Distributed brain tumor diagnosis using a federated learning environment

In the last few years, a very huge development has occurred in medical techniques using artificial intelligence tools, especially diagnosis field. One of essential things is brain tumor (BT) detection and diagnosis. This kind disease needs an expert physician to decide on treatment or surgical operation based magnetic resonance imaging (MRI) images; therefore, researchers focus such images analysis understanding help specialist make decision. this work, new environment been investigated deep learning method distributed federated (FL) algorithm. The proposed model evaluated cross-validation two different standard datasets, BT-small-2c, BT-large-3c. achieved classification accuracy was 0.82 0.96 consecutively. provides active effective system for assessing BT with high reliability accurate clinical findings.