone extraction thus on more general basis. We introduce two generic parameters to measure the goodness of working areas, one for the degree of overlap, and the other for the spatial occupancy. We also propose a cascading classification network for the classification of different areas. The effectiveness of our method has been tested on over 150 labeled images acquired from three malaria-infected Giemsa-stained blood smears using an oil immersion 100x objective.",

keywords = "Central pallor zone, Classification, Distribution, Equivalent diameter, Generic features, Occupancy, Overlap, Peripheral blood smears, Working area",

author = "W. Xiong and Lim, {J. H.} and Ong, {S. H.} and Tung, {N. N.} and J. Liu and D. Racoceanu and K. Tan and A. Chong and K. Foong",

year = "2008",

doi = "10.1109/iembs.2008.4650104",

language = "English",

isbn = "9781424418152",

series = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - {"}Personalized Healthcare through Technology{"}",

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pages = "4074--4077",

booktitle = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08",

address = "United States",

note = "30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 ; Conference date: 20-08-2008 Through 25-08-2008",

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Xiong, W, Lim, JH, Ong, SH, Tung, NN, Liu, J, Racoceanu, D, Tan, K, Chong, A & Foong, K 2008, Automatic working area classification in peripheral blood smears without cell central zone extraction. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4650104, Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology", IEEE Computer Society, pp. 4074-4077, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canada, 20/08/08. https://doi.org/10.1109/iembs.2008.4650104

Automatic working area classification in peripheral blood smears without cell central zone extraction. / Xiong, W.; Lim, J. H.; Ong, S. H. et al.
Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. p. 4074-4077 4650104 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Automatic working area classification in peripheral blood smears without cell central zone extraction

AU - Xiong, W.

AU - Lim, J. H.

AU - Ong, S. H.

AU - Tung, N. N.

AU - Liu, J.

AU - Racoceanu, D.

AU - Tan, K.

AU - Chong, A.

AU - Foong, K.

PY - 2008

Y1 - 2008

N2 - In this paper we study automatic classification of working areas in peripheral blood smears using image analysis and recognition methods. Such automatic classification can provide objective and reproducible quality control for the evaluation of smears and smear maker devices. However, research in this filed has drawn little attention. Existing methods either can not differentiate correctly different cell distributions or rely on the extraction of the central pallor zones in cells for counting, which are not always observable. In contrast, we do not rely on the pallor zone extraction thus on more general basis. We introduce two generic parameters to measure the goodness of working areas, one for the degree of overlap, and the other for the spatial occupancy. We also propose a cascading classification network for the classification of different areas. The effectiveness of our method has been tested on over 150 labeled images acquired from three malaria-infected Giemsa-stained blood smears using an oil immersion 100x objective.

AB - In this paper we study automatic classification of working areas in peripheral blood smears using image analysis and recognition methods. Such automatic classification can provide objective and reproducible quality control for the evaluation of smears and smear maker devices. However, research in this filed has drawn little attention. Existing methods either can not differentiate correctly different cell distributions or rely on the extraction of the central pallor zones in cells for counting, which are not always observable. In contrast, we do not rely on the pallor zone extraction thus on more general basis. We introduce two generic parameters to measure the goodness of working areas, one for the degree of overlap, and the other for the spatial occupancy. We also propose a cascading classification network for the classification of different areas. The effectiveness of our method has been tested on over 150 labeled images acquired from three malaria-infected Giemsa-stained blood smears using an oil immersion 100x objective.

KW - Central pallor zone

KW - Classification

KW - Distribution

KW - Equivalent diameter

KW - Generic features

KW - Occupancy

KW - Overlap

KW - Peripheral blood smears

KW - Working area

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DO - 10.1109/iembs.2008.4650104

M3 - Conference contribution

C2 - 19163607

AN - SCOPUS:61849151394

SN - 9781424418152

T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

SP - 4074

EP - 4077

BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

PB - IEEE Computer Society

T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

Y2 - 20 August 2008 through 25 August 2008

ER -

Xiong W, Lim JH, Ong SH, Tung NN, Liu J, Racoceanu D et al. Automatic working area classification in peripheral blood smears without cell central zone extraction. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society. 2008. p. 4074-4077. 4650104. (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"). doi: 10.1109/iembs.2008.4650104

Automatic working area classification in peripheral blood smears without cell central zone extraction

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

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