Alonso-Caneiro David, Sampson Danuta M, Chew Avenell L, Collins Michael J, Chen Fred K
Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Victoria Park Road, Kelvin Grove QLD 4059, Brisbane, Australia.
Lions Eye Institute, 2 Verdun Street, Nedlands WA 6009, Perth, Australia.
Biomed Opt Express. 2018 Jan 18;9(2):679-693. doi: 10.1364/BOE.9.000679. eCollection 2018 Feb 1.
Adaptive optics flood illumination ophthalmoscopy (AO-FIO) allows imaging of the cone photoreceptor in the living human retina. However, clinical interpretation of the AO-FIO image remains challenging due to suboptimal quality arising from residual uncorrected wavefront aberrations and rapid eye motion. An objective method of assessing image quality is necessary to determine whether an AO-FIO image is suitable for grading and diagnostic purpose. In this work, we explore the use of focus measure operators as a surrogate measure of AO-FIO image quality. A set of operators are tested on data sets acquired at different focal depths and different retinal locations from healthy volunteers. Our results demonstrate differences in focus measure operator performance in quantifying AO-FIO image quality. Further, we discuss the potential application of the selected focus operators in (i) selection of the best quality AO-FIO image from a series of images collected at the same retinal location and (ii) assessment of longitudinal changes in the diseased retina. Focus function could be incorporated into real-time AO-FIO image processing and provide an initial automated quality assessment during image acquisition or reading center grading.
自适应光学泛光照明检眼镜(AO-FIO)能够对活体人类视网膜中的视锥光感受器进行成像。然而,由于残余未校正的波前像差和快速眼球运动导致图像质量欠佳,AO-FIO图像的临床解读仍然具有挑战性。需要一种客观的图像质量评估方法来确定AO-FIO图像是否适合分级和诊断目的。在这项工作中,我们探索使用聚焦度量算子作为AO-FIO图像质量的替代度量。一组算子在从健康志愿者获取的不同焦深和不同视网膜位置的数据集上进行了测试。我们的结果表明,聚焦度量算子在量化AO-FIO图像质量方面的性能存在差异。此外,我们讨论了所选聚焦算子在以下方面的潜在应用:(i)从在同一视网膜位置采集的一系列图像中选择质量最佳的AO-FIO图像,以及(ii)评估病变视网膜的纵向变化。聚焦函数可纳入实时AO-FIO图像处理中,并在图像采集或阅片中心分级期间提供初步的自动质量评估。