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3D-Spectral Imaging System for Anterior Chamber Metrology

机译:前房计量3D光谱成像系统

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摘要

Accurate metrology of the anterior chamber of the eye is useful for a number of diagnostic and clinical applications. In particular, accurate corneal topography and corneal thickness data is desirable for fitting contact lenses, screening for diseases and monitoring corneal changes. Anterior OCT systems can be used to measure anterior chamber surfaces, however accurate curvature measurements for single point scanning systems are known to be very sensitive to patient movement. To overcome this problem we have developed a parallel 3D spectral metrology system that captures simultaneous A-scans on a 2D lateral grid. This approach enables estimates of the elevation and curvature of anterior and posterior corneal surfaces that are robust to sample movement. Furthermore, multiple simultaneous surface measurements greatly improve the ability to register consecutive frames and enable aggregate measurements over a finer lateral grid. A key element of our approach has been to exploit standard low cost optical components including lenslet arrays and a 2D sensor to provide a path towards low cost implementation. We demonstrate first prototypes based on 6 Mpixel sensor using a 250 μm pitch lenslet array with 300 sample beams to achieve an RMS elevation accuracy of 1μm with 95 dB sensitivity and a 7.0 mm range. Initial tests on Porcine eyes, model eyes and calibration spheres demonstrate the validity of the concept. With the next iteration of designs we expect to be able to achieve over 1000 simultaneous A-scans in excess of 75 frames per second.
机译:眼睛的准确计量眼睛的眼睛室是有用的许多诊断和临床应用。特别地,精确的角膜地形和角膜厚度数据是为了配合隐形眼镜,筛选疾病和监测角膜变化。前oct系统可用于测量前腔室表面,但是已知对单点扫描系统的精确曲率测量对患者运动非常敏感。为了克服这个问题,我们开发了一个并行3D光谱计量系统,该系统在2D横向网格上捕获同时扫描。该方法能够估计对样品运动的鲁棒和后部角膜表面的仰角和曲率。此外,多个同时表面测量大大提高了登记了连续帧的能力,并在更精细的横向网格上实现聚合测量。我们的方法的一个关键因素已经利用标准的低成本光学组件,包括Lenslet阵列和2D传感器,以提供低成本实现的路径。我们使用具有300个样本梁的250μm间距透镜阵列的6个MPixel传感器展示了基于6个MPIXEL传感器的第一种原型,以实现1μm的RMS高度精度,具有95 dB灵敏度和7.0mm。猪眼的初始测试,模型眼睛和校准球体展示了概念的有效性。随着设计的下一次迭代,我们希望能够实现超过1000多个同时扫描超过每秒75帧的扫描。

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