How machines learn to find and track brain tumors on MRI

Brain tumors come in different shapes and that makes them hard to treat, and hard to spot on scans. Scientists looked at seven years of a big contest called BraTS to see which methods work best at finding tumor parts, following their growth over time, and guessing how long patients might live. They used many tools that learn from images to mark the tumor edges on MRI scans. Good marks can show subtle change in a tumor, so doctors might see growth sooner than before, and it may help with decisions. The study also asks which tool is best for each job, but the answer changes because the data grew and changed every year. This means one method may win once, but not always. With better segmentation and smart machine learning, we can get clearer pictures of tumor behavior, and make better survival prediction for patients after surgery. It’s not perfect yet, but the work is moving fast and gives hope for smarter, faster care for people with a brain tumor.

Read article comprehensive review in Paperium.net: Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation,Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

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