SD-OCT图像视网膜最小距离带(MDB)自动计算

Md. Akter Hussain, A. Bhuiyan, K. Ramamohanarao
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引用次数: 2

摘要

本文提出了一种从视网膜SD-OCT图像自动确定最小距离带(MDB)的新方法。MDB是视网膜色素上皮(RPE)层与视神经头(ONH)表面之间的最小距离。它是青光眼早期检测的有效生物标志物。本文提出的方法是第一个自动计算最小距离频带(MDB)的方法。该方法使用视网膜的三个基准参考层(TBMR)的近似位置,有助于减少搜索空间。这种方法是高度准确的检测边界层,即使在存在病理。RPE的端点作为ONH区域。ONH和MDB的准确性以青光眼患者的13个手动分级视盘中心SD-OCT体积(每体积11个b扫描)作为金标准进行测试。我们的方法非常有效,ONH宽度和MDB的误差均值和标准差分别为5.36±5.55和14.96±17.75。ONH区域的查准率为94.90,查全率为98.14,F1分数为96.49。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Retinal Minimum Distance Band (MDB)Computation from SD-OCT Images
In this paper, we have proposed a novel automatic method to determine the Minimum Distance Band (MDB) from the retinal SD-OCT image. MDB is the minimum distance between the retinal pigment epithelium (RPE) layer and the Optic Nerve Head (ONH) surface. It is an effective biomarker for early detection of glaucoma. Our proposed method is the first automatic method for computing the Minimum Distance Band (MDB). This method uses the approximate location of three benchmark reference (TBMR) layers of the retina that help to reduce the search space. This approach is highly accurate in detecting the boundary layers even in the presence of pathology. The terminal points of the RPE serve as the ONH region. The accuracies of ONH and MDB are tested against 13 manually graded optic disc centred SD-OCT volumes (11 B-scan per volume) of Glaucoma patients as a gold standard. Our method is very effective with mean and standard deviation of the error of the ONH width and MDB of 5.36±5.55 and 14.96±17.75 respectively. The precision, recall and F1 score for the ONH region are 94.90, 98.14 and 96.49 respectively.
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