Bone Fracture Classification using Transfer Learning

2024/06/22 by Shyam Gupta, Gupta, Shyam, Dhanisha Sharma +1
Engineering · Medicine · #Medical Imaging and Analysis #COVID-19 diagnosis using AI

paper · pdf · doi:10.48550/arxiv.2406.15958

Abstract

The manual examination of X-ray images for fractures is a time-consuming process that is prone to human error. In this work, we introduce a robust yet simple training loop for the classification of fractures, which significantly outperforms existing methods. Our method achieves superior performance in less than ten epochs and utilizes the latest dataset to deliver the best-performing model for this task. We emphasize the importance of training deep learning models responsibly and efficiently, as well as the critical role of selecting high-quality datasets.

Related

• A novel approach towards the classification of Bone Fracture from Musculoskeletal Radiography images using Attention Based Transfer Learning
• A Supervised Approach to Musculoskeletal Imaging Fracture Detection and Classification Using Deep Learning Algorithms
• Fracture Detection In X-rays Using Custom Convolutional Neural Network (CNN) And Transfer Learning Models
• Pre-trained Under Noise: A Framework for Robust Bone Fracture Detection in Medical Imaging
• Weakly-Supervised Localization and Classification of Proximal Femur Fractures