A Comprehensive Analysis of AI Applications in Bone Fracture Detection: A Systematic Review

Abstract

The human body relies significantly on bones, enabling movement and structural support. Fractures within bones are frequently observed, prompting doctors to utilize X-ray imaging for accurate diagnosis. However, manually detecting fractures is both time-consuming and prone to a higher chance of errors. In the realm of medical diagnostics, advancements in image processing techniques play a pivotal role in enhancing the accuracy and efficiency of fracture detection in X-ray images. Due to the recent advancement of artificial intelligent and increased the power of computational hardware, researchers is working on various machine learning and deep learning algorithms which can assists radiology and orthopedics in their diagnosis and reduce the possibility of misdiagnosis. This paper presents the progress in deep learning specifically related to bone fracture and addressing the challenge of precise localization and characterization.

Ähnliche Arbeiten