Optical coherence tomography (OCT) is a nondestructive imaging modality with the potential to make quantitative spatial measurements. OCT's noncontact nature, sensitivity to small refractive index mismatches, and micron-scale resolution make it attractive for contact lens metrology, specifically, measuring prism. Prism is defined as the maximum difference in thickness of the contact lens, measured over a full 360 deg of rotation, at a fixed distance from the contact lens edge. We develop and test a novel algorithm that automatically analyzes OCT images and calculates prism. Images are obtained using a Thorlabs OCT930SR OCT system. The OCT probe is fastened to an automated rotation stage that rotates 360 deg in small increments (typically 10 deg) to acquire OCT images of the edge of the contact lens around the entire circumference. The images are 1.6 mm in optical depth (512 pixels) and 2 mm wide (1000 pixels). Several sets of images are successfully analyzed. The prism measured for a toric lens is 42 µm, which is in line with design parameters. Thickness measurements are repeatable with a standard deviation of 0.5 µm and maximum range of 1.8 µm over ten image sets. This work demonstrates the possibility of using OCT to perform nondestructive contact lens metrology.
Optical Coherence Tomography (OCT) is a non-destructive imaging modality that has proven to be a useful tool for making quantitative measurements in a variety of applications. One area where non-destructive quantitative measurement is important is contact lens metrology, specifically prism. Prism is defined as the difference between the largest and smallest thickness measured at a fixed distance from the contact lens edge. We developed and tested an algorithm that automatically analyzes OCT images to accurately measure contact lens thickness. Images were obtained with the Thorlabs OCT930SR spectral radar OCT system. An automated rotation stage was used to precisely rotate the OCT probe 360 degrees in small increments to acquire OCT images along the entire outer edge of the contact lens. The algorithm was able to successfully analyze hundreds of OCT images. For comparison, measurements were taken by physically slicing contact lenses and manually measuring their thickness using a microscope. The error between the two measurements had a mean of -1.268 um and a range of 9.041 um. Thickness measurements were repeatable with a maximum range of 1.8 μm. The success of the algorithm has demonstrated the possibility of using OCT images for performing non-destructive contact lens metrology.