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The software is able to recognize bones and organs on three-dimensional grayscale images, and segment them

Self-learning algorithms developed by researchers at the Technical University of Munich in Germany can help analyze medical image data.

Credit: Astrid Eckert/TUM

Researchers at the Technical University of Munich (TUM) in Germany have developed self-learning algorithms that can help analyze medical image data.

The AIMOS (Artificial Intelligence-based Mouse Organ Segmentation) software is centered on the use of artificial neural networks to recognize patterns and find solutions on their own.

The algorithms were trained using images of mice, with the goal of enabling the program to evaluate three-dimensional (3D) full-body scans to display the exact position and shape of specific organs.

Said TUM's Bjoern Menze, "The result shows that self-learning algorithms are not only faster at analyzing biological image data than humans, but also more accurate.”

From Technical University of Munich (Germany)
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