Identification of Osteoporotic Changes of Vertebral Bodies on Computed Tomography Images Based on the Analysis of Groups of Textural Features

M. Ya. Lyakin, N. Yu. Ilyasova, E. N. Alekhin, N. S. Demin
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Abstract

The study presented in this paper is devoted to the development of technology for detecting osteoporotic changes in vertebral bodies according to computed tomography data based on the analysis of groups of textural features. This technology will be of interest to radiologists when assessing the structure of vertebral bodies in patients with osteoporosis, and especially in patients with malignant neoplasms, in which the disease proceeds with a decrease in bone mineral density. Automation of the analysis process will significantly reduce the time spent by a radiologist on the evaluation of vertebral bodies, including when evaluating the effectiveness of osteoporosis treatment. During the development process, the most informative group of signs was identified, which allows achieving high accuracy in detecting signs of osteoporotic changes in the vertebral bodies in 94.5%.

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基于纹理特征群分析的计算机断层图像中椎体骨质疏松变化的识别
本文的研究是基于纹理特征组的分析,开发基于计算机断层扫描数据检测椎体骨质疏松变化的技术。当放射科医生评估骨质疏松症患者的椎体结构时,特别是在恶性肿瘤患者中,这项技术将引起他们的兴趣,因为恶性肿瘤患者的疾病发展伴随着骨矿物质密度的降低。分析过程的自动化将大大减少放射科医生在评估椎体上花费的时间,包括评估骨质疏松症治疗的有效性。在开发过程中,确定了最具信息量的体征组,这使得在94.5%的椎体中检测骨质疏松症改变的迹象具有很高的准确性。
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CiteScore
1.50
自引率
11.10%
发文量
25
期刊介绍: The journal covers a wide range of issues in information optics such as optical memory, mechanisms for optical data recording and processing, photosensitive materials, optical, optoelectronic and holographic nanostructures, and many other related topics. Papers on memory systems using holographic and biological structures and concepts of brain operation are also included. The journal pays particular attention to research in the field of neural net systems that may lead to a new generation of computional technologies by endowing them with intelligence.
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