Automated Segmentation of Brain Tumor MRI Images Using Machine Learning

The field of medical imaging has been revolutionized by intelligent systems, especially those powered by machine learning and artificial intelligence (AI). Among various applications, brain tumor detection and classification stand out due to their critical impact on patient health outcomes. Brain tumors—whether benign or malignant—are among the most serious neurological conditions and often require prompt and accurate diagnosis. Traditionally, identifying brain tumors through imaging has been a manual and expertise-driven process, but with the integration of AI, especially deep learning, the accuracy and speed of diagnosis have improved significantly. This overview explores how machine learning contributes to brain tumor analysis, from the collection and pre-processing of MRI data to model training and classification. Key challenges such as data quality, model explainability, and tumor variability are also addressed, alongside modern advancements in deep learning models that continue to evolve in precision and clinical applicability.