A Novel Architecture for Semantic Segmentation of Brain Tumors Using Multi-Modal MRI Images

The human brain is affected by about 120 different forms of brain tumors. AI-based intervention for tumor identification and surgical pre-assessment is on the verge of becoming a necessity rather than a luxury as we approach the era of artificial intelligence (AI) in healthcare. Brain tumors can be characterized in depth using techniques like volumetric analysis to track their growth and aid in pre-surgical planning.

The characterization of defined tumors can be directly used for the prognosis of life expectancy, in addition to surgical uses. The segmentation of brain tumors is at the forefront of all such applications. Primary and secondary tumors are the two forms of brain tumors. Primary brain cancers arise from brain cells, whereas secondary tumors spread from other organs to the brain.

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