A survey of fracture detection techniques in bone X-ray images
A survey of fracture detection techniques in bone X-ray images
复制标题
DOI：
10.1007/s10462-019-09799-0
复制
发表时间：
2020-08-01
影响因子：
12
通讯作者：
Singh, Thipendra P.
中科院分区：
文献类型：
--
作者：
Joshi, Deepa;Singh, Thipendra P.
放射科医生通过肉眼检查x射线样本来诊断各种骨骼中是否存在骨折。x线片的解读是一个耗时且紧张的过程，需要手工检查骨折。此外，在医疗资源不足的地区，临床医生的短缺，在繁忙的临床环境中缺乏放射科专家，或者由于工作量大而导致的疲劳，都可能导致假检率和骨折的恢复不良。一项全面的研究在这里传授骨折诊断的目的是协助研究人员开发模型，自动检测骨折在人的骨头。这篇论文分五页发表。首先，我们讨论了数据准备阶段。其次，我们介绍了用于裂缝检测的各种图像处理技术。第三，我们分析了传统的和基于深度学习的骨折诊断技术。第四，对现有技术进行比较分析。第五，讨论了裂缝检测研究面临的不同问题和挑战。
Radiologists interprets X-ray samples by visually inspecting them to diagnose the presence of fractures in various bones. Interpretation of radiographs is a time-consuming and intense process involving manual examination of fractures. In addition, clinician's shortage in medically under-resourced areas, unavailability of expert radiologists in busy clinical settings or fatigue caused due to demanding workloads could lead to false detection rate and poor recovery of the fractures. A comprehensive study is imparted here covering fracture diagnosis with the aim to assist investigators in developing models that automatically detects fracture in human bones. The paper is presented in five folds. Firstly, we discuss data preparation stage. Second, we present various image-processing techniques used for fracture detection. Third, we analyze conventional and deep learning based techniques for diagnosing bone fractures. Fourth, we make comparative analysis of existing techniques. Fifth, we discuss different issues and challenges faced by researches while dealing with fracture detection.