초록

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Abstract ▼ AI-Helper

In this paper, the structure of image retrieval system for pulmonary computed tomography nodule by using texture feature extraction is proposed and realized. This system is designed to be easy to add various texture feature extraction methods, and co-occurrence matrices, Gabor filters, and Markov ra...

In this paper, the structure of image retrieval system for pulmonary computed tomography nodule by using texture feature extraction is proposed and realized. This system is designed to be easy to add various texture feature extraction methods, and co-occurrence matrices, Gabor filters, and Markov random fields apply to texture feature extractors. After feature extraction of all pulmonary nodule images, the similar nodule images are found by calculating and comparing similarities between two nodule images. Besides, in order to reduce the time to compute texture feature at everytime when a user operates the system, we also propose function to save and load texture feature database of pulmonary nodule images. The proposed system is realized using C# language, and it is tested with Lung Image Database Consortium from U.S. National Cancer Institute.

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