Brain tumors are among the deadliest diseases in the world. Magnetic Resonance Imaging (MRI) is one of the most effective ways to detect brain tumors. Accurate detection of brain tumors based on MRI scans is critical, as it can potentially save many lives and facilitate better decision-making at the early stages of the disease. Within our paper, four different types of MRI-based images have been collected from the database: glioma tumor, no tumor, pituitary tumor, and meningioma tumor. Our study focuses on making predictions for brain tumor classification. Five models, including four pre-trained models (MobileNet, EfficientNet-B0, ResNet-18, and VGG16) and one new model, MobileNet-BT, have been proposed for this study.

翻译：脑肿瘤是全球最致命的疾病之一。磁共振成像（MRI）是检测脑肿瘤最有效的方法之一。基于MRI扫描的脑肿瘤精准检测至关重要，因其可能挽救众多生命并在疾病早期阶段促进更优决策。本文从数据库中收集了四种不同类型的基于MRI的图像：胶质瘤、无肿瘤、垂体瘤和脑膜瘤。我们的研究聚焦于脑肿瘤分类预测。为此研究提出了五种模型，包括四个预训练模型（MobileNet、EfficientNet-B0、ResNet-18和VGG16）和一个新模型MobileNet-BT。