Brain Tumor Detection and Classification

Brain tumors are among the most dangerous and heterogeneous cancers, and accurately identifying their type and grade from MRI scans is critical for choosing the right treatment. Doing this by hand is time-consuming and subject to variability between clinicians, so researchers have turned to deep learning methods — particularly convolutional neural networks — to automate the detection, segmentation, and classification of tumors directly from imaging data. These models learn to distinguish subtle patterns in tissue appearance that correlate with tumor biology, often matching or exceeding expert performance on benchmark datasets. Active challenges include making these systems reliable across different MRI scanners and patient populations, and building models that can explain their decisions in ways clinicians can trust and act on.

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Keywords

MRIBrain TumorClassificationDeep LearningConvolutional Neural NetworkFeature Extraction