A computer tool that finds brain tumors on MRI scans
Original title: Enhanced MRI brain tumor segmentation with DNet and hybrid dice-weighted cross-entropy loss.
How far along is this research?
- Lab cells
- Animals
- Review
- Tested in people
This was done on cells in a lab, not in people. It is a very early step.
This was only tested on stored scan images by computer, not with patients in a clinic.
The short version
Researchers built software that can outline brain tumors on MRI pictures on its own.
What was studied. Researchers made a computer program called DNet. They tested it on 1664 MRI pictures that showed three kinds of tumors: glioma: A tumor that starts in the glial cells, the support cells of the brain and spinal cord. Gliomas are graded 1 to 4 by how fast they tend to grow. See the glossary, meningioma, and pituitary tumors.
What they found. The program found and outlined tumors in the pictures. It reached 99.6% accuracy on the set of pictures with three tumor types. It did better than the older program it was based on. It also worked about the same on a separate set of pictures.
What this means, and what it doesn't
What it could mean: Tools like this may one day help doctors spot and measure a tumor on a scan faster. It could support the doctor reading your MRI. It would not replace them.
What it doesn't mean: This is not a treatment. It is not a cure and it does not tell you anything about how a person will do. The work was done on stored MRI pictures, not with patients in a clinic. The researchers say it still needs testing on many more scans from many different hospitals before it could be used in real care.
Source: PubMed, July 13, 2026 · Read the original
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