摘要
背景超长扫描深度OCT可应用于人眼前节的完整成像，但是如何快速、精确地从OCT图像中测量得到眼前节结构的生物学参数是目前亟待解决的难题，目前尚无精确自动处理频域OCT图像的理想软件系统。目的研究自行研制的软件自动测量基于超长扫描深度OCT图像的人眼前节生物学参数，评估软件自动化算法的精确度和重复性。方法于2013年6—7月在温州医科大学附属眼视光医院纳入10名健康受检者，共20眼，利用自主研发的超长扫描深度OCT获取人眼前节图像，编写自动探测软件对原始图像进行边界分割、图像配准和光学矫正等处理，其中边界分割算法基于图像的轴向亮度梯度信息，并利用最短路径搜索原理优化边界的准确探测。利用该自动化算法获取受检者中央角膜厚度（CCT）、前房深度（ACD）、瞳孔直径（PD）、晶状体厚度（LT）、晶状体前表面曲率半径（LAC）和后表面曲率半径（LPC），通过比较自动和手动测量眼前节各参数的差异以及重复测量值，评估自动化算法的精度和重复性。结果自动测量与手动测量的CCT、ACD、PD、LT、LAC和LPC值比较差异均无统计学意义（P=0．205、0．167、0．285、0．127、0．102、0．074），自动测量与手动测量各眼前节生物学参数值均有较好的一致性（均ICC〉0．75）。自动测量和手动测量测得的CCT、ACD和LT的重复测量值显示ICC〉0．75，自动测量的PD和LAC重复性（ICC=0．793、0．872；COR=2．90、5．79）优于手动测量（ICC：0．631、0．579；COR=5．62、10．46），但LPC自动测量的重复性（ICC=0．663；COR=6．17）稍差于手动测量（ICC=0．794；COR=4．79）。结论本研究组研制的图像测量软件算法自动测量的眼前节生物学参数具有精确度高、重复性好和运行速度快等特点，在实时探测眼前节形态学动态变化的研究中具有重要的应用价值。
Background Ultra-long scan depth OCT can achieve imaging of full range of human ocular anterior segment. However,the measurement of the dimension of anterior segment from the OCT image with high speed and precision is a challenge at present. The software of automatic data processing is still lack in analyzing spectral domain OCT. Objective This study was to perform the automatic biometry and data processing of human ocular anterior segment OCT image by using self-developed automatic detection software and evaluate the accuracy and repeatability of this method. Methods Twenty eyes of 10 normal subjects were included in Eye Hospital of Wenzhou Medical University from June to July 2013. The OCT image of anterior eye segments were obtained with custom-made ultra-long scan depth OCT under the informed consent. An＇automatic software algorithm was developed for the biometric measurement on these OCT images,including boundary s^egmentation,image registration and optical correction of OCT images. The boundary segmentation algorithm utilized the axial gradient information of OCT images and the shortest path search principal based on the dynamic programming to optimize edge finding. Central corneal thickness （CCT） , anterior chamber depth （ACD） , pupil diameter （PD） ,lens thickness （LT） , radius of lens anterior curvatures （LAC） and radius of lens of posterior curvatures （LPC） were automatically and manually measured, and the validity of automatic detection algorithm was assessed by calculating the intraclass correlation coefficient （ICC） between the automatic and manual measurements,and the repeatability was validated by calculating the coefficient of repeatability （COR） between repeated measurement. This study was approved by the Ethic Committee of Wenzhou Medical University and informed consent was obtained from all subjects. Results There were no significantdifferences in the results of CCT, ACD, PD, LT, LAC and LPC hetween the atitomatie and manual measurements （ P = O. 205, 0. 167,
出处
《中华实验眼科杂志》
CAS
CSCD
北大核心
2016年第4期345-350,共6页
Chinese Journal Of Experimental Ophthalmology
基金
浙江省自然科学基金项目（LY14H180007、LY13H180014）
