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基于三维重建的股骨髋臼撞击症(FAI)的有限元分析

Finite Element Analysis of Femoral-Acetabular Impingement (FAI) Based on Three-Dimensional Reconstruction.

机构信息

College of Architectural Engineering, Kunming University of Science and Technology, Kunming 650500, Yunnan, China.

Department of Orthopedics, Second Affiliated Hospital of Kunming Medical University, Kunming 651000, Yunnan, China.

出版信息

J Healthc Eng. 2022 Feb 27;2022:2937056. doi: 10.1155/2022/2937056. eCollection 2022.

Abstract

In order to solve the problem that people often have pain in the hip joint, it is more meaningful to study femoral-acetabular impingement syndrome in the future. This article aims to study the finite element analysis of femoral-acetabular impingement based on three-dimensional reconstruction. This paper proposes a selective image matching strategy. In the feature matching stage, all images are not matched in pairs, but the corresponding camera distance between the images is calculated initially, which has little effect on the number of features and greatly reduces the time of feature matching, thereby reducing the time cost of 3D reconstruction. In this experiment, a double-blind experiment was used to check the range of motion of all hip joints. Two senior radiologists read the obtained hip joint orthographic films to screen out the hip joint orthographic films that meet the requirements. Experimental data shows that although the initial matching points of the algorithm in this paper are lower than those of the traditional algorithm, the final number of matching points is higher than that of the traditional algorithm. When the final number of patches is fixed to 10000, the initial patch required by the algorithm in this paper is more than that required by the SAD algorithm, nearly 13%, but the total storage requirement is 56.4% of the SAD algorithm, which is a big improvement.

摘要

为了解决人们髋关节经常疼痛的问题,未来研究股骨髋臼撞击综合征更有意义。本文旨在基于三维重建研究股骨髋臼撞击的有限元分析。本文提出了一种选择性图像匹配策略。在特征匹配阶段,并不是所有图像都进行两两匹配,而是初步计算图像之间的对应相机距离,这对特征数量的影响很小,但大大减少了特征匹配的时间,从而减少了 3D 重建的时间成本。在该实验中,采用双盲实验检查所有髋关节的活动范围。两位资深放射科医生阅读获得的髋关节正位片,筛选出符合要求的髋关节正位片。实验数据表明,尽管本文算法的初始匹配点低于传统算法,但最终的匹配点数高于传统算法。当最终的斑块数固定为 10000 时,本文算法所需的初始斑块数比 SAD 算法多,将近 13%,但总存储需求仅为 SAD 算法的 56.4%,这是一个很大的改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/425c/8898867/0811476c408d/JHE2022-2937056.001.jpg

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