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Glaucoma Diagnosis by Mapping Macula with Fourier Domain Optical Coherence Tomography

机译:通过用傅里叶域光学相干断层扫描来映射黄斑的青光眼诊断

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A new image segmentation method was developed to detect macular retinal sub-layers boundary on newly-developed Fourier-Domain Optical Coherence Tomography (FD-OCT) with macular grid scan pattern. The segmentation results were used to create thickness map of macular ganglion cell complex (GCC), which contains the ganglion cell dendrites, cell bodies and axons. Overall average and several pattern analysis parameters were defined on the GCC thickness map and compared for the diagnosis of glaucoma. Intraclass correlation (ICC) is used to compare the reproducibility of the parameters. Area under receiving operative characteristic curve (AROC) was calculated to compare the diagnostic power. The result is also compared to the output of clinical time-domain OCT (TD-OCT). We found that GCC based parameters had good repeatability and comparable diagnostic power with circumpapillary nerve fiber layer (cpNFL) thickness. Parameters based on pattern analysis can increase the diagnostic power of GCC macular mapping.
机译:开发了一种新的图像分割方法,以检测新开发的傅立叶域光学相干断层扫描(FD-OCT)的黄斑视网膜子层边界,具有黄斑网格扫描模式。分段结果用于创建黄斑神经节细胞复合物(GCC)的厚度图,其包含神经节细胞枝晶,细胞体和轴突。在GCC厚度图上定义了总体平均值和几种模式分析参数,并比较了青光眼的诊断。脑内相关性(ICC)用于比较参数的再现性。计算接受操作特征曲线(AROC)的区域以比较诊断功率。结果也与临床时域OCT(TD-OCT)的输出进行比较。我们发现基于GCC的参数具有良好的重复性和具有环状神经纤维层(CPNFL)厚度的可比诊断功能。基于模式分析的参数可以增加GCC Matulum映射的诊断功率。

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