All-depth dispersion cancellation in spectral domain optical coherence tomography using numerical intensity correlations

Dispersion mismatch correction for evident chromatic anomaly in low coherence interferometry

The applications of ultrafast optics to biomedical microscopy have expanded rapidly in recent years, including interferometric techniques like optical coherence tomography and microscopy (OCT/OCM). The advances of ultra-high resolution OCT and the inclusion of OCT/OCM in multimodal systems combined with multiphoton microscopy have marked a transition from using pseudo-continuous broadband sources, such as superluminescent diodes, to ultrafast supercontinuum optical sources. We report anomalies in the dispersion profiles of low-coherence ultrafast pulses through long and non-identical arms of a Michelson interferometer that are well beyond group delay or third-order dispersions. This chromatic anomaly worsens the observed axial resolution and causes fringe artifacts in the reconstructed tomograms in OCT/OCM using traditional algorithms. We present DISpersion COmpensation Techniques for Evident Chromatic Anomalies (DISCOTECA) as a universal solution to address the problem of chromatic dispersion mismatch in interferometry, especially with ultrafast sources. First, we demonstrate the origin of these artifacts through the self-phase modulation of ultrafast pulses due to focusing elements in the beam path. Next, we present three solution paradigms for DISCOTECA: optical, optoelectronic, and computational, along with quantitative comparisons to traditional methods to highlight the improvements to the dynamic range and axial profile. We explain the piecewise reconstruction of the phase mismatch between the arms of the spectral-domain interferometer using a modified short-term Fourier transform algorithm inspired by spectroscopic OCT. Finally, we present a decision-making guide for evaluating the utility of DISCOTECA in interferometry and for the artifact-free reconstruction of OCT images using an ultrafast supercontinuum source for biomedical applications.

Time-domain full-field optical coherence tomography (TD-FF-OCT) in ophthalmic imaging

Ocular imaging plays an irreplaceable role in the evaluation of eye diseases. Developing cellular-resolution ophthalmic imaging technique for more accurate and effective diagnosis and pathogenesis analysis of ocular diseases is a hot topic in the cross-cutting areas of ophthalmology and imaging. Currently, ocular imaging with traditional optical coherence tomography (OCT) is limited in lateral resolution and thus can hardly resolve cellular structures. Conventional OCT technology obtains ultra-high resolution at the expense of a certain imaging range and cannot achieve full field of view imaging. In the early years, Time-domain full-field OCT (TD-FF-OCT) has been mainly used for ex vivo ophthalmic tissue studies, limited by the low speed and low full-well capacity of existing two-dimensional (2D) cameras. The recent improvements in system design opened new imaging possibilities for in vivo applications thanks to its distinctive optical properties of TD-FF-OCT such as a spatial resolution almost insensitive to aberrations, and the possibility to control the curvature of the optical slice. This review also attempts to look at the future directions of TD-FF-OCT evolution, for example, the potential transfer of the functional-imaging dynamic TD-FF-OCT from the ex vivo into in vivo use and its expected benefit in basic and clinical ophthalmic research. Through non-invasive, wide-field, and cellular-resolution imaging, TD-FF-OCT has great potential to be the next-generation imaging modality to improve our understanding of human eye physiology and pathology.

Extracting Group Velocity Dispersion values using quantum-mimic Optical Coherence Tomography and Machine Learning

Quantum-mimic Optical Coherence Tomography (Qm-OCT) images are cluttered with artefacts - parasitic peaks which emerge as a by-product of the algorithm used in this method. However, the shape and behaviour of an artefact are uniquely related to Group Velocity Dispersion (GVD) of the layer this artefact corresponds to and consequently, the GVD values can be inferred by carefully analysing them. Since for multi-layered objects the number of artefacts is too high to enable layer-specific analysis, we employ a solution based on Machine Learning. We train a neural network with Qm-OCT data as an input and dispersion profiles, i.e. depth distribution of GVD within an A-scan, as an output. By accounting for noise during training, we process experimental data and estimate the GVD values of BK7 and sapphire as well as provide a qualitative GVD value distribution in a grape and cucumber. Compared to other GVD-retrieving methods, our solution does not require user input, automatically provides dispersion values for all the visualised layers and is scalable. We analyse the factors affecting the accuracy of determining GVD: noise in the experimental data as well as general physical limitations of the detection of GVD-induced changes, and suggest possible solutions.

Towards retrieving dispersion profiles using quantum-mimic optical coherence tomography and machine learning

Artefacts in quantum-mimic optical coherence tomography are considered detrimental because they scramble the images even for the simplest objects. They are a side effect of autocorrelation, which is used in the quantum entanglement mimicking algorithm behind this method. Interestingly, the autocorrelation imprints certain characteristics onto an artefact - it makes its shape and characteristics depend on the amount of dispersion exhibited by the layer that artefact corresponds to. In our method, a neural network learns the unique relationship between the artefacts' shape and GVD, and consequently, it is able to provide a good qualitative representation of object's dispersion profile for never-seen-before data: computer-generated single dispersive layers and experimental pieces of glass. We show that the autocorrelation peaks - additional peaks in the A-scan appearing due to the interference of light reflected from the object - affect the GVD profiles. Through relevant calculations, simulations and experimental testing, the mechanism leading to the observed GVD changes is identified and explained. Finally, the network performance is tested in the presence of noise in the data and with the experimental data representing single layers of quartz, sapphire and BK7.

Ultrahigh resolution spectral-domain optical coherence tomography using the 1000-1600 nm spectral band

Ultrahigh resolution optical coherence tomography (UHR-OCT) can image microscopic features that are not visible with the standard OCT resolution of 5-15 µm. In previous studies, high-speed UHR-OCT has been accomplished within the visible (VIS) and near-infrared (NIR-I) spectral ranges, specifically within 550-950 nm. Here, we present a spectral domain UHR-OCT system operating in a short-wavelength infrared (SWIR) range from 1000 to 1600 nm using a supercontinuum light source and an InGaAs-based spectrometer. We obtained an axial resolution of 2.6 µm in air, the highest ever recorded in the SWIR window to our knowledge, with deeper penetration into tissues than VIS or NIR-I light. We demonstrate imaging of conduction fibers of the left bundle branch in freshly excised porcine hearts. These results suggest a potential for deep-penetration, ultrahigh resolution OCT in intraoperative applications.

Artefact-removal algorithms for Fourier domain quantum optical coherence tomography

Quantum Optical Coherence Tomography (Q-OCT) is a non-classical equivalent of Optical Coherence Tomography and is able to provide a twofold axial resolution increase and immunity to resolution-degrading dispersion. The main drawback of Q-OCT are artefacts which are additional elements that clutter an A-scan and lead to a complete loss of structural information for multilayered objects. Whereas there are very practical and successful methods for artefact removal in Time-domain Q-OCT, no such scheme has been devised for Fourier-domain Q-OCT (Fd-Q-OCT), although the latter modality-through joint spectrum detection-outputs a lot of useful information on both the system and the imaged object. Here, we propose two algorithms which process a Fd-Q-OCT joint spectrum into an artefact-free A-scan. We present the theoretical background of these algorithms and show their performance on computer-generated data. The limitations of both algorithms with regards to the experimental system and the imaged object are discussed.

Intensity correlation OCT is a classical mimic of quantum OCT providing up to twofold resolution improvement

Quantum Optical Coherence Tomography (Q-OCT) uses quantum properties of light to provide several advantages over its classical counterpart, OCT: it achieves a twice better axial resolution with the same spectral bandwidth and it is immune to even orders of dispersion. Since these features are very sought-after in OCT imaging, many hardware and software techniques have been created to mimic the quantum behaviour of light and achieve these features using traditional OCT systems. The most recent, purely algorithmic scheme—an improved version of Intensity Correlation Spectral Domain OCT named ICA-SD-OCT—showed even-order dispersion cancellation and reduction of artefacts. The true capabilities of this method were unfortunately severely undermined, both in terms of its relation to Q-OCT and its main performance parameters. In this work, we provide experimental demonstrations as well as numerical and analytical arguments to show that ICA-SD-OCT is a true classical equivalent of Q-OCT, more specifically its Fourier domain version, and therefore it enables a true two-fold axial resolution improvement. We believe that clarification of all the misconceptions about this very promising algorithm will highlight the great value of this method for OCT and consequently lead to its practical applications for resolution- and quality-enhanced OCT imaging.

Line field Fourier domain optical coherence tomography based on a spatial light modulator

In this study, we developed a line-field Fourier domain optical coherence tomography (LF-FDOCT) system that performs lateral scanning using a two-dimension spatial light modulator and detects multiple channels of spectral domain OCT signal in parallel using a two-dimensional sensor. The LF-FDOCT system eliminates the need for mechanical scanning to acquire volumetric OCT data. It allows parallel acquisition of signal for B mode scan imaging through snapshot detection and offers unprecedented flexibility to select a fast scanning dimension. In this work, we describe the principle of LF-FDOCT imaging and present experimental results to demonstrate the effectiveness of this technology.

Fourier domain quantum optical coherence tomography

Quantum optical coherence tomography (Q-OCT) is the non-classical counterpart of optical coherence tomography (OCT), a high-resolution 3D imaging technique based on white-light interferometry. Because Q-OCT uses a source of frequency-entangled photon pairs, not only is the axial resolution not affected by dispersion mismatch in the interferometer but is also inherently improved by a factor of two. Unfortunately, practical applications of Q-OCT are hindered by image-scrambling artefacts and slow acquisition times. Here, we present a theoretical analysis of a novel approach that is free of these problems: Fourier domain Q-OCT (Fd-Q-OCT). Based on a photon pair coincidence detection as in the standard Q-OCT configuration, it also discerns each photon pair by their wavelength. We show that all the information about the internal structures of the object is encoded in the joint spectrum and can be easily retrieved through Fourier transformation. No depth scanning is required, making our technique potentially faster than standard Q-OCT. Finally, we show that the data available in the joint spectrum enables artefact removal and discuss prospective algorithms for doing so.

Structural and Functional Sensing of Bio-Tissues Based on Compressive Sensing Spectral Domain Optical Coherence Tomography

In this paper, a full depth 2D CS-SDOCT approach is proposed, which combines two-dimensional (2D) compressive sensing spectral-domain optical coherence tomography (CS-SDOCT) and dispersion encoding (ED) technologies, and its applications in structural imaging and functional sensing of bio-tissues are studied. Specifically, by introducing a large dispersion mismatch between the reference arm and sample arm in SD-OCT system, the reconstruction of the under-sampled A-scan data and the removal of the conjugated images can be achieved simultaneously by only two iterations. The under-sampled B-scan data is then reconstructed using the classic CS reconstruction algorithm. For a 5 mm × 3.2 mm fish-eye image, the conjugated image was reduced by 31.4 dB using 50% × 50% sampled data (250 depth scans and 480 spectral sampling points per depth scan), and all A-scan data was reconstructed in only 1.2 s. In addition, we analyze the application performance of the CS-SDOCT in functional sensing of locally homogeneous tissue. Simulation and experimental results show that this method can correctly reconstruct the extinction coefficient spectrum under reasonable iteration times. When 8 iterations were used to reconstruct the A-scan data in the imaging experiment of fisheye, the extinction coefficient spectrum calculated using 50% × 50% data was approximately consistent with that obtained with 100% data.

Real-time high-resolution mid-infrared optical coherence tomography

The potential for improving the penetration depth of optical coherence tomography systems by using light sources with longer wavelengths has been known since the inception of the technique in the early 1990s. Nevertheless, the development of mid-infrared optical coherence tomography has long been challenged by the maturity and fidelity of optical components in this spectral region, resulting in slow acquisition, low sensitivity, and poor axial resolution. In this work, a mid-infrared spectral-domain optical coherence tomography system operating at a central wavelength of 4 µm and an axial resolution of 8.6 µm is demonstrated. The system produces two-dimensional cross-sectional images in real time enabled by a high-brightness 0.9- to 4.7-µm mid-infrared supercontinuum source with a pulse repetition rate of 1 MHz for illumination and broadband upconversion of more than 1-µm bandwidth from 3.58-4.63 µm to 820-865 nm, where a standard 800-nm spectrometer can be used for fast detection. The images produced by the mid-infrared system are compared with those delivered by a state-of-the-art ultra-high-resolution near-infrared optical coherence tomography system operating at 1.3 μm, and the potential applications and samples suited for this technology are discussed. In doing so, the first practical mid-infrared optical coherence tomography system is demonstrated, with immediate applications in real-time non-destructive testing for the inspection of defects and thickness measurements in samples that exhibit strong scattering at shorter wavelengths.

Recovering distance information in spectral domain interferometry

This work evaluates the performance of the Complex Master Slave (CMS) method, that processes the spectra at the interferometer output of a spectral domain interferometry device without involving Fourier transforms (FT) after data acquisition. Reliability and performance of CMS are compared side by side with the conventional method based on FT, phase calibration with dispersion compensation (PCDC). We demonstrate that both methods provide similar results in terms of resolution and sensitivity drop-off. The mathematical operations required to produce CMS results are highly parallelizable, allowing real-time, simultaneous delivery of data from several points of different optical path differences in the interferometer, not possible via PCDC.