3Deep Supervised Learning on Radiological Images to Classify Bone Fractures: A Novel Approach
Abstract
Several researchers in recent years have proposed several ways to classify bone fractures. Despite this, there is no well-defined system for categorizing the many fractures that might occur in a human body. The use of X-rays to identify bone fractures is just one such application, yet this can also occur with smaller fissures. This highlights the need to quickly diagnose a patient with a fracture and start treatment. Because of this, it is crucial to design efficient and intelligent systems. Still it is a regular emergency when a fracture is not properly diagnosed. Patients’ access to care and treatment is limited and often delayed as a result. The potential use of deep learning (DL) and other forms of artificial intelligence to aid radiologists in the identification of bone fractures is now receiving a great deal of attention. The analysis of medical images is a promising area for the use of DL. In this chapter, we investigate how deep supervised learning can be used to analyze X-ray pictures and categorize the many types of bone fractures.
Keywords: Deep supervised learning, radiological images, bone fracture, bone classification, X-ray, deep learning
3.1 Introduction
There has been widespread application of image processing methods across the medical sector. Applications of wavelet transform in medical image processing are discussed by researchers [1]. The ability to ...
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