First Affiliated Hospital of Xiamen University, Xiamen 361000, China.
J Healthc Eng. 2021 Nov 22;2021:4644392. doi: 10.1155/2021/4644392. eCollection 2021.
There are many kinds of orthopedic diseases with complex professional background, and it is easy to miss diagnosis and misdiagnosis. The computer-aided diagnosis system of orthopedic diseases based on the key technology of medical image processing can locate and display the lesion location area by visualization, measuring and providing disease diagnosis indexes. It is of great significance to assist orthopedic doctors to diagnose orthopedic diseases from the perspective of visual vision and quantitative indicators, which can improve the diagnosis rate and accuracy of orthopedic diseases, reduce the pain of patients, and shorten the treatment time of diseases. To solve the problem of possible spatial inconsistency of medical images of orthopedic diseases, we propose an image registration method based on volume feature point selection and Powell. Through the linear search strategy of golden section method and Powell algorithm optimization, the best spatial transformation parameters are found, which maximizes the normalized mutual information between images to be registered, thus ensuring the consistency of two-dimensional spatial positions. According to the proposed algorithm, a computer-aided diagnosis system of orthopedic diseases is developed and designed independently. The system consists of five modules, which can complete many functions such as medical image input and output, algorithm processing, and effect display. The experimental results show that the system developed in this paper has good results in cartilage tissue segmentation, bone and urate agglomeration segmentation, urate agglomeration artifact removal, two-dimensional and three-dimensional image registration, and visualization. The system can be applied to clinical gout and cartilage defect diagnosis and evaluation, providing sufficient basis to assist doctors in making diagnosis decisions.
骨科疾病种类繁多,专业背景复杂,容易出现漏诊和误诊。基于医学图像处理关键技术的骨科疾病计算机辅助诊断系统,可以通过可视化、测量和提供疾病诊断指标来定位和显示病变部位。从视觉和定量指标的角度辅助骨科医生诊断骨科疾病,对于提高骨科疾病的诊断率和准确率、减轻患者的痛苦、缩短疾病的治疗时间具有重要意义。为了解决骨科疾病医学图像可能存在的空间不一致性问题,提出了一种基于体积特征点选择和 Powell 的图像配准方法。通过黄金分割法的线性搜索策略和 Powell 算法优化,找到最佳的空间变换参数,最大化待配准图像之间的归一化互信息,从而保证二维空间位置的一致性。根据提出的算法,独立开发了一种骨科疾病计算机辅助诊断系统。该系统由五个模块组成,可以完成医学图像输入输出、算法处理、效果显示等多种功能。实验结果表明,本文开发的系统在软骨组织分割、骨和尿酸盐聚集分割、尿酸盐聚集伪影去除、二维和三维图像配准以及可视化方面具有良好的效果。该系统可应用于临床痛风和软骨缺损的诊断和评估,为辅助医生做出诊断决策提供充分依据。