Automatic Classification of white blood cell images by neural network
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- Yamasaki Takayuki
- Himeji Institute of Technology
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- Isokawa Teijiro
- Himeji Institute of Technology
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- Matsui Nobuyuki
- Himeji Institute of Technology
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- Okamoto Minoru
- Sysmex Corporation
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- Koeda Noriaki
- Sysmex Corporation
Bibliographic Information
- Other Title
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- ニューラルネットワークを用いた白血球画像の自動分類
Abstract
Measuring the proportion of white blood cells is effective for estimating the source of the disease or for observing the progress of the disease. However, it takes long time by hand and requires the specialized knowledge, thereby the method for automatically classifying cells is needed. We propose a classification of white blood cells based on neural network in this paper. Nine parameters of area, shape and color information are extracted from a microscopic image of cells. These parameters are used as inputs for neural network classifier. Experimental results show that our proposed method can classify cells with high accuracy.
Journal
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- Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers
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Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers SCI03 (0), 6023-6023, 2003
The Institute of Systems, Control and Information Engineers
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Details 詳細情報について
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- CRID
- 1390001205621720704
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- NII Article ID
- 130006981788
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed