Percolation Images: Fractal Geometry Features for Brain Tumor Classification
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Resumo
Brain tumor detection is crucial for clinical diagnosis and efficient therapy. In this work, we propose a hybrid approach for brain tumor classification based on both fractal geometry features and deep learning. In our proposed framework, we adopt the concept of fractal geometry to generate a “percolation” image with the aim of highlighting important spatial properties in brain images. Then both the original and the percolation images are provided as input to a convolutional neural network to detect the tumor. Extensive experiments, carried out on a well-known benchmark dataset, indicate that using percolation images can help the system perform better.
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Brain tumors, Classification ensemble, Deep learning, Feature representations, Fractal features
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Inglês
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Advances in Neurobiology, v. 36, p. 557-570.
