| Abstract |
Bone fractures are a common health issue that can occur due to accidents or conditions like bone cancer. Fractures can happen in any bone in the human body, including the wrist, hip, heel, ankle, rib, leg, chest, and more. However, X-ray images of bone fractures sometimes lack the detailed information necessary for proper diagnosis. This paper explores image processing techniques for bone fracture detection. It aims to assist healthcare practitioners by reviewing various methods of bone fracture identification through efficient image processing, while also suggesting new approaches to improve fracture detection accuracy. The strategies are presented in a simple, easy-to-understand manner. This paper is the first of its kind to examine bone fracture detection methods across different imaging modalities. |
| Keywords |
Bone fracture, machine learning, image processing, X-ray, fracture detection, healthcare, diagnostic techniques, bone cancer, medical imaging, fracture identification |
