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A new artificial intelligence method called MetaSeg is changing how doctors analyze medical images. Unlike traditional AI models, which require large amounts of data and computing power, MetaSeg is designed to work efficiently while maintaining high accuracy. This makes it easier for hospitals and clinics to adopt AI technology without needing expensive resources.

MetaSeg uses a technique known as implicit neural representations, which represents images as continuous mathematical functions instead of relying on pixel-based data. This allows the AI to process medical images faster and with fewer resources, while still producing detailed and accurate results.

One of the major benefits of MetaSeg is its versatility. It can handle both 2D and 3D medical scans, including complex images like brain MRIs. Despite using about 90% fewer computing parameters than traditional models, it performs at a similar level of accuracy.

The research behind MetaSeg was recognized at the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) conference, where it received the Best Paper Award. Experts say this development could make AI-driven medical imaging tools more accessible to healthcare providers worldwide.

With this innovation, doctors may soon be able to diagnose conditions more quickly and accurately, marking a significant step forward in medical technology.