提出一种光学相干层析(OCT)视网膜体数据3维分割的新方法。综合利用视网膜边界方向、图像强度峰值及分而治之的策略,可分割出多层重要边界面。具体过程是:在OCT体数据中,从上到下查找A-scan的第1个峰值确定内界膜(ILM)的初始位置,再通过表面光滑性约束去除异常点进行优化;利用类似的方法从下到上查找A-scan的第1个峰值定位视网膜色素上皮层(RPE);然后,对由ILM和RPE之间的数据构成的子体,确定每条A-scan的亮度最大值分割出内外节层(IS/OS)上边界表面;最后,对由ILM和IS/OS之间的数据构成的子体,从下到上寻找A-scan的第1个峰值定位内核层和外网织层(INL/OPL)之间的边界表面。实验结果表明,本文方法在普通台式计算机上能够正确地分割出上述4个边界面,且每个边界面的分割可在几秒内完成。

A new three-dimensional segmentation approach of retina Optical Coherence Tomography (OCT) volume data is presented, which makes full use of the retina layers’ directions, signal intensity peaks and divide-and-conquer strategy to detect multiple retina boundary surfaces. The primary position of the inner limiting membrane (ILM) is determined by finding the first peak in every A-scan from top to bottom in the volume. Abnormal points of the boundary are removed by using surface smoothness constraints. The retinal pigment epithelium (RPE) boundary surface is obtained similarly by finding the first peak in every A-scan from bottom to top. Then, the boundary surface of the inner segments and outer segments (IS/OS) layer is positioned by detecting the maximum intensity of every A-scan in the sub-volume data between the ILM and RPE. Finally, the boundary surface of the inner nuclear layer and the outer plexiform (INL/OPL) layer is segmented by searching the first peak of every A-scan from bottom to top in the sub-volume data between the ILM and IS/OS. Experimental results show that the method can not only segment the four boundary surfaces correctly, but also only takes several seconds for segmenting each surface on a personal computer.