基于人工智能技术的骨折检测

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Preksha Pareek, Ruchi Jayaswal, S. Patil, Kishan Vyas
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引用次数: 0

摘要

医学领域本身就是一个复杂的术语,其中诊断是最重要的。如果在适当的时间内及时做出正确的诊断,那么就可以及时开始治疗,这种治疗将有利于治愈患者。有许多不同的技术可用于在给定的图像中发现异常,但我们将回顾其中一些最近发展起来的技术,并将比较每种技术的结果。本文最后对裂缝及其类型进行了详细的研究。我们将考虑的数据集是MURA数据集。并对该领域的进一步研究进行了探讨,以帮助研究者探索该领域的新维度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Bone Fracture Detection using AI-Based Techniques
The medical field in itself is a complex term where the diagnosis is of the most importance. If there is a correct diagnosis made on time in the appropriate time duration then the treatment can be started in a timely manner and this treatment will be beneficial in curing the patient. There are many different techniques that are available to find the abnormalities in an image given but we will review some of them which are most recently developed and will compare the results of each of them. A detailed study is done at the end of this paper which gives insights into fractures and their types. The dataset which we would consider is the MURA dataset. Discussion about further research in this area is also done to help researchers in exploring new dimensions in this field.  
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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