Classification of brain tumor types by deep learning with convolutional neural network on magnetic resonance images using a developed web-based interface

Ucuzal H.Yasar S.Colak C.2024-08-042024-08-0420199781728137896https://doi.org/10.1109/ISMSIT.2019.8932761https://hdl.handle.net/11616/922513rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 -- 11 October 2019 through 13 October 2019 -- 156063Automated machine learning (AutoML) algorithms developed using deep learning algorithms have been the focus of interest in many studies recently. This study aims to develop a free web-based software based on deep learning that can be utilized in the diagnosis and detection of brain tumors (Glioma/Meningioma/Pituitary) on T1-weighted magnetic resonance imaging. The Keras library, which is used in Python programming language, is utilized in the construction of the deep learning algorithm in this software. The experimental results show that this software can be used for the detection and diagnosis of three types of brain tumors. This developed web-based software can be publicly available at http://biostatapps.inonu.edu.tr/BTSY/ in both English and Turkish. © 2019 IEEE.eninfo:eu-repo/semantics/closedAccessbrain tumorsclassification taskdeep-learning strategyKerasmagnetic resonance imagingClassification of brain tumor types by deep learning with convolutional neural network on magnetic resonance images using a developed web-based interfaceConference Object10.1109/ISMSIT.2019.89327612-s2.0-85078043017N/A