Cao Guiping, Zhao Wei, Higashita Risa, Liu Jiang, Chen Wan, Yuan Jin, Zhang Yubing, Yang Ming
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:1646-1649. doi: 10.1109/EMBC44109.2020.9175944.
Lens structures segmentation on anterior segment optical coherence tomography (AS-OCT) images is a fundamental task for cataract grading analysis. In this paper, in order to reduce the computational cost while keeping the segmentation accuracy, we propose an efficient segmentation method for lens structures segmentation. At first, we adopt an efficient semantic segmentation network in the work, and used it to extract the lens area image instead of the conventional object detection method, and then used it once again to segment the lens structures. Finally, we introduce the curve fitting processing (CFP) on the segmentation results. Experiment results show that our method has good performance on accuracy and processing speed, and could be applied to CASIA II device for practical applications.
在前节段光学相干断层扫描（AS-OCT）图像上进行晶状体结构分割是白内障分级分析的一项基础任务。在本文中，为了在保持分割精度的同时降低计算成本，我们提出了一种用于晶状体结构分割的高效分割方法。首先，我们在工作中采用了一种高效的语义分割网络，并用它来提取晶状体区域图像，而不是传统的目标检测方法，然后再次用它来分割晶状体结构。最后，我们对分割结果引入曲线拟合处理（CFP）。实验结果表明，我们的方法在精度和处理速度方面具有良好的性能，并且可以应用于CASIA II设备进行实际应用。
