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MRI-Based prototype for early detection of muscular knee injuries with U-Net
0
Zitationen
3
Autoren
2025
Jahr
Abstract
This study presents the development and initial validation of an Artificial Intelligence [AI] based prototype for the early detection of knee muscle injuries using Magnetic Resonance Imaging [MRI]. The system leverages a U-Net architecture for lesion segmentation and classification, achieving performance above 90% in preliminary tests while reducing analysis time to less than five minutes per case. The development methodology included data preprocessing, model training and performance evaluation, as well as the implementation of a web interface [React for the frontend and Python for the backend]. The solution is designed for deployment in clinical settings, aiming to streamline diagnosis, support medical decision-making, and enhance patient care, particularly in resource-limited contexts
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