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

Abstract

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.

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

“…1 a) is created with the algorithm in Ref. 9 : first a 1024 element-long spectrum is synthesised (at central wavelength of 840 nm, and with the total spectral bandwidth of 160 nm, a Gaussian profile and Gaussian noise, resulting in the axial resolution equal to 4.08 μm), then split into 50 fragments, which are then autocorrelated, zero-padded to be 2048 element-long and Fourier transformed. Half of a Fourier transform is taken, which means that the resultant signal size is 50 by 1024 elements.…”

“…Quantum-mimic Optical Coherence Tomography (Qm-OCT) achieves resolution enhancement and even-order dispersion cancellation by mimicking quantum entanglement found in Quantum OCT. Proposed theoretically in various forms, 1 – 3 Qm-OCT is realised experimentally by introducing modifications in the OCT detection setup 4 – 7 or simply by applying a computer algorithm to raw OCT spectra 8 , 9 . In principle, a Qm-OCT A-scan is obtained by Hilbert-transforming the spectrum, autocorrelating it and then performing Fourier transformation.…”

Two-fold resolution increase and all-depth linearization using a neural network

“…Current methods for removing depth-dependent dispersion rely on piece-wise phase corrections [3] or a priori knowledge of dispersion variability [4]. An approach showing partial immunity to nonlinearities in the spectrum and enabling resolution improvement is quantum-mimic OCT [5,6]. It allows the resolution increase of around √2 and the cancellation of even-order nonlinearities, leaving intact the third-order nonlinearitywhich becomes significant in deep OCT imaging.…”

Blind, all-depth dispersion compensation and blind spectral calibration

“…Current methods for removing such depth-dependent dispersion rely on piece-wise phase corrections [3] or a priori knowledge of dispersion variability [4] both very error-prone solutions. A blind all-depth linearisation is obtained in quantum-mimic OCT [5,6], but at the expense of artefacts and only for the even orders.…”