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利用降噪处理描绘单张光学相干断层扫描血管造影图像的近视性脉络膜新生血管的效用。

Usefulness of Denoising Process to Depict Myopic Choroidal Neovascularisation Using a Single Optical Coherence Tomography Angiography Image.

机构信息

Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.

Department of Ophthalmology, Red Cross Otsu Hospital, Otsu, Japan.

出版信息

Sci Rep. 2020 Apr 10;10(1):6172. doi: 10.1038/s41598-020-62607-6.

DOI:10.1038/s41598-020-62607-6
PMID:32277172
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7148361/
Abstract

Quality of single optical coherence tomography angiography (OCTA) images of myopic choroidal neovascularisation (mCNV) is poorer than in averaged images, although obtaining averaged images takes much time. This study evaluated the clinical usefulness of novel denoising process for depicting mCNV. This study included 20 eyes of 20 patients with mCNV. Ten en face images taken in a 3 × 3 mm macular cube were obtained from outer-retina-to-choriocapillaris layer. Three image types were prepared for analysis; single images before and after the denoising process accomplished deep learning (single and denoising groups, respectively) and up to 10 images were averaged (averaging group). Pairwise comparisons showed vessel density, vessel length density, and fractal dimension (FD) were higher; whereas, vessel density index (VDI) was lower in single group than in denoising and averaging groups. Detectable CNV indices, contrast-to-nose ratio, and CNV diagnostic scores were higher in denoising and averaging groups than in single group. No significant differences were detected in VDI, FD, or CNV diagnostic scores between denoising and averaging groups. The denoising process can utilise single OCTA images to provide results comparable to averaged OCTA images, which is clinically useful for shortening examination times with quality similar to averaging.

摘要

近视性脉络膜新生血管(mCNV)的单光学相干断层扫描血管造影(OCTA)图像质量比平均图像差,尽管获得平均图像需要花费大量时间。本研究评估了一种新的去噪处理方法在描绘 mCNV 方面的临床应用价值。本研究共纳入 20 例 20 只眼 mCNV 患者。从外视网膜到脉络膜毛细血管层获取 3×3mm 黄斑立方体面的 10 张共焦图像。准备了 3 种图像类型进行分析;分别是在深度学习前后完成去噪处理的单张图像(单张组和去噪组)和多达 10 张图像的平均图像(平均组)。两两比较显示,血管密度、血管长度密度和分形维数(FD)在单张组中较高,而血管密度指数(VDI)在单张组中较低,去噪组和平均组中。在去噪组和平均组中,可检测的 CNV 指数、对比噪声比和 CNV 诊断评分均高于单张组。去噪组和平均组之间的 VDI、FD 或 CNV 诊断评分无显著差异。去噪处理可以利用单张 OCTA 图像提供与平均 OCTA 图像相当的结果,这对于缩短检查时间、保持相似的质量具有临床意义。

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