https://www.taxtmi.com/news?id=59007 An open-source neural network automates segmentation of infant MRI scans to distinguish gray and white matter with over 90% internal accuracy, serving as a decision-support tool for suspected cerebral palsy in infants under 12 months. The project created new annotated data with medical collaborators, validated a dedicated architecture, and released code on GitHub for integration into medical IT systems to accelerate diagnosis, quantify gray-white matter ratios, and increase radiology throughput while supporting less-experienced clinicians. en-us Thu, 16 Oct 2025 12:46:03 +0530 Thu, 16 Oct 2025 12:46:03 +0530 TaxTMI RSS Generator https://www.taxtmi.com/news?id=59007 An open-source neural network automates segmentation of infant MRI scans to distinguish gray and white matter with over 90% internal accuracy, serving as a decision-support tool for suspected cerebral palsy in infants under 12 months. The project created new annotated data with medical collaborators, validated a dedicated architecture, and released code on GitHub for integration into medical IT systems to accelerate diagnosis, quantify gray-white matter ratios, and increase radiology throughput while supporting less-experienced clinicians. News - Thu, 16 Oct 2025 12:46:03 +0530 https://www.taxtmi.com/news?id=59007