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基于人工智能分割算法的光学相干断层扫描图像在双眼糖尿病视网膜病变评估中的应用。

Artificial Intelligence Segmentation Algorithm-Based Optical Coherence Tomography Image in Evaluation of Binocular Retinopathy.

机构信息

Department of Ophthalmology, The First People's Hospital of Tonglu County, Tonglu, 311500 Hangzhou, China.

出版信息

Comput Math Methods Med. 2022 Jun 1;2022:3235504. doi: 10.1155/2022/3235504. eCollection 2022.

Abstract

On account of optical coherence tomography (OCT) images with intelligent segmentation algorithm, this article investigated the clinical efficacy and safety of docetaxel combined with fluorouracil. In this study, 60 patients with retinopathy treated in hospital were selected as the research objects. There were 30 cases in each group, the control group was treated with conventional images, and the observation group was treated with algorithm-based OCT images. Intelligent segmentation boundary detection algorithm, boundary tracking, and contour localization were proposed and applied to the OCT images of patients to analyze features and measure corneal thickness in OCT images with high signal-to-noise ratio and noise and artifacts. Objects in the control group were treated with semiconductor laser, and those in the observation group were treated with OCT images with algorithm in addition to the treatment of the control group. The results showed that the number of images with relative error of 2 was more, and the number of images with relative error of -2 was the least. The average thickness of high-quality images was 562.7 m, and the average thickness of images with noise and artifacts was 573.8 m. The total effective rate of the observation group was 96.67%, which was significantly higher than that of the control group (80%), and the curative effect and physical improvement rate of the observation group were significantly better than that of the control group ( < 0.05). All in all, the feature extraction of OCT images and corneal measurement proposed in this study had a good measurement effect, and the method had the advantages of strong anti-interference ability and high measurement accuracy.

摘要

基于光学相干断层扫描(OCT)图像的智能分割算法,本文研究了多西紫杉醇联合氟尿嘧啶治疗视网膜病变的临床疗效和安全性。本研究选取医院收治的 60 例视网膜病变患者作为研究对象,每组 30 例,对照组采用常规图像治疗,观察组采用基于算法的 OCT 图像治疗。提出了智能分割边界检测算法、边界跟踪和轮廓定位,并将其应用于患者的 OCT 图像中,以分析特征并测量 OCT 图像中具有高信噪比和噪声及伪影的角膜厚度。对照组采用半导体激光治疗,观察组在对照组治疗的基础上增加算法 OCT 图像治疗。结果显示,相对误差为 2 的图像数量较多,相对误差为-2 的图像数量最少。高质量图像的平均厚度为 562.7μm,噪声和伪影图像的平均厚度为 573.8μm。观察组总有效率为 96.67%,明显高于对照组(80%),观察组的疗效和身体改善率明显优于对照组( < 0.05)。总之,本研究中提出的 OCT 图像特征提取和角膜测量方法具有良好的测量效果,该方法具有抗干扰能力强、测量精度高的优点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7aad/9177319/dcb3bc5958b5/CMMM2022-3235504.001.jpg

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