Abstract: This research investigates the application of Convolutional Neural Networks (CNNs) in identifying and managing brain tumors using MRI scans, emphasizing the importance of early and precise detection for successful treatment and enhanced patient prognosis. Conventional imaging techniques often fall short in providing reliable tumor detection, highlighting the necessity for more advanced solutions. By utilizing CNNs, this study focuses on building an accurate system capable of detecting and categorizing tumors based on distinct features, thereby improving diagnostic reliability while enabling customized treatment plans for individual patients. The methodology incorporates key factors like tumor type, size, and position to refine treatment approaches, along with ongoing monitoring to adapt therapies using real-time updates, ensuring optimal care. The project aims to make meaningful advancements in neuro-oncology by enhancing early diagnosis, facilitating tailored treatment plans, and elevating patient outcomes through cutting-edge techniques and sophisticated neural network applications.
Keywords: Brain tumor detection, MRI scans, Machine learning, Image preprocessing Convolutional Neural Networks, Logistic Regression, Personalized treatment plans, Neuro-oncology.
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DOI:
10.17148/IJARCCE.2025.14441
