Abstract
This paper proposed an automatic method for the classification of meningioma subtypes based on the unsupervised color segmentation method and feature selection scheme. Firstly, a color segmentation method is utilized to segment the cell nuclei. Then the set of shape feature vectors which are calculated from the segmentation results are constructed. Finally, a k-nearest neighbour classifier (kNN) is used to classify the meningioma subtypes. Experiment shows that the classification accuracy of 85 % is achieved by using a leave-one-out cross validation approach on 80 meningioma images.
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References
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© 2014 Springer Science+Business Media Dordrecht
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Zeng, Z., Tong, Z., Han, Z., Zhang, Y., Zwiggelaar, R. (2014). The Classification of Meningioma Subtypes Based on the Color Segmentation and Shape Features. In: Li, S., Jin, Q., Jiang, X., Park, J. (eds) Frontier and Future Development of Information Technology in Medicine and Education. Lecture Notes in Electrical Engineering, vol 269. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7618-0_335
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DOI: https://doi.org/10.1007/978-94-007-7618-0_335
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