A Review on Techniques and Approaches of Deep Learning in Bone Fracture Detection

In this study, the exploration of the complexities of the skeletal system in humans and look at which parts of the body are more prone to fractures due to things like tiredness, accidents, age-related brittleness, and traumas. This research looks for potential weak spots in the bone structure using cutting-edge medical imagingMedical imaging methods like X-rays, CT scans, MRI, as well as ultrasound on occasion. The use of artificial intelligence—more especially deep learning and machine learningDeep learning and machine learning—in conjunction with conventional image processing approaches to identify bone fractures is what makes this investigation so interesting. Through careful examination and evaluation of these state-of-the-art techniques, the article guides readers through several pre-processing processes. While dealing with the difficulties of bone fracture diagnosisBone fracture diagnosis in various organs, it also assesses the approaches utilising standard metrics. Additionally, the approaches that researchers have used for localization, object recognitionObject recognition, and segmentation in order to achieve improved precision and accuracy in fracture diagnosis are covered. Here there is a potential future of healthcare equipment that combines medical knowledge with AI; it has the potential to revolutionise bone injury diagnostics.