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Microtron camera used for development of pupil tracking device for eye research







Seeing is Believing: Microtron camera used to develop pupil tracking device for eye research

January 24, 2023 – The human eye is in constant involuntary movement, even when fixating on a target. When involuntary eye movement goes to extremes in amplitude and angular velocity, it is a medical condition called nystagmus. Nystagmus is most often caused by a neurological problem that is present at birth or develops in early childhood. Acquired nystagmus, which occurs later in life, may be a symptom of another condition or disease.


Nystagmus presents a number of problems for physicians who use ophthalmoscopy to diagnose and monitor eye diseases, including glaucoma, diabetes, and high blood pressure, or to evaluate symptoms of retinal detachment. Nystagmus can introduce significant blurring in ophthalmoscope images and distortion in scanning ophthalmoscope images, making the detection of eye disease challenging. Blurring and distortion are particularly problematic in adaptive optics ophthalmoscopy due to its high magnification and small fields of view.


Pupil tracker optical setup showing Mikrotron camera, interferometric bandpass filter, and achromatic doublets (L1 to L3). The camera is tilted relative to the optical axis to compensate for the 45° object plane tilt, facilitating integration with ophthalmoscopes or other devices (courtesy of Stanford University).



Researchers at the Department of Ophthalmology at Stanford University (Palo Alto, CA) have developed a low-latency monocular pupil tracker using hybrid FPGA-CPU computing. They found that by overlapping the image processing in a pixel stream downloaded from a high-resolution camera, as opposed to the more conventional approach where images are fully downloaded before processing starts, they could reduce latency and therefore image blur in ophthalmoscope images. High precision and low latency make their device suitable for retinal imaging, retinal function testing, retinal laser treatment and refractive surgery requiring real-time eye movement compensation.


The pupil tracker was built with off-the-shelf components with the aim of improving both its performance and cost. It consists of an optical system with infrared illumination that relays the pupil of the eye to a Mikroton CMOS camera connected to an FPGA in a computer with a powerful CPU. Two 940 nm light-emitting diodes are located to the left and right of the lens closest to the eye. The use of two LEDs instead of one spreads the retinal irradiation over two areas with their centers separated by a viewing angle of approx. 25°, which provides better light reliability than using a single LED.


Raw pupil images (linear intensity scale) captured on the same subject using different camera gains and the corresponding thresholded binary images. The annotations show the edges identified by ellipse fitting (green) and those discarded by median linear fit (red) and clustering (yellow) (Courtesy of Stanford University).



Specifically, the pupil tracker was evaluated with a Mikroton EoSens 3CL camera with extended full configuration CameraLink interfaces when capturing 8-bit depth images to achieve the maximum download data rate allowed by this interface. The compact EoSens 3CL camera’s maximum resolution is 1696 × 1710 pixels at a frame rate of 285 fps. The integrated and adjustable area of ​​interest function enables operation at 628 fps at 1280 × 1024-pixel resolution, 893 fps at 1280 × 720 and 816 fps at 1000 × 1000. It achieves infinitely adjustable frame rates of up to 285,000 fps at reduced resolution.


Three optical setups were used in testing with an approximately 18 mm square field of view tilted 45° to the optical axis and correspondingly tilted image plane. The third experimental approach used the Mikrotron setup to capture 210×284 pixel images with 0.18 ms exposure at 5400 frames/s. Raw pixel values ​​for the camera were downloaded to a reconfigurable frame grabber with a Kintex-7 325T FPGA that was custom programmed using the LabVIEW FPGA module and the Vivado Design Suite. The frame grabber was installed in a PCIe slot on a computer with an Intel i7-6850K CPU and an Nvidia GeForce GTX 1050 discrete GPU. Raw images underwent background subtraction, field flattening, 1-dimensional low-pass filtering, thresholding, and robust pupil-edge detection on an FPGA pixel stream, followed by least-squares fitting of the pupil-edge pixel coordinates to an ellipse in the CPU.


Pupil tracking was successfully demonstrated in a normally fixating subject at 575, 1250 and 5400 frames per second. According to the study, the approach seems suitable for tracking the pupil with precision comparable to or better than current pupil trackers. High precision and low latency make the device suitable for applications requiring real-time eye movement compensation, such as retinal imaging, retinal function testing, retinal laser treatment and refractive surgery.


The project was funded by Research to Prevent Blindness and the National Eye Institute.

1. Bartholomew Kowalski, Xiaojing Huang, Samuel Steven, and Alfredo Dubra, “Hybrid FPGA-CPU pupil tracker,” Biomed. Opt. Express 12, 6496-6513 (2021)


About Mikrotron GmbH


Established in 1976 and located just outside Munich, Germany, Mikrotron GmbH offers a complete range of advanced imaging solutions for challenging applications in industry, engineering, science and sports. The company designs, manufactures and commercializes high-speed and high-resolution cameras, imaging cameras and systems, software and image processing components. Mikrotron’s slow-motion recording enables customers to optimize manufacturing processes, improve product design, revolutionize quality control and analyze motion. Mikrotron is ISO:9001 certified. Mikrotron is operated under the umbrella of SVS-Vistek.





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