N. bone fracture frame
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Date
2025
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Journal ISSN
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Publisher
UMT.Lahore
Abstract
Bone fractures are a significant medical challenge, requiring accurate and timely diagnosis to ensure effective treatment. Traditional methods of fracture detection, which rely heavily on manual analysis, are often prone to human error and can lead to delayed treatments, adversely affecting patient recovery. To address these challenges, this project introduces "Bone racture Frame," an AI-powered desktop application designed to detect bone fractures in X-ray images with high accuracy and efficiency. The system utilizes advanced deep learning models to analyze medical images, identify anomalies, and generate actionable insights for healthcare professionals. Key features of the application include user registration, image upload functionality, real-time fracture detection, result visualization, and downloadable reports. Designed with a focus on user- friendliness, the application ensures accessibility for medical practitioners of varying technical expertise. By automating the fracture detection process, the application significantly reduces diagnostic errors, alleviates the workload on medical professionals, and enables faster treatment planning. This project highlights the transformative potential of integrating artificial intelligence into medical imaging, offering a scalable and adaptable solution to enhance healthcare delivery and improve patient outcomes. "Bone Fracture Frame" serves as a foundation for future innovations in AI-driven diagnostics, paving the way for broader applications in the medical field.