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首页> 外文会议>Dynamics and fluctuations in biomedical photonics XI >Automated Choroidal Segmentation Method in Human Eye with 1050 nm Optical Coherence Tomography
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Automated Choroidal Segmentation Method in Human Eye with 1050 nm Optical Coherence Tomography

机译：1050 nm光学相干层析成像技术在人眼中自动脉络膜分割方法

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摘要

Choroidal thickness (ChT), defined as the distance between the retinal pigment epithelium (RPE) and the choroid-sclera interface (CSI), is highly correlated with various ocular disorders like high myopia, diabetic retinopathy, and central serous chorioretinopathy. Long wavelength Optical Coherence Tomography (OCT) has the ability to penetrate deep to the CSI, making the measurement of the ChT possible. The ability to accurately segment the CSI and RPE is important in extracting clinical information. However, automated CSI segmentation is challenging due to the weak boundary in the lower choroid and inconsistent texture with varied blood vessels. We propose a K-means clustering based automated algorithm, which is effective in segmenting the CSI and RPE. The performance of the method was evaluated using 531 frames from 4 normal subjects. The RPE and CSI segmentation time was about 0.3 seconds per frame, and the average time was around 0.5 seconds per frame with correction among frames, which is faster than reported algorithms. The results from the proposed method are consistent with the manual segmentation results. Further investigation includes the optimization of the algorithm to cover more OCT images captured from patients and the increase of the processing speed and robustness of the segmentation method.
机译：脉络膜厚度（ChT）定义为视网膜色素上皮（RPE）与脉络膜-巩膜界面（CSI）之间的距离，与各种眼部疾病高度相关，例如高度近视，糖尿病性视网膜病变和中央性浆液性脉络膜视网膜病变。长波长光学相干断层扫描（OCT）具有穿透CSI深度的能力，从而可以测量ChT。准确分割CSI和RPE的能力在提取临床信息中很重要。但是，由于下脉络膜的边界薄弱且血管变化，质地不均匀，所以自动CSI分割是一项挑战。我们提出了一种基于K均值聚类的自动化算法，该算法可有效地分割CSI和RPE。使用来自4个正常对象的531帧评估了该方法的性能。 RPE和CSI的分段时间约为每帧0.3秒，平均时间约为每帧0.5秒，并且帧之间有校正，这比报告的算法快。所提方法的结果与人工分割结果一致。进一步的研究包括算法的优化，以覆盖从患者捕获的更多OCT图像，并提高处理速度和分割方法的鲁棒性。

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