한국정보처리학회논문지 (The Transactions of the Korea Information Processing Society)
- 제6권10호
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- Pages.2707-2715
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- 1999
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- 1226-9190(pISSN)
말초혈액영상에서 신경망 모델을 이용한 적혈구의 형태학적 변이 분류
Morphological Variation Classification of Red Blood Cells using Neural Network Model in the Peripheral Blood Images
- Kim, Gyeong-Su ;
- Kim, Pan-Gu (Dept.of Computer Engineering, Chosun University)
- 발행 : 1999.10.01
초록
Recently, there have been researches to automate processing and analysing images in the medical field using image processing technique, a fast communication network, and high performance hardware. In this paper, we propose a system to be able to analyze morphological abnormality of red-blood cells for peripheral blood image using image processing techniques. To do this, we segment red-blood cells in the blood image acquired from microscope with CCD camera and then extract UNL fourier features to classify them into 15 classes. We reduce the number of multi-variate features using PCA to construct a more efficient classifier. Our system has the best performance in recognition rate, compared with two other algorithms, LVQ3 and k-NN. So, we show that it can be applied to a pathological guided system.
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