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首页> 外文会议>Optical Coherence tomography and coherence domain optical methods in biomedicine XX >THREE DIMENSIONAL CHOROIDAL SEGMENTATION IN SPECTRAL OCT VOLUMES USING OPTIC DISC PRIOR INFORMATION
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THREE DIMENSIONAL CHOROIDAL SEGMENTATION IN SPECTRAL OCT VOLUMES USING OPTIC DISC PRIOR INFORMATION

机译：使用视盘先验信息在光谱10月体积中的三维脉络膜分割

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Recently, much attention has been focused on determining the role of the peripapillary choroid - the layer between the outer retinal pigment epithelium (RPE)/Bruchs membrane (BM) and choroid-sclera (C-S) junction, whether primary or secondary in the pathogenesis of glaucoma. However, the automated choroidal segmentation in spectral-domain optical coherence tomography (SD-OCT) images of optic nerve head (ONH) has not been reported probably due to the fact that the presence of the BM opening (BMO, corresponding to the optic disc) can deflect the choroidal segmentation from its correct position. The purpose of this study is to develop a 3D graph-based approach to identify the 3D choroidal layer in ONH-centered SD-OCT images using the BMO prior information. More specifically, an initial 3D choroidal segmentation was first performed using the 3D graph search algorithm. Note that varying surface interaction constraints based on the choroidal morphological model were applied. To assist the choroidal segmentation, two other surfaces of internal limiting membrane and inner-outer segment junction were also segmented. Based on the segmented layer between the RPE/BM and C-S junction, a 2D projection map was created. The BMO in the projection map was detected by a 2D graph search. The pre-defined BMO information was then incorporated into the surface interaction constraints of the 3D graph search to obtain more accurate choroidal segmentation. Twenty SD-OCT images from 20 healthy subjects were used. The mean differences of the choroidal borders between the algorithm and manual segmentation were at a sub-voxel level, indicating a high level segmentation accuracy.
机译：最近，人们已经将许多注意力集中在确定乳头周围脉络膜的作用上-视网膜外色素上皮（RPE）/ Bruchs膜（BM）和脉络膜巩膜（CS）交界之间的层，无论是其发病的主要还是继发性青光眼。但是，尚未报告视神经乳头（ONH）的光谱域光学相干断层扫描（SD-OCT）图像中的脉络膜自动分割，可能是由于存在BM开口（BMO，与视盘相对应） ）可以使脉络膜分段偏离其正确位置。这项研究的目的是开发一种基于3D图形的方法，以使用BMO先验信息来识别以ONH为中心的SD-OCT图像中的3D脉络膜层。更具体地说，首先使用3D图形搜索算法执行初始3D脉络膜分割。注意，基于脉络膜形态模型应用了变化的表面相互作用约束。为了辅助脉络膜切开术，还对内部限制膜和内外节段连接处的其他两个表面进行了切分。基于RPE / BM和C-S连接之间的分段层，创建了2D投影图。投影图中的BMO通过2D图形搜索进行检测。然后将预定义的BMO信息合并到3D图形搜索的表面交互约束中，以获得更准确的脉络膜分割。使用了来自20位健康受试者的20张SD-OCT图像。算法和手动分割之间脉络膜边界的平均差异在亚体素水平上，表明分割精度很高。

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