Mohaghegh Navid, Magierowski Sebastian, Ghafar-Zadeh Ebrahim
Biologically Inspired Sensors and Actuators (BioSA) Laboratory, Department of EECS, York University, Toronto, ON M3J1P3, Canada.
Vision (Basel). 2019 Dec 11;3(4):68. doi: 10.3390/vision3040068.
This paper presents a new mathematical model along with a measurement platform for accurate detection and monitoring of various visual distortions (VD) caused by macular disorders such as central serous chorioretinopathy (CSR) and age-related macular degeneration (AMD). This platform projects a series of graphical patterns on the patient's retina and calculates the severity of VDs accordingly. The accuracy of this technique relies on the accurate detection of distorted lines by the patient. We also propose a simple mathematical model to evaluate the VD created by CSR. The model is used as a control for the test results achieved from the proposed platform. The proposed platform consists of the required hardware and software for the generation and projection of patterns along with the collection and processing of patients against their standard optical coherence tomography (OCT) images. Based on these results, the OCT images agree with the VD test results, and the proposed platform can be used as an alternative home monitoring method for various macular disorders.
本文提出了一种新的数学模型以及一个测量平台,用于精确检测和监测由黄斑疾病(如中心性浆液性脉络膜视网膜病变(CSR)和年龄相关性黄斑变性(AMD))引起的各种视觉畸变(VD)。该平台在患者视网膜上投射一系列图形模式,并据此计算VD的严重程度。该技术的准确性依赖于患者对扭曲线条的准确检测。我们还提出了一个简单的数学模型来评估由CSR产生的VD。该模型用作所提出平台测试结果的对照。所提出的平台包括用于生成和投射模式以及收集和处理患者相对于其标准光学相干断层扫描(OCT)图像所需的硬件和软件。基于这些结果,OCT图像与VD测试结果一致,并且所提出的平台可作为各种黄斑疾病的替代家庭监测方法。