روح اله مهدوي

The emergence of deep learning has revolutionized medical diagnosis, especially in the field of brain tumor diagnosis using magnetic resonance imaging (MRI). This thesis examines the application of deep learning techniques in the automatic diagnosis of brain tumors using medical data; Magnetic resonance imaging (MRI) addresses and provides a comprehensive exploration of the integration between advanced computational models, particularly convolutional neural networks (CNNs), and the complexities of MRI for early brain tumor detection. Chapter 1 provides an overview of the historical development of medical imaging, emphasizing the pivotal role of MRI in modern diagnostics and laying the groundwork for further research. Chapter 2 reviews the relevant literature and sheds light on the prospects for brain tumor detection methods. It articulates research hypotheses and questions and creates a framework for empirical exploration. This chapter extends its reach to practical barriers and challenges to clinical adoption, and grounds subsequent research in real-world considerations. Chapter 3 explains the research methodology and clarifies the complexities of the research design and emphasizes the importance of the quality and diversity of the data set. Chapter 4 appears as the focus of the empirical findings. A detailed comparison pits the developed CNN model against pre-trained models such as ResNet-50, VGG16 and Inception V3. The results, including the training steps, provide a comprehensive eva‎luation of the model's effectiveness and validation. Chapter 5 serves as a body of knowledge and provides a summary of the research design. This holistic exploration contributes to the evolving landscape of medical diagnosis and demonstrates the potential of deep learning models in early brain tumor diagnosis. Finally, it ends by summarizing the findings, discussing their implications and suggesting avenues for future research in this vital field. This research is a promising step towards increasing the early detection of brain tumors, which ultimately contributes to more effective medical interventions and improved patient care.

تشخيص تومور مغزي , يادگيري عميق , شبكه‌ عصبي پيچشي

brain tumor diagnosis , Deep Learning , Convolutional Neural Network

Roohollah Mahdavi

Dr. Javad Vahidi