Abstract
The purpose of this paper is to build an automatic system for extraction and classification of brain tumor in medical images. The system is able to process Resonance Magnetic Images (MRI) most quickly with a high detection rates. Indeed, based on Convolutional Neural Network (CNN) method for classification and a thresholding algorithm for image segmentation, the system has been developed. Moreover, many experiments were conducted to evaluate the performance of our approach using different optimizers with a huge dataset of MRI brain images. Results showed that the Root Mean Square Propagation (RMSprop) optimizer converges faster with a highest accuracy comparing to other optimizers.
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El Boustani, A., Aatila, M., El Bachari, E., El Oirrak, A. (2020). MRI Brain Images Classification Using Convolutional Neural Networks. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1105. Springer, Cham. https://doi.org/10.1007/978-3-030-36674-2_32
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DOI: https://doi.org/10.1007/978-3-030-36674-2_32
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