Our data indicate that the human precorneal tear film can be measured with excellent reproducibility using ultrahigh-resolution optical coherence tomography. This technique may be a valuable tool in the management of dry eye syndrome.

Applying novel detector development based on CMOS technology to Fourier domain optical coherence tomography we achieve depth profile rates up to 200,000 scans/sec. This speed allows for dramatic improvement for imaging small retinal details, such as photo-receptors and capillaries. We demonstrate the impact of this achievable speed to Doppler tomography and discuss advantages as well as short-comings of high speed 3D Doppler imaging of the human retina. Experimental data of 3D static DFDOCT sets from fovea and nerve head region are shown together with first 4D imaging of retinal capillary flow.

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We present a high speed polarization sensitive spectral domain optical coherence tomography system based on polarization maintaining fibers and two high speed CMOS line scan cameras capable of retinal imaging with up to 128 k A-lines/s. This high imaging speed strongly reduces motion artifacts and therefore averaging of several B-scans is possible, which strongly reduces speckle noise and improves image quality. We present several methods for averaging retardation and optic axis orientation, the best one providing a 5 fold noise reduction. Furthermore, a novel scheme of calculating images of degree of polarization uniformity is presented. We quantitatively compare the noise reduction depending on the number of averaged frames and discuss the limits of frame numbers that can usefully be averaged.

Using a spectral domain OCT system, equipped with a broadband Ti:sapphire laser, we imaged the human retina with 5 µm x 1.3 µm transverse and axial resolution at acquisition rate of 100 kHz. Such imaging speed significantly reduces motion artifacts. Combined with the ultra-high resolution, this allows observing microscopic retinal details with high axial definition without the help of adaptive optics. In this work we apply our system to image the parafoveal capillary network. We demonstrate how already on the intensity level the parafoveal capillaries can be segmented by a simple structural high pass filtering algorithm. This data is then used to quantitatively characterize the capillary network of healthy and diseased eyes. We propose to use the fractal dimension as index for capillary integrity of pathologic disorders.