基于三维限制区域生长的SD-OCT中浆NRD病变区域分割

Abstract

Abstract: It is important to segment neurosensory retianl detachment (NRD) of central serous chorioretinopathy (CSC) region,because the volume of CSC region plays a very important role in the diagnosis and study of CSC,while NRD is the most common and serious situation in CSC.The paper presented an automated spatial-domain optical cohe-rence tomography (SD-OCT) NRD segmentation method,which firstly segments NRD lesion in 3D space.And the segmentation of lesion in two-dimensional images is transformed into three-dimensional space segmentation problem,which makes full use of the three-dimensional structure information of data and improves the segmentation precision.The experiment results with 18 SD-OCT cubes indicate that the proposed method can segment the NRD accurately,and the average area coverage is as high as 89.5%.Compared to other four segmentation methods,the proposed algorithm achieves the highest accuracy and costs the least time,which has great advantages in clinical application and research.

Key words: 3-D region growing, Adaptive threshold, Central serous chorioretinopathy, Neurosensory retianl detachment, Spatial-domain optical coherence tomography

CLC Number:

TP391

HE Xiao-jun, WU Meng-lin, FAN Wen, YUAN Song-tao, CHEN Qiang. SD-OCT CSC NRD Region Segmentation Based on Region Restricted 3D Region Growing[J].Computer Science, 2018, 45(6A): 187-192.

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SD-OCT CSC NRD Region Segmentation Based on Region Restricted 3D Region Growing

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