Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model

Recently, Internet of Medical Things (IoMT) has gained considerable attention to provide improved healthcare services patients. Since earlier diagnosis brain tumor (BT) using medical imaging becomes an essential task, automated IoMT and cloud enabled BT model can be devised recent deep learning models. With this motivation, paper introduces a novel model, named IoMTC-HDBT. The IoMTC-HDBT comprises the data acquisition process by use devices which captures magnetic resonance (MRI) images transmit them server. Besides, adaptive window filtering (AWF) based image preprocessing is used remove noise. In addition, server executes disease includes sparrow search algorithm (SSA) with GoogleNet (SSA-GN) model. applies functional link neural network (FLNN), ability detect classify MRI as normal or abnormal. It finds useful generate reports instantly for patients located in remote areas. validation takes place against BRATS2015 Challenge dataset experimental analysis carried out interms sensitivity, accuracy, specificity. experimentation outcome pointed betterment proposed accuracy 0.984.