Classification of Brain Tumours Types Based On MRI Images Using Mobilenet
Tsamara Hanifa Arfan, Mardhiya Hayaty, Arifiyanto Hadinegoro
Abstract
MRI can detect soft tissue that contains a brain tumour. Imaging produced by MRI in brain tumours can not be analyzed easily if done manually. Results in a longer time required. Deep learning is part of artificial intelligence that can analyze data automatically. Mobilenet is one of the methods in deep learning that functions to perform the segmentation process of medical images. Mobile Network is a CNN model with high accuracy and less computation. Therefore, this study proposes the use of Mobile Network architecture to classify brain tumour types. Mobile Network there are various categories. This study finds evidence that the application of Mobile networks improves overall accuracy. The best result from the Mobile Network category was MobileNet V2 140×224, which achieved an accuracy test of 94%.