Artificial intelligence models are getting better at detecting brain tumors in images from MRIs. More than 150 types of brain tumors have been identified to date; and while not all of them are brain cancer, they can still be dangerous because of their locations. Benign brain tumors located in vital areas of the brain can be life-threatening.
On rare occasions, a benign tumor can become malignant, according to John Hopkins Medicine . Nearly 19,000 people were projected to die from brain and other nervous system cancers this year. About the same amount were estimated to die from brain and spinal cord tumors last year, according to the American Cancer Society .
Now, scientists have trained convolutional neural networks – also known as machine learning algorithms, a type of AI – to identify which MRI images showed healthy brains and which had been affected by cancer . In addition, the models could determine the area affected by cancer and what type of cancer it looked like. They found that the AI networks scored highly at detecting normal brain images and distinguishing the difference between cancerous and healthy brains.
The first could detect brain cancer with an average accuracy rate of nearly 86 percent. The second had a rate of more than 83 percent. Researchers used public domain MRI imaging data to train the models.
Their findings were published Tuesday in a new paper in the journal Biology Methods and Protocols . To improve the networks’ abilities to detect tumors, t.
