Journal article Open Access

FRACTURE DETECTION: A QUICK SURVEY OF DEEP LEARNING MODELS

Irfan Khatik; Nilesh Mahajan

Bone fracture is a common problem now days due to road accidents, unhealthy lifestyle and many other causes. Bone is an integral part of the human body to move and shape it. A small fracture in the bone affects normal functioning of the bone and in result affects the free movement of the person. Fracture is common in human bones. There are a lot of techniques to find out fractures. Normal technique is time consuming and expert dependent. It also has a high error rate. In case of suspected fractures, the patient visits emergency units and X-ray is the primary tool to assess the patient for fracture. X-ray detection is economical mean for fracture. Missing a fracture has severe consequences on patients. Automated detection of bone fracture is a hot research topic today. There are a lot of papers on automated fracture detection. This paper focuses on deep learning methods for bone fracture detection. Deep learning is a Neural Network based method where more hidden layers are used with the artificial neural network. Objective is to provide an overview of deep learning methods on bone fracture to help researchers to further explore the idea. This paper also discuss about the popular python APIs in deep learning

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