Classical dispersion-cancellation interferometry

Even-order dispersion cancellation, an effect previously identified with frequency-entangled photons, is demonstrated experimentally for the first time with a linear, classical interferometer. A combination of a broad bandwidth laser and a high resolution spectrometer was used to measure the intensity correlations between anti-correlated optical frequencies. Only 14% broadening of the correlation signal is observed when significant material dispersion, enough to broaden the regular interferogram by 4250%, is introduced into one arm of the interferometer.Comment: 4 pages, 3 figure

Improved image speckle noise reduction and novel dispersion cancellation in Optical Coherence Tomography

Optical coherence tomography (OCT) is an innovative modern biomedical imaging technology that allows in-vivo, non-invasive imaging of biological tissues. At present, some of the major challenges in OCT include the need for fast data acquisition system for probing fast developing biochemical processes in biological tissue, for image processing algorithms to reduce speckle noise and to remove motion artefacts, and for dispersion compensation to improve axial resolution and image contrast. To address the need for fast data acquisition, a novel, high speed (47,000 A-scans/s), ultrahigh axial resolution (3.3μm) Fourier Domain Optical Coherence Tomography (FD-OCT) system in the 1060nm wavelength region has been built at the University of Waterloo. The system provides 3.3μm image resolution in biological tissue and maximum sensitivity of 110 dB. Retinal tomograms acquired in-vivo from a human volunteer and a rat animal model show clear visualization of all intra-retinal layers and increased penetration into the choroid. OCT is based on low-coherence light interferometry. Thus, image quality is dependent on the spatial and temporal coherence properties of the optical waves back-scattered from the imaged object. Due to the coherent nature of light, OCT images are contaminated with speckle noise. Two novel speckle noise reduction algorithms based on interval type II fuzzy sets has been developed to improve the quality of the OCT images. One algorithm is a combination of anisotropic diffusion and interval type II fuzzy system while the other algorithm is based on soft thresholding wavelet coefficients using interval type II fuzzy system. Application of these novel algorithms to Cameraman test image corrupted with speckle noise (variance=0.1) resulted in a root mean square error (RMSE) of 0.07 for both fuzzy anisotropic diffusion and fuzzy wavelet algorithms. This value is less compared to the results obtained for Wiener (RMSE=0.09), adaptive Lee (RMSE=0.09), and median (RMSE=0.12) filters. Applying the algorithms to optical coherence tomograms acquired in-vivo from a human finger-tip show reduction in the speckle noise and image SNR improvement of ~13dB for fuzzy anisotropic diffusion and ~11db for fuzzy wavelet. Comparison with the Wiener (SNR improvement of ~3dB), adaptive Lee (SNR improvement of ~5dB) and median (SNR improvement of ~5dB) filters, applied to the same images, demonstrates the better performance of the fuzzy type II algorithms in terms of image metrics improvement. Micrometer scale OCT image resolution is obtained via use of broad bandwidth light sources. However, the large spectral bandwidth of the imaging beam results in broadening of the OCT interferogram because of the dispersive properties of the imaged objects. This broadening causes deterioration of the axial resolution and as well as loss of contrast in OCT images. A novel even-order dispersion cancellation interferometry via a linear, classical interferometer has been developed which can be further expanded to dispersion canceled OCT

In vivo volumetric imaging of chicken retina with ultrahigh-resolution spectral domain optical coherence tomography

The chicken retina is an established animal model for myopia and light-associated growth studies. It has a unique morphology: it is afoveate and avascular; oxygen and nutrition to the inner retina is delivered by a vascular tissue (pecten) that protrudes into the vitreous. Here we present, to the best of our knowledge, the first in vivo, volumetric high-resolution images of the chicken retina. Images were acquired with an ultrahigh-resolution optical coherence tomography (UHROCT) system with 3.5 µm axial resolution in the retina, at the rate of 47,000 A-scans/s. Spatial variations in the thickness of the nerve fiber and ganglion cell layers were mapped by segmenting and measuring the layer thickness with a semi-automatic segmentation algorithm. Volumetric visualization of the morphology and morphometric analysis of the chicken retina could aid significantly studies with chicken retinal models of ophthalmic diseases

Automated detection and cell density assessment of keratocytes in the human corneal stroma from ultrahigh resolution optical coherence tomograms

Keratocytes are fibroblast-like cells that maintain the optical clarity and the overall health of the cornea. The ability to measure precisely their density and spatial distribution in the cornea is important for the understanding of corneal healing processes and the diagnostics of some corneal disorders. A novel computerized approach to detection and counting of keratocyte cells from ultra high resolution optical coherence tomography (UHR-OCT) images of the human corneal stroma is presented. The corneal OCT data is first processed using a state-of-the-art despeckling algorithm to reduce the effect of speckle on detection accuracy. A thresholding strategy is then employed to allow for improved delineation of keratocyte cells by suppressing similarly shaped features in the data, followed by a second-order moment analysis to identify potential cell nuclei candidates. Finally, a local extrema strategy is used to refine the candidates to determine the locations and the number of keratocyte cells. Cell density distribution analysis was carried in 3D UHR-OCT images of the human corneal stroma, acquired in-vivo. The cell density results obtained using the proposed novel approach correlate well with previous work on computerized keratocyte cell counting from confocal microscopy images of human cornea

Wavelet denoising of multiframe optical coherence tomography data

We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation. Based on this analysis, the wavelet detail coefficients are weighted, averaged and reconstructed. At a signal-to-noise gain at about 100% we observe only a minor sharpness decrease, as measured by a full-width-half-maximum reduction of 10.5%. While a similar signal-to-noise gain would require averaging of 29 frames, we achieve this result using only 8 frames as input to the algorithm. A possible application of the proposed algorithm is preprocessing in retinal structure segmentation algorithms, to allow a better differentiation between real tissue information and unwanted speckle noise

Tensor total variation approach to optical coherence tomography reconstruction for improved visualization of retinal microvasculature

A novel optical coherence tomography (OCT) reconstruction approach is introduced for improved visualization of inner-retina capillaries in retinal OCT tomograms. The proposed method utilizes a minimization framework based on a tensor total variation (TTV) energy functional, to enforce capillary structural characteristics in the spatial domain. By accounting for structure tensor characteristics, the TTV reconstruction method allows for contrast enhancement of capillary structural characteristics. The novel TTV method was tested on high resolution OCT images acquired in-vivo from the foveal region of the retina of a healthy human subject. Experimental results demonstrate significant contrast and visibility enhancement of the inner retina capillaries in the retinal OCT tomograms, achieved by use of the TTV reconstruction method. Therefore, the TTV method has a strong potential for improved disease progression analysis based on the study of disease-induced changes in the inner retina vasculature

An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin

Background: Optical coherence tomography (OCT) of skin delivers three-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution modality, OCT images suffer from some artifacts that lead to misinterpretation of tissue structures. Therefore, an overview of methods to mitigate artifacts in OCT imaging of the skin is of paramount importance. Speckle, intensity decay, and blurring are three major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. Method: Two speckle reduction methods (one based on artificial neural network and one based on spatial compounding), an attenuation compensation algorithm (based on Beer-Lambert law) and a deblurring procedure (using deconvolution), are described. Moreover, optical properties extraction algorithm based on extended Huygens-Fresnel (EHF) principle to obtain some additional information from OCT images are discussed. Results: In this short overview, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. The results showed a significant improvement in the visibility of the clinically relevant features in the images. The quality improvement was evaluated using several numerical assessment measures. Conclusion: Clinical dermatologists benefit from using these image enhancement algorithms to improve OCT diagnosis and essentially function as a noninvasive optical biopsy

Speckle reduction algorithm for optical coherence tomography based on Interval Type II Fuzzy Set

A novel speckle reduction technique based on soft thresholding of wavelet coefficients using interval type II fuzzy system was developed for reducing speckle noise in Optical Coherence Tomography images. The proposed algorithm is an extension of a recently published method for filtering additive noise by use of type I fuzzy system. Unlike type I, interval type II fuzzy based thresholding filter considers the uncertainty in the calculated threshold and the wavelet coefficient is adjusted based on this uncertainty. Application of this novel algorithm to optical coherence tomography images of a finger tip show reduction in speckle with little edge blurring

High-speed 1310 nm-band spectral domain optical coherence tomography at 184,000 lines per second

We propose a useful method to boost the imaging speed for spectral domain optical coherence tomography (SDOCT) by multiplying a number of high-speed spectrometers used in the system with selective precise control of data-recording and data-reading phases for spectral cameras employed in each spectrometer. To demonstrate the proposed method, we use two spectrometers built in a 1310 nm-band SDOCT system, each equipped with a high-speed InGaAs line-scan camera capable of 92-kHz line-scan rate, to achieve an unprecedented imaging speed at 184,000 lines/s. We validate the multiplied imaging speed by measuring Doppler-induced phase shift in the spectrograms using a flow phantom