Techniques for improving capabilities of optical coherence tomography systems

Abstract

In some embodiments, a system for scanning a scene using optical coherence tomography (OCT) is provided. The system comprises a swept laser, a reference arm, a sample arm, a balanced photodetector, a computing device, and a digitizer. The digitizer is configured to receive output from the balanced photodetector and to provide digitized signals to the computing device as raw OCT interferometric signals. The computing device is configured to process the raw OCT interferometric signals to adjust for electrical dispersion by performing actions comprising: receiving, by the computing device, the raw OCT interferometric signals and a k-clock signal; determining, by the computing device, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k-shift; and sampling, by the computing device, the raw OCT interferometric signals using the adjusted k-clock signal.

Description

TECHNIQUES FOR IMPROVING CAPABILITIES OF OPTICAL COHERENCETOMOGRAPHY SYSTEMSCROSS-REFERENCE(S) TO RELATED APPLICATION(S)

[0001] This application claims the benefit of Provisional Application No. 63 / 664076, filed June 25, 2024, the entire disclosure of which is hereby incorporated by reference herein for all purposes.BACKGROUND

[0002] The development of optical coherence tomography (OCT) technology has evolved from time-domain to spectral domain implementations, eventually leading to the development of swept source configurations (SS-OCT). SS-OCT has gained prominence due to its capability of higher imaging speed and longer ranging distance, finding widespread applications including but not limited to biomedical imaging fields such as ophthalmology, endoscopy, dermatology, dentistry, and neuroscience, among others.

[0003] Recent technical advancements in SS-OCT have primarily focused on enhancing imaging speed and depth ranging. One motivation behind this trend is the growing demand in clinical medicine for rapid acquisition of high-quality images and the desire of biomedical research for observing tissue structures and functions over larger field of view. High-speed SS-OCT enables the efficient imaging of a broader range of tissue structures within a short timeframe, providing timely information to aid the clinical decision making. Moreover, the evolution towards wider fields of view (FoV) and longer ranging distance facilitates a more comprehensive understanding of physiological and pathological processes, proving valuable in applications such as comprehensive eye examinations, whole-brain vascular visualization in neuroscience, and large FoV skin imaging. Further dramatic improvements in FoV and ranging distance may also allow imaging of other types of scenes.SUMMARY

[0004] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0005] In some embodiments, a system for scanning a scene using optical coherence tomography (OCT) is provided. The system comprises a swept laser, a reference arm, a sample arm, a balanced photodetector, a computing device, a first fiber coupler configuredto divide output of the swept laser between the reference arm and the sample arm, a second fiber coupler configured to provide signals from the reference arm and the sample arm to the balanced photodetector, and a digitizer configured to receive output from the balanced photodetector and to provide digitized signals to the computing device as raw OCT interferometric signals. The computing device is configured to process the raw OCT interferometric signals to adjust for electrical dispersion by performing actions comprising: receiving, by the computing device, the raw OCT interferometric signals and a k-clock signal; determining, by the computing device, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k-shift; and sampling, by the computing device, the raw OCT interferometric signals using the adjusted k-clock signal.

[0006] In some embodiments, a computer-implemented method of scanning a scene using an optical coherence tomography (OCT) system is provided. A computing device receives raw OCT interferometric signals and transforms the raw OCT interferometric signals to a spatial domain to create spatial signals. The computing device extracts amplitude data from the spatial signals. The computing device produces a binary mask based on the amplitude data, and generates a representation of the scene based on the binary mask. In some embodiments, a non-transitory computer-readable medium having computer-executable instructions stored thereon is provided wherein the instructions, in response to execution by one or more processors of a computing device, cause the computing device to perform such a method. In some embodiments, a computing device configured to perform such a method is provided.

[0007] In some embodiments, a computer-implemented method of processing signals in an optical coherence tomography (OCT) system is provided. A computing device receives an OCT interference signal and a k-clock signal. The computing device determines a non-linear k-shift caused by electrical dispersion based on a depth. The computing device adjusts the k-clock signal based on the non-linear k-shift, and samples the OCT interference signal using the adjusted k-clock signal. In some embodiments, a non-transitory computer- readable medium having computer-executable instructions stored thereon is provided wherein the instructions, in response to execution by one or more processors of a computing device, cause the computing device to perform such a method. In some embodiments, a computing device configured to perform such a method is provided.

[0008] In some embodiments, a computer-implemented method of scanning a target in an optical coherence tomography (OCT) system is provided. A computing device determines a topology of the target. The computing device divides the target into segments based on thetopology. For each segment, the computing device adjusts the OCT system based on a depth of the segment, and causes the OCT system to scan the segment to create a segment rendering. The computing device combines the segment renderings to create a combined rendering of the target. In some embodiments, a non-transitory computer-readable medium having computer-executable instructions stored thereon is provided wherein the instructions, in response to execution by one or more processors of a computing device, cause the computing device to perform such a method. In some embodiments, a computing device configured to perform such a method is provided.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The foregoing aspects and many of the attendant advantages of this invention will become more readily appreciated as the same become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings, wherein:

[0010] FIG. 1 shows a schematic overview of a non-limiting example embodiment of a basic OCT system, according to various aspects of the present disclosure.

[0011] FIG. 2 is a schematic drawing that illustrates a non-limiting example embodiment of an OCT system configured to minimize the influence of non-linear frequency phase response in order to provide high-speed, long-distance ranging, and wide FoV capabilities, according to various aspects of the present disclosure

[0012] FIG. 3 is a flowchart that illustrates a non-limiting example embodiment of a method of processing signals in an OCT system, according to various aspects of the present disclosure.

[0013] FIG. 4A and FIG. 4B are charts that illustrate system sensitivity roll-off and axial resolution measurements of a 600 kHz SS-OCT system

[0014] FIG. 5A and FIG. 5B are charts that illustrate system sensitivity roll-off and axial resolution measurements of a non-limiting example embodiment of a 600 kHz SS-OCT system with k-clock calibration

[0015] FIG. 6 is a schematic drawing that illustrates a non-limiting example embodiment of an OCT system configured to more effectively generate images of targets having varying depth, according to various aspects of the present disclosure.

[0016] FIG. 7 is a flowchart that illustrates a non-limiting example embodiment of a method of scanning a target in an OCT system, according to various aspects of the present disclosure.

[0017] FIG. 8A illustrates imaging results of using a traditional long-range scan mode to image a human mouth, with focus adjusted to a position that was approximately located at the canine tooth.

[0018] FIG. 8B illustrates imaging results of using the ACTS technique described in FIG. 7.

[0019] FIG. 9 is a block diagram that illustrates a non-limiting example embodiment of a long-range SS-OCT system based on an akinetic swept-source laser, according to various aspects of the present disclosure.

[0020] FIG. 10 is a flowchart that illustrates a non-limiting example embodiment of a method of scanning a scene using an OCT system, according to various aspects of the present disclosure.

[0021] FIG. 11 illustrates a non-limiting example result of scanning a human subject in a hallway at distances incrementally ranging from 5 to 35 m, using the system illustrated in FIG. 9 and the techniques described in FIG. 10.

[0022] FIG. 12 illustrates a non-limiting example result of scanning within an uncontrolled outdoor environment using the system of FIG. 9 and the techniques of FIG. 10.

[0023] FIG. 13 is a block diagram that illustrates aspects of a non-limiting example embodiment of a computing device 1300 appropriate for use as a computing device of the various embodiments of the present disclosure.DETAILED DESCRIPTION

[0024] FIG. 1 shows a schematic overview of a non-limiting example embodiment of a basic OCT system, according to various aspects of the present disclosure. In the OCT system 100, coherent light is generated by a light source 104. The light is provided to a beam splitter 112, which directs a portion of the light to a sample arm 106 and another portion of the light to a reference arm 110. The sample arm 106 directs the light to a target 108 to be imaged, which may be an object, a scene containing multiple objects, or another suitable target 108.

[0025] Light is reflected from the target 108 and received by the sample arm 106. The reflected light is recombined with light from the reference arm 110 in order to create an interference pattern. The interference pattern is processed by a photodetector 114, which provides the resultant signals to a computing device 102 to create the OCT image. While FIG. 1 illustrates components of a generic OCT system 100, further details of specific OCTsystems that provide various improvements compared to existing systems are discussed below.K-Clock Calibration for Compensating for Electrical Dispersion

[0026] Recently, OCT has garnered significant attention for its application in imaging the oral cavity, owing to its capability of providing 3D microstructural and microcirculation information that can aid clinical assessments in dentistry. Notably, its non-radiative nature positions it as a safe imaging modality for oral cavity examinations in pregnant women and children. Moreover, OCT has demonstrated efficacy in detecting tooth demineralization and cavities by observing changes in backscattered signals from enamel and dentin. Even in the early stages of enamel demineralization, OCT excels in identifying the locations of white spot lesions. Additionally, OCT can be employed for diagnosing tooth fractures, manifesting as clear bright lines in OCT images. Enamel thickness, a reflection of tooth wear, can be quantified using OCT, offering a valuable tool for assessing enamel loss. Beyond hard tissues, OCT has shown applicability in examining soft tissues, addressing conditions such as gum diseases, oral mucosal lesions, and oral tumors.

[0027] Despite these successes, existing OCT systems in dentistry face challenges, primarily stemming from slow imaging speed and a limited imaging field of view (FoV). Additionally, the uneven topology of the oral cavity demands OCT to have a relatively long- ranging distance (>20mm). Currently, most existing OCT systems designed for dental applications have an A-scan rate typically ranging from 20 kHz to 200 kHz and a ranging distance of <12mm, providing a FoV generally smaller than 10^ 10 mm2that covers only one to two teeth. These limitations hinder the efficiency of data acquisition, impacting the workflow in imaging practice, especially in situations where a rapid overall visualization and examination of a patient's oral cavity is desired. An OCT system for dentistry should possess enhanced imaging capabilities, overcoming the current challenges. Therefore, it is desired that dental OCT includes: 1) improved imaging speed, which is desired for real-time clinical applications and patient comfort; 2) expanded field of view to capture comprehensive images of the entire oral cavity in a single scan, which facilitates more efficient and thorough examinations; and 3) increased ranging distance to cope with uneven surface topology in the oral cavity. Previous studies have attempted to achieve a large FoV by montaging multiple scans. Although this approach mitigates the oral curvature, it would prolong the time required to complete an imaging session, significantly affecting patient compliance for imaging.

[0028] Recently developed swept laser sources may be used to in an OCT system to help achieve oral cavity imaging with a wide FoV and long-ranging distance. For example, a 1310nm vertical-cavity surface-emitting laser (VCSEL) has been reported to achieve a cubic meter volume imaging for OCT applications. However, this previous technique utilized the assistance of a high-speed oscilloscope with a 16 GHz analog bandwidth that sampled the data at 50 GS / s and underwent post-data processing, neither of which are practical in a clinical setting.

[0029] Achieving fast scanning speed, long imaging range, and a wide FoV simultaneously in practice pose a significant challenge for current OCT hardware, particularly when considering electrical signal collection and handling. One reason is that the signals with high-frequency and high-bandwidth are difficult to deal with, including both the OCT interference signals of interest and the k-clock signal used to trigger data acquisition. As a note, the bandwidth mentioned here refers to the frequency range of the generated interference signal. To avoid confusion, the wavelength range of the light emitted by the laser source is referred to as spectral bandwidth, whereas the frequencies range of the interference signal is referred to as frequency bandwidth.

[0030] The signal handling hardware, including the photodetector 114, the transmission cables of the sample arm 106 and reference arm 110, and the computing device 102, typically assumes a linear frequency response within a designated frequency bandwidth. If the signal frequency is close to or beyond the limit of this bandwidth, a non-linear phase response would occur, introducing a time delay. The situation worsens for OCT signals because the spectral broadband swept source generates an interference signal with a frequency bandwidth that is consequently converted into a broadband electrical signal, imposing different time delays for different wavelengths. This process is akin to the optical dispersion phenomenon observed in OCT imaging. This electrical time delay is referred to herein as electrical dispersion when a high-frequency OCT signal with broad frequency bandwidth travels through the system hardware before being sampled by the data acquisition card. This electrical dispersion would inevitably affect the imaging performance of the OCT system.

[0031] Frequently when designing an OCT imaging system for most applications, for example retinal imaging where a ranging distance of 6 mm may be sufficient, the frequency bandwidth of the hardware may be adequate to cope with the OCT interference signals due to the use of the relatively short ranging distance. To digitally sample this OCT signal, an efficient way is to sample it in a linearized k-space through a k-clock triggering acquisition, facilitated by an auxiliary Mach-Zender interferometer (MZI). This is because compared tothe internal clock acquisition, this method eliminates the need for resampling interference spectrum signals of interest, reducing the burden on the acquisition card and simplifying post-data processing.

[0032] In this case, to properly generate the k-clock signal to trigger the sampling, the frequency of the MZI signal is required to be at least twice that of the OCT signal of interest (per Nyquist theorem), determined by the optical delay set at the MZI. This results in an expanded frequency bandwidth of the k-clock signal that likely goes beyond the designated frequency bandwidth for the hardware, leading to a noticeable phase shift for each sampling point (zero crossing point) due to the non-linear phase responses. Consequently, k-clock triggered acquisition would inevitably deteriorate the system imaging performance, e.g., broadening the system point-spread function, especially in the regions with long-ranging distances. As a result, minimizing the influence of non-linear frequency phase response is desired for developing high-speed, long-range, and wide FoV OCT imaging systems such as those used for oral cavity examination.

[0033] FIG. 2 is a schematic drawing that illustrates a non-limiting example embodiment of an OCT system configured to minimize the influence of non-linear frequency phase response in order to provide high-speed, long-distance ranging, and wide FoV capabilities, according to various aspects of the present disclosure. The system 200 provides a highspeed and long-range solution which may be applied to oral cavity examinations, while operating within the constraints of the existing computing device (i.e., without adding additional hardware such as a high-speed oscilloscope or significant post processing). This system 200 may operate at a scan speed of 600 kHz, providing a wide imaging field of 42x42 mm2and a ranging distance of 36 mm, effectively matching the physiological curvature of the oral cavity. To address the issue of k-clock non-linear phase errors, the system 200 uses a global k-clock calibration method to compensate for the electrical dispersion, which has been verified by the analyses of system sensitivity roll-off curve and point spread function before and after compensation. The system 200 may also compensate for spatial discrepancies resulting from long-range and wide-field imaging.

[0034] In the system 200, a swept laser 202 is used as the light source. One non-limiting example of a suitable swept laser 202 is a 600 kHz MEMS VCSELs swept laser source, centered at 1310 nm with 20 nm bandwidth. A swept laser source such as this may provide a theoretical axial resolution of approximately 41.5 pm in air (equivalent to -29.6 pm in tissue, assuming a refractive index of 1.4). In some embodiments, the swept laser 202 may include a built-in sweep trigger and linear k-clock, which may serve as the initiation signalfor an external clock to synchronize the interference fringes and subsequent data acquisition.

[0035] The output of the swept laser 202 is directed through a 90 / 10 fiber coupler 208, splitting 90% power to the sample arm, and allocating 10% to the reference arm. In the sample arm, the output of the fiber coupler 208 is coupled to a fiber collimator 224 via a circulator 214, generating a collimated beam. Any suitable device may be used for the circulator 214, including but not limited to a CIR-1310-50-APC Fiber Optic Circulator, provided by Thorlabs Inc. The collimated beam may have a diameter of approximately 2.8 mm. This collimated beam is then guided to the target 108 using a galvanometer 220 that includes a pair of synchronized galvo scanners triggered by a sweeping mechanism. A nonlimiting example of a suitable device for providing the galvanometer 220 is the Model 621 OH Galvanometer Optical Scanner, from Cambridge Tech Inc. The delivery of light to the target 108 is facilitated by a lens 222. Any suitable lens 222 may be used. In some embodiments, an f-theta lens with a 100 mm focus length may be used, which may achieve a lateral resolution of ~60 pm.

[0036] In the reference arm, the output of the swept laser 202 is directed from a polarization controller 210 to an optical delay line 212, which is employed to align the optical path difference between the sample arm and reference arm. The reference light from the optical delay line 212 and the backscattered light received from the circulator 214 from the circulator 214 are coupled to a 50 / 50 fiber coupler 216, and subsequently directed to a balanced photodetector 218.

[0037] To optimize the time delay between the trigger and k-clock, and to reduce the phase jitter arising from swept-to- swept variations, a function generator 206 is employed to introduce a controlled delay to the swept trigger signal. Though not illustrated, the interference signal is sampled by a digitizer to provide the sampled signals to the dispersion adjustment computing device 204 for processing. In some embodiments, a digitizer such as a 1.8 GHz digitizer with a designed frequency bandwidth from DC to 0.8 GHz may be used. A non-limiting example of a suitable digitizer is the ATS9360 digitizer provided by AlazarTech Inc. In some embodiments, the electrical cable layout may make the signal frequency bandwidth of the system 200 dominated by the digitizer employed, meaning the system frequency bandwidth may also be from DC to 0.8 GHz (matching the frequency bandwidth of the digitizer).

[0038] In a non-limiting example embodiment, the designed ranging distance of the system 200 may be 18mm in the air, given an MZI with a 72 mm optical path difference (OPD) andthe digitizer operating at single edge sampling mode. With this ranging distance, the laser operating at 600 kHz, and 20nm spectral bandwidth would generate a highest frequency OCT interference signal at maximum ranging distance that is estimated to have an averaged frequency of ~0.5 GHz and a frequency bandwidth of -0.4 GHz. While such a signal would likely experience electrical dispersion when it travels from the detector to the digitizer, the effect may be negligible because the signal frequency bandwidth of interest is well within the capacity of the system frequency bandwidth of 0.8 GHz. This is likely a reason why prior SS-OCT system developments reported in the literature did not notice the electrical dispersion issue. However, it may not be true when handling the MZI interference signals to generate k-clock signals for triggering the data acquisition. In order to increase the ranging distance with the k-clock signal generated by the MZI with a fixed OPD of 72 mm, the digitizer in the system 200 may be operated using a dual edge sampling (DES) mode. This DES sampling may lead to an actual imaging range of 36 mm, compared to the originally designed 18 mm.

[0039] FIG. 3 is a flowchart that illustrates a non-limiting example embodiment of a method of processing signals in an OCT system, according to various aspects of the present disclosure. In the method 300, techniques for minimizing the influence of non-linear frequency phase response are used by an OCT system such as system 200 to generate a rendering of a target 108.

[0040] From a start block, the method 300 proceeds to block 302, where a dispersion adjustment computing device 204 receives an OCT interferometric signal and a k-clock signal. While present discussion is equally applicable to the OCT interference signals, the discussion focuses on the k-clock signal generation and the effect of its non-linear phase response on imaging performances for the sake of brevity.

[0041] In conventional SS-OCT systems, a k-clock trigger signal is commonly employed to clock the acquisition of the interference signal in order to mitigate the mechanical sweep- to-sweep variations inherent in VCSEL’s operation. The k-clock trigger signal is typically generated by an auxiliary MZI with a predetermined OPD, tailored to the specific requirements of the system design. Subsequently, a zero-crossing detector is employed to convert the MZI interference signal into the k-clock signal, aligning its frequency with that of the MZI signal.

[0042] The mathematical representation of the MZI signal, characterized by an OPD of AZ MZI, is:Equation 1 where S(k) represents the laser source power spectrum, and k indicates the wavenumber. Consequently, the generated k-clock frequency (fcik can be expressed as:Equation 2 where 3k denotes the sweep rate of wavenumber during the laser source operation.Assuming an ideal linear wavenumber change in the time domain, 3k is given by:Ak • fsweep 2nAk sweepO fck= -Dkc2DEquation 3 where Ak is the variation in k within a sweep, fsweePis the sweep rate of the laser source, D is the sweep duty cycle (typically ranging from 0.3 to 0.7), Ak is the optical wavelength bandwidth, and kcis the central wavelength. Thus, considering a linear sweep of wavenumber, the expression for an averaged fcik becomes:Equation 4 where the generated k-clock trigger would be a signal with its frequency proportional to MZI OPD ( ZMZI), spectral bandwidth (Ak), and laser sweep rate (fsweep).

[0043] In practical applications, achieving a perfectly linear sweep of wavenumber in the time domain poses challenges due to the mechanical tuning of the mirror in the MEMS VCSEL laser source. The inherent nonlinear wavenumber sweep over time is unavoidable. Assuming a deviation range of Bk (i.e., the frequency bandwidth of 3k), the frequency of the k-clock signal would also vary within a specific range according to Equation 2, referred to as the k-clock frequency bandwidth, which is scaled with the MZI OPD that determines the OCT ranging distance.

[0044] For example, for the system 200, if an OPD is set to 36 mm, each interference spectrum can theoretically generate a k-clock trigger signal with an average frequency of~0.5 GHz, under a linear wavenumber sweep rate with a setting of Zlz = 20 nm, Ac = 1310 nm, sweep = 900 kHz and D = 0.5. However, the change in wavenumber is nonlinear in the time domain, leading to an estimated k-clock frequency bandwidth of -0.4 GHz. Transmitting a k-clock signal through the electronic devices in the system 200 introduces frequency-dependent phase instability due to the nonlinear phase response of the electronic devices, including the transmitting electrical cables. Essentially, the higher the k- clock frequency bandwidth produced by each MZI interference spectrum, the greater the phase error would be. This phase instability may not be noticeable when the ranging distance is relatively short, as in conventional system setups where the ranging distance is typically less than 12 mm, simply because they are within the capability of the system frequency bandwidth.

[0045] In systems such as the system 200 that are tailored for applications involving uneven surfaces, including but not limited to dental imaging, maximizing the measurement range may include generating as many k-clock trigger signals as possible for each MZI interference spectrum. Consequently, the optical path difference in the MZI in the system 200 may be set to 72 mm, theoretically generating 920 trigger signals per interference spectrum (though a lower number of trigger signals, such as 850, may actually be available). At this limit, each interference spectrum can theoretically generate an average frequency of -1 GHz k-clock trigger signals, with a frequency variation range from 0.5 to 1.3 GHz (beyond the system bandwidth of DC to 0.8GHz). Under this circumstance, electrical dispersion would occur, leading to a non-linear phase error in the acquired interference signals, which would degrade OCT imaging performance.

[0046] FIG. 4A and FIG. 4B are charts that illustrate system sensitivity roll-off and axial resolution measurements of the 600 kHz SSOCT system: (A) without optical dispersion compensation and (B) with optical dispersion compensation. Shown are the point spread functions (PSFs) measured at each ranging distance that are plotted with different shades, and the dash lines with circle markers show the corresponding axial resolution measured by the FWHM of the PSFs using gaussian fitting.

[0047] To visually demonstrate the impact of k-clock phase errors on the system, reflection signals were collected at various depths using a mirror as the sample, with the implementation of a 52 dB attenuator to mitigate strong reflections. In FIG. 4A, the measured point spread function (PSF) roll-off curve across the 36 mm ranging distance, employing the MZI- generated k-clock for triggering and DES sampling, is depicted, where an average SNR is approximately 97.7 dB. The PSF exhibits a relatively symmetrical profile with a narrow peak within a ranging distance of less than 10 mm, attributed to negligible phase errors fromelectrical dispersion for low-frequency interference signals. However, with the increase of the ranging distance, the PSF tends to broaden asymmetrically, accompanied by an elevation of side lobes on the left. This phenomenon primarily arises from the same phase drift but results in a larger phase difference in the high-frequency signal region. The axial resolution, assessed by the full width at half maximum (FWHM) of the PSF marked by black dots, experiences a gradual decline within the initial 16 mm of the ranging distance, followed by a rapid deterioration beyond this point. This decline significantly impacts the performance of the OCT system, particularly in capturing images beyond 16 mm, leading to diminished image quality as the ranging distance increases. In essence, the nonlinear phase effect in the generated k-clock signal begins to affect the acquired OCT signal around a ranging distance of approximately 16 mm (with an average frequency of ~0.4 GHz). Interestingly, this value coincides with half of the frequency bandwidth of the system, which warrants further investigation.

[0048] While the OCT interference signal is sampled in a linear k-space, there may still be residue of optical dispersion effect in the acquired interferogram. For this reason, numerical optical dispersion compensation methods are sometimes used to further minimize this effect on the PSF performance. After employing the numerical optical dispersion compensation, the PSF performance (FIG. 4B) is improved, but only within a narrow imaging range of less than 11 mm. The system sensitivity -3 dB roll-off is improved from 7 mm to 11 mm. The SNR has increased from 97.7 dB to 98.1 dB. However, it does not yield a global improvement in the PSF performance, particularly at deeper-ranging distances, where the effect of electrical dispersion in the generated k-clock signal gradually becomes non-negligible in the sampled interference signal of interest.

[0049] Accordingly, at block 304, the dispersion adjustment computing device 204 determines a non-linear k-shift caused by electrical dispersion based on a depth to rectify the nonlinear phase shift in the k-clock signal and improve the PSF performance throughout the entire ranging distance. In some embodiments, a polynomial equation may be used to model and compensate for the nonlinear phase error.

[0050] Considering an OCT signal from mirror in air at depth z as I(k)= S(k)cos((pz), the phase evolution of the interference signal can be expressed as:Equation 5where z represents the depth, k is the wavenumber, ko denotes the central wavenumber, Ak. ko signifies the nonlinear k shift at the wavenumber of (k- ko), aurepresents the optical dispersion coefficients, and v is the highest dispersion order. The first term of the equation accounts for a linear k-clock induced phase component, and the second term represents a nonlinear k shift induced component, both of which are depth related. The last term accounts for phase distortion from the optical dispersion of the system 200, which is approximately depth independent.

[0051] To accurately model the nonlinear k shift, the optical dispersion-induced phase error may be computed by the difference of the phase evolution from a mirror at two adjacent positions:Equation 6 where 4z12= zx— z2. To determine the k shift, a polynomial equation was employed to approximate the change in k with 4k-ko=Cp(k — k0)p, where Cprepresents / ?-order coefficients, and m is the highest order. To optimize across the entire ranging distance from multiple measurements, the minimum phase residual:Loss=Equation 7 is utilized as the merit function to find a globally optimized nonlinear k shift vector, A six-order polynomial curve may be employed to fit the electronic phase frequency response from three measurements, but in other embodiments, polynomials of other orders may be used.

[0052] At block 306, the dispersion adjustment computing device 204 adjusts the k-clock signal based on the non-linear k-shift. In some embodiments, the non-linear k-shift may be subtracted from the raw k vector to adjust the k-clock signal to eliminate the impact of the nonlinear k-shift.

[0053] At optional block 308, the dispersion adjustment computing device 204 further adjusts the k-clock signal based on one or more of a linear k-shift based on the depth or an optical dispersion k-shift. In some embodiments, the linear k-shift based on the depth and / orthe optical dispersion k-shift may be determined as listed in Equation 5, and the k-clock signal may be adjusted by further subtracting these values from the raw k vector.

[0054] At block 310, the dispersion adjustment computing device 204 samples the OCT interferometric signal using the adjusted k-clock signal. By sampling the OCT interferometric signal using the adjusted k-clock signal instead of with the traditional, unadjusted signal, performance of the system 200 is improved.

[0055] At block 312, the dispersion adjustment computing device 204 generates a rendering of a target 108 based on the sampled OCT interferometric signal. In some embodiments, the rendering may be an A-mode or B-mode scan of the target 108 that is presented on a display associated with the dispersion adjustment computing device 204. In some embodiments, the rendering may be stored by the dispersion adjustment computing device 204 for later use or reference.

[0056] The method 300 then proceeds to an end block and terminates.

[0057] FIG. 5A and FIG. 5B are charts that illustrate system sensitivity roll-off and axial resolution measurements of a non-limiting example embodiment of a 600 kHz SS-OCT system with k-clock calibration: (A) without optical dispersion compensation and (B) with optical dispersion compensation. The system point spread functions (PSFs) measured at each optical delay are plotted with different shades, and the dash lines with circle markers show the corresponding axial resolution measured by the FWHM of the PSFs using gaussian fitting.

[0058] Upon applying the k-clock calibration method as described above, a notable enhancement in the PSF performance was achieved, as depicted in FIG. 5A. The measured FWHM of the PSF exhibits a consistently flat profile across the entire ranging distance, resulting in a mean resolution of 42.3 pm (close to theoretical value of 41.5 pm). The average SNR increased from 97.7 dB to 101 dB. In contrast to the PSF roll-off without calibration (FIG. 4A), the -3 dB roll-off distance is expanded from 7 mm to 18 mm, while the total sensitivity remains consistently above 104.9 dB throughout the -3 dB roll-off distance postcompensation. These improvements in PSF performance and sensitivity demonstrate the effectiveness of the k-clock compensation in enhancing the imaging capabilities of the OCT system. When combined with optical dispersion compensation, the PSFs roll-off closely resembles its profile prior to dispersion compensation, with a very slight axial resolution improvements in longer ranging distances (FIG. 5B). The improvement in SNR is also no longer significant. This observation further attests to the fact that the phase error originatingfrom k-clock nonlinearity, attributed to electrical frequency responses, is effectively addressed by the proposed compensation process.Adaptive Contour Tracking

[0059] While it is desirable to use OCT imaging for targets 108 that have varying depth, one problem is that OCT imaging quality deteriorates with the increase of depth, particularly in the case of large-field imaging. The primary factors affecting OCT imaging quality at the system level are defocus and system sensitivity roll-off. Defocus occurs when the sample is not near the focal plane, while sensitivity roll-off affects the imaging quality when the sample is located too far from the zero-path difference plane. In wide-field imaging, samples are more likely to be away from the focal plane or zero path difference plane, especially with irregularly shaped samples such as a gum-line in the oral cavity. As a result, some imaged regions may appear blurred due to either the defocus effect or the tissue region of interest being located at relatively deep imaging positions.

[0060] To address these challenges, OCT systems are desired with high-speed, long-range, and wide-field capabilities that also maintain excellent image quality at larger ranging depth positions. Some studies have explored improving image quality at deeper positions by optimizing the optical system, such as using longer focal length objective lenses (lower numerical aperture) for an increased confocal depth. However, this approach trades lateral resolution for confocal depth. Other methods focus on reducing system sensitivity roll-off by optimizing the OCT data acquisition mode, mitigating sensitivity drop caused by k-clock nonlinearity in high-speed and long-ranging modes. While these methods can reduce the rate of sensitivity drop, they do not eliminate system sensitivity roll-off. Commercial OCT systems often employ autofocus devices to find the optimal focal plane for imaging, using mechanical methods to adjust the focal plane. However, this process is typically slow. Using a movable probe to adjust the distance or angle between the probe and the sample can enhance image quality, but this method is impractical when the distance cannot be freely adjusted and may introduce motion artifacts.

[0061] The introduction of tunable lenses has attempted to address these issues. Acoustooptic tunable lenses (AOTL) and electrically tunable lenses (ETL) are widely used in OCT to optimize imaging quality. AOTL achieves focal adjustment by inducing changes in refractive index through sound waves, while ETL adjusts the lens shape and curvature by altering the electric field. Studies have utilized tunable lenses to scan multiple times at the same B-scan position, adjusting focal length during each scan and fusing the resulting images to obtain final high-quality images across the entire depth range. However, thismethod significantly increases the imaging time and the data volume that the system and computing device must handle. Other studies have reported imaging samples by searching and selecting the optimal focal length throughout the entire focal range, but real-time focus adjustment significantly extends data acquisition time.

[0062] Although tunable lenses can alleviate defocusing effects, system sensitivity roll-off remains an issue, especially at relatively long-ranging distances where sensitivity loss can exceed 20 dB, affecting the efficient identification of tissue structures of interest and blood flow signals at deeper positions. Simultaneously adjusting both the focus and optical pathlength difference between reference and sample arms, allowing the effective imaging window to adapt along the sample surface contour, may offer further opportunities for improving image quality at different depths. This adaptive contour-tracking and scanning (ACTS) strategy, based on dual adjustment of focus and optical delay line, does not require changes in spatial distance between the system and the sample, overcoming some limitations above and reducing motion artifacts. However, it has not yet been reported in wide-field SS-OCT, and its performance improvements and challenges in practice remain unknown.

[0063] In some embodiments of the present disclosure, a realization of an ACTS method through the automatic and joint control of ETL in the sample arm and adjustable optical delay line (AODL) in the reference arm is provided. The disclosed techniques partition the entire system's ranging distance into several segments determined by the confocal length of the SS-OCT system. The surface contour within a large FoV of the sample is acquired, such as by rapid pre-scanning in the slow scan direction. The system then analyzes the surface variations and generates a personalized scanning protocol. Subsequently, the system uses a shorter ranging mode to adaptively image along the surface contour in the defined segments, employing multiple confocal functions to eliminate unevenness in image signal intensity caused by multiple focuses.

[0064] FIG. 6 is a schematic drawing that illustrates a non-limiting example embodiment of an OCT system configured to more effectively generate images of targets having varying depth, according to various aspects of the present disclosure. The illustrated OCT system 600 is constructed to conduct the ACTS strategy described in further detail below. As shown, the OCT system 600 uses a swept laser 602 operating at 600 kHz, with a central wavelength of 1310 nm and a 20 nm optical bandwidth, theoretically providing an axial resolution of approximately 41 pm in air. The output of the swept laser 602 is split 99: 1 to power both the OCT imaging system (99%) and an auxiliary Mach-Zehnder interferometer (MZI, 1%) that is used to generate a k-clock signal for OCT signal acquisition. The 1%output is provided to a fiber coupler 624, which splits the output between an optical delay line 626 and a polarization controller 628 before the signals are provided by a coupler 632 to a balanced photodetector 616 in order to generate the k-clock trigger signal. The optical path difference (OPD) established by the optical delay line 626 in the MZI may be set at an appropriate amount, such as 72 mm. With the use of single-edge and double-edge sampling modes, the ranging distance of the OCT system 600 is 18 mm (short range mode) and 36 mm (long range mode), respectively. The OCT system 600, as illustrated, is designed to interchangeably employ single-edge and dual-edge sampling modes when triggering and capturing the OCT interference signals of interest, where the short ranging mode significantly reduces the data volume that must handle, a consideration for large field of view imaging.

[0065] As illustrated, a 90: 10 fiber coupler 606 splits the received output of the swept laser 602 into the reference arm (10%) and the sample arm (90%). In the sample arm, the light passes through a circulator 612 and is collimated using a fiber collimator 622, generating a collimated beam with a diameter of approximately 2.8 mm. This beam traverses an electrically tunable lens 630 (Opotune Ltd) before being directed to a galvanometer 618. Any suitable device may be used for the electrically tunable lens 630, such as an electrically tunable lens obtained from Opotune Ltd. The response time of such a device may be 2.5 ms, with a stabilization time of 15 ms. A further lens 620, such as an f-theta lens with a focal length of 100 mm, is employed in the sample arm to achieve a large FoV of up to 42x42 mm.

[0066] In the reference arm, an electrically adjustable optical delay line 610 (AODL) receives the output of the swept laser 602 via a polarization controller 608, and is used to align the optical pathlength with that of the sample arm. The response speed of the adjustable optical delay line 610 may be 6 mm / s. The backscattered light from the target 108 is directed from the circulator 612 to a 50:50 beam splitter and combined is with the light from the reference arm by a fiber coupler 614. The optical interference signal is converted to electrical signals by a balanced photodetector 616. The resulting signals output by the balanced photodetector 616 may be processed and collected using a digitizer (e.g., ATS 9630, AlazarTech, Canada), and is provided along with the k-clock trigger signal and a sweep trigger signal to a controller computing device 604 for processing. To ensure synchronized data collection, all hardware components, including the electrically tunable lens 630, the galvanometer 618, the adjustable optical delay line 610, and the digitizer, may be synchronized using the laser sweep trigger and controlled through a customized Lab View program, including the procedures described below.

[0067] FIG. 7 is a flowchart that illustrates a non-limiting example embodiment of a method of scanning a target in an OCT system, according to various aspects of the present disclosure. The method 700 uses Adaptive Contour-Tracking Scanning (ACTS) to improve the imaging results. ACTS enables the OCT system 600 to adaptively adjust the focal position relative to the target 108. This is achieved by altering the focal position of the electrically tunable lens 630 during imaging, in conjunction with adjusting the adjustable optical delay line 610 in the reference arm to ensure portion of the target 108 being scanned falls within the effective OCT imaging window. This adjustment is facilitated by near realtime feedback from surface contour information, initially obtained through a rapid pre-scan of the target 108. This strategy allows the effective OCT imaging window to follow changes in the contour of the target 108, optimizing image quality within a wide FoV. The effective OCT imaging window refers to the imaging depth range defined by the confocal depth of the OCT system 600, over which range the lateral resolution remains relatively constant.

[0068] From a start block, the method 700 proceeds to block 702, where a controller computing device 604 determines a topology of the target 108 using a fast surface profiling technique. The controller computing device 604 may use any any suitable technique for determining the topology of the target 108. In some embodiments, the controller computing device 604 may determine the rough surface contour of the target 108 by using the OCT system 600 to perform a sparse scan of the target 108 along the slow scan direction (e.g., approximately 0.1 sec for 20 B-frames) using the long range scanning mode (e.g., 36 mm). The controller computing device 604 may process the pre-scans by removing isolated points, thus yielding slow-axis B-scans from which the surface contour may be extracted.

[0069] The use of the OCT system 600 to determine the topology of the target 108 may be desirable because it does not use additional hardware beyond that being used for the OCT imaging. However, in some embodiments, other techniques may be used to determine the topology of the target 108. For example, a structured light three-dimensional scanner, a stereoscopic camera, and / or a depth camera that uses time-of-flight sensors may be used to determine the topology of the target 108.

[0070] At block 704, the controller computing device 604 divides the target 108 into segments based on the topology. Typically, the controller computing device 604 uses the confocal depth of the OCT system 600 (the Rayleigh length) to divide the target 108 into segments, such that the surface contour remains within the confocal depth within each segment.

[0071] The method 700 then proceeds to a for-loop defined between a for-loop start block 706 and a for-loop end block 712, wherein each of the segments are processed. Typically, the segments may be arranged in depth order, such that the adjustable portions of the OCT system 600 can be adjusted in small increments instead of jumping between widely different positions. However, in other embodiments, the segments may be processed in any order.

[0072] From the for-loop start block 706, the method 700 proceeds to block 708, where the controller computing device 604 adjusts the OCT system 600 based on a depth of the segment. The controller computing device 604 adjusts the focal length and the adjustable optical delay line 610 based on the depth of the current segment in order to maintain high resolution throughout the entire depth range. In some embodiments, at block 708 the controller computing device 604 may transmit signals that stop driving the galvanometer 618 in the slow scan direction, and that drive the electrically tunable lens 630 and the adjustable optical delay line 610 to positions that correspond to the depth of the current segment. The control signal that stops driving the galvanometer 618 in the slow scan direction may be transmitted to pause scanning in the slow scan direction for an amount of time that it takes the electrically tunable lens 630 and the adjustable optical delay line 610 to adjust to the new position. After the amount of time, the controller computing device 604 may return to transmitting signals that drive the galvanometer 618 in the slow scan direction.

[0073] At block 710, the controller computing device 604 causes the OCT system 600 to scan the segment to create a segment rendering. The OCT system 600 scans the segment by having the galvanometer 618 scan in both the fast scan direction and the slow scan direction to gather interference signals within the segment.

[0074] The method 700 then proceeds to the for-loop end block 712. If further segments remain to be processed, then the method 700 returns from for-loop end block 712 to for- loop start block 706 to process the next segment. Otherwise, if all of the segments have been processed, the method 700 advances to block 714.

[0075] At block 714, the controller computing device 604 combines the segment renderings to create a combined rendering of the target 108. At each segment, the reflected light strength along the depth can be affected by the system confocal function. Accordingly, in some embodiments, the confocal functions at each segment are used to compensate for the light strengths in the OCT images to create the final compensated wide field OCT image. The confocal function, A(z), and the Raleigh length, zR, may be described as:Equation 9 where z represents depth, meacured in millimeters, m represents the depth-segment number, zfmdenotes the focus position, a is used to distinguish specular reflection («=1) from diffuse reflection («=2), n is the refractive index, AXmis the lateral resolution, and 2 is the central wavelength of the light source.

[0076] The method 700 then proceeds to an end block and terminates.

[0077] The method 700 was compared to the use of conventional OCT scanning protocols for imaging the human mouth. FIG. 8A illustrates imaging results of using a traditional long-range scan mode to image a human mouth, with focus adjusted to a position that was approximately located at the canine tooth. Section 1 of FIG. 8 A shows the volumetric structural information, and Section 2 of FIG. 8 A shows the microvascular information. The scan field of view was 42mm x 42mm, covering upper and lower right quadrant of the total 12 teeth, where there is a significant curvature in the gumline. The imaging time for structural scan alone was 4.75 sec, and that for both structural and blood flow imaging (OCTA scan protocol) was 19 sec. It is apparent that the image quality for both the structural and blood flow OCT images decreases with the increase of ranging distance, where the contrast at the regions near molar teeth are diminishing (pointed by white arrows). In addition, the vessels appeared blurred due to the defocus of the OCT beam at those regions. This is because the regions near molar teeth are located away from the focal and zero-delay line planes, causing blurring and reduced contrast and signal strength in the final images. For better scrutinizing the results, the microvascular image is zoomed for upper (Section 3) and lower gum (Section 4) regions, where the challenges of wide field of view imaging of uneven samples are clearly appreciated.

[0078] In contrast, ACTS OCT maintains high resolution and signal strength throughout the entire FoV. FIG. 8B illustrates imaging results of using the ACTS technique described in FIG. 7. Section 1 of FIG. 8B shows the volumetric structural information, and Section 2shows the microvascular information, with Sections 3 and 4 showing the zoomed in regions of the upper and lower gum regions, respectively. As shown, the issues observed in the conventional scan protocol are mostly mitigated.

[0079] Such wide field imaging could be useful in aiding the clinical diagnosis of oral diseases. For example, OCT structural information may be used to detect tooth structures, including enamel and dentin, aiding in the detection of pathologies such as caries, tooth fractures, and enamel wear. OCTA image provides information about the gingival vascular system, which may be used to assess the blood flow in the gums, improving understanding of inflammation, gum diseases, and blood flow recovery after gum repair surgeries. It may also be envisioned that OCT can be used in conjunction with other imaging modalities, for example 3 -shape topological tool or simply a camera image, to provide complementary information in aiding clinical decision making. In this case, OCT images may be fused together with the images provided by other imaging technologies to present to dentists for better analysis of the relationships between topology, microstructural and microvasculature within the oral cavity.

[0080] Another advantage of the ACTS strategy is the adaptive adjustment of the imaging window along the sample contour, which offers the potential to achieve an extended working range with a reduced system-ranging distance. Each incremental scan uses only half of the spectral sampling rate to meet the requirements. The OCT system 600 adopts the k-clock triggering acquisition method. Without compromise of the performance in k-clock acquisition card, there is a competitive mechanism among sweep speed, bandwidth, and spectral sampling rate, which correspond to OCT parameters such as imaging speed, axial resolution, and imaging range. If the short-range mode is used, the burden on spectral sampling rate is relaxed. The released parameter space can then be utilized by the other two parameters. In other words, the system can choose a swept laser 602 with a faster sweep speed or a wider bandwidth to improve imaging speed and axial resolution. Additionally, the reduction in spectral sampling rate means an increase in data transfer speed, saving storage space and computational power.Using OCT for Long Range Volumetric Imaging and Metrology

[0081] The growing demand for high-resolution, non-contact measurement technologies in industrial metrology, robotic perception, and environmental mapping has created a unique opportunity for OCT to contribute beyond its biomedical roots. OCT offers distinct advantages over conventional ranging and imaging techniques such as LIDAR and radar, including superior axial resolution, immunity to ambient light, and coherent phasesensitivity. These capabilities make long-range OCT a promising candidate for 3D surface profiling, precision inspection, and autonomous system integration.

[0082] Conventional OCT systems — particularly those based on spectral-domain (SD) architectures — are fundamentally constrained by their reliance on broadband light sources and spectrometer-based detection. These systems suffer from limited spectral resolution, sensitivity roll-off, and nonlinear k-space sampling, resulting in imaging depths typically limited to a few millimeters. Consequently, SD-OCT is best suited for small, relatively flat biological specimens, and is generally unsuitable for imaging extended structures or large- volume objects.

[0083] The emergence of swept-source OCT (SS-OCT) has markedly expanded the performance envelope of OCT systems. By replacing the broadband source and spectrometer with a tunable narrow-linewidth laser and balanced photodetector, SS-OCT achieves higher imaging speeds, extended coherence lengths, and improved detection sensitivity. These features have not only enhanced performance in traditional biomedical applications but have also laid the foundation for extending OCT into domains requiring long-range, high-precision, non-contact imaging. However, widely available swept-source lasers have not typically had sufficient performance to support a depth and width useful for imaging large environmental scenes.

[0084] Recent breakthroughs in swept-source laser design — particularly the development of akinetic all-semiconductor lasers such as Vernier-tuned distributed Bragg reflector (VT- DBR) sources — have enabled OCT systems with coherence lengths exceeding 17 cm, ultra-linear k-space tuning, and high phase stability. These advances support meter-scale imaging ranges and wide fields of view, making volumetric imaging of large, complex targets feasible. Demonstrations of facial and mannequin imaging, as well as video-rate 3D mapping of dynamic scenes, underscore the potential for OCT to transition from microscopic to macroscopic applications.

[0085] FIG. 9 is a block diagram that illustrates a non-limiting example embodiment of a long-range SS-OCT system based on an akinetic swept-source laser, according to various aspects of the present disclosure. The OCT system 900 is engineered to achieve extended imaging ranges with high spatial resolution and signal stability. The OCT system 900 is capable of performing high-resolution volumetric imaging over centimeter- to hundredmeter-scale depths, thus being applicable to non-contact metrology and large-scale 3D imaging. By bridging the gap between biomedical imaging and optical metrology, the OCTsystem 900 provides a flexible and powerful imaging platform for diverse scientific and engineering applications.

[0086] To support long-range imaging, the design of the OCT system 900 leverages the unique benefits of swept-source OCT (SS-OCT) and the extended coherence length of akinetic laser sources. The fundamental signal detected by a photodetector for a single reflector configuration can be described by the time-varying interference of the reference and sample beams. Assuming a linear sweep in wavenumber (k-space), the detected interferometric signal takes the form of a modulated cosine whose frequency is proportional to the optical path length difference between the sample and reference arms. The axial resolution, 5z, is inversely proportional to the source bandwidth, while the imaging range is determined by the digitizer's sampling rate and the sweep speed of the laser.

[0087] Assuming a Gaussian spectral profile, the axial resolution is given by:2 In 2 n6z = -71 4A

[0088] where Ao is the center wavelength and AA is the spectral bandwidth. The frequency of the interferometric fringe, and hence the maximum imaging range zmax, is limited by the Nyquist criterion to:

[0089] Here, n is the refractive index (assumed to be unity in air), / is the sampling frequency of the digitizer, At is the effective sweep time for each A-line, and AZ is the total sweep range in wavelength-space. This relation illustrates the trade-off between imaging range and spectral bandwidth: narrower sweeps enable longer imaging ranges but reduce axial resolution. For a system operating at a center wavelength of 1550 nm and an effective sweep time of 10 ps, reducing the sweep bandwidth to ~0.1 nm permits imaging depths of tens of meters with moderate sampling rates. However, excessive narrowing of the spectral bandwidth may limit axial resolution and photon budget, suggesting a balance based on application needs.

[0090] In FIG. 9, an OCT system 900 is illustrated that uses an akinetic swept laser 902 as a light source 104. In a tested embodiment, the akinetic swept laser 902 utilized was an akinetic all -semi conductor laser operating at a center wavelength of 1550 nm with a sweep rate of 50 kHz, driven by a 600 MHz clock, provided by Insight Photonic Solutions. Thisakinetic swept laser 902 provides precise electrical trigger signals and clocks for synchronizing the galvanometer 916 and digitizer 922 for accurate data acquisition. This akinetic swept laser 902 also offers an ultra-narrow instantaneous linewidth of less than 0.6 MHz, translating into an exceptionally long theoretical coherence length exceeding 200 m. This coherence length inherently allows imaging at distances up to approximately 200 m, provided that suitable hardware support is available. In the tested embodiment, due to practical hardware constraints — primarily sample beam divergence and limitations in the sampling rate of the digitizer 922 — a maximum imaging range was demonstrated of approximately 53 m. The spectral bandwidth of the tested akinetic swept laser 902 was approximately 0.09 nm, yielding an axial resolution of around 1.18 cm. In other embodiments, other types of akinetic swept lasers 902 may be used.

[0091] The output of the akinetic swept laser 902 is split by a 90 / 10 fiber coupler 906, directing 90% of the optical power into the sample arm through a circulator 910 and routing the remaining 10% to the reference arm. The reference arm path length was precisely adjusted to place the zero optical delay immediately after the scanning probe. A polarization controller 908 was included in the reference arm to optimize interference contrast. In the sample arm, the beam exits the fiber via a collimator 920 and is subsequently scanned using a galvanometer 916 that includes a pair of galvanometer mirrors, producing a beam diameter of approximately 3 mm that is directed to the target 108 via a lens 918. The mirrors of the galvanometer 916 are driven by sawtooth and step waveforms along X and Y axes, respectively, enabling 3D volumetric imaging. In the tested embodiment, the optical power of the probing beam in the sample arm was measured at -5 mW, (which is within eye-safety limits).

[0092] Interferometric OCT signals from the recombined reference and sample arm beams are received via a fiber coupler 912 and captured using a balanced photodetector 914. In the tested embodiment, a balanced photodetector 914 having a 600 MHz bandwidth was used, though other types of balanced photodetectors 914 may be used in other embodiments. Synchronization and digitization is managed using an analog output 924 of the akinetic swept laser 902 that is also used to drive the galvanometer 916, a digital output board (e.g., a digital output board provided by National Instruments), and a digitizer 922 (e.g., a AlazarTech ATS9373 digitizer), operating at a sampling rate of 900 MS / s in external clock mode. Acquired data are rapidly transferred to a processing computing device 904 via a suitable interface (e.g., an 8-lane PCI Express Gen2 interface), enabling efficient postprocessing and visualization. In the tested embodiment, the signal to noise ratio (SNR) was measured to be -105 dB at the zero-delay line.

[0093] Future hardware enhancements, such as integrating advanced digitizers with higher sampling rates and beam conditioning optics to mitigate divergence, would allow practical exploitation of the full theoretical imaging range provided by this swept-source laser, potentially extending volumetric imaging capabilities up to or beyond 200 m. Further, while the OCT system 900 is illustrated with some different components than the system 200 shown in FIG. 2 that performs electrical dispersion adjustment, in some embodiments, the OCT system 900 includes components (e.g., an optical delay line 212, a function generator 206, a swept laser that provides a sweep trigger and an MZI K-CLK signal, etc.) that allow the OCT system 900 to perform similar electrical dispersion adjustment on the raw OCT interferometric signals. Alternatively, the dispersion adjustment computing device 204 of the system 200 may be configured to process received OCT interferometric signals using the data processing techniques illustrated in FIG. 10 and described in further detail below.

[0094] Due to the extended imaging range and high digitization rate provided by the OCT system 900, the amount of data produced by each volumetric scan may quickly become impractical to be processed, often reaching several gigabytes per acquisition. Efficient management and processing of such large datasets present significant computational challenges, particularly with regard to real-time or near-real-time visualization and analysis that may be desired for applications such as industrial metrology, robotic perception, or environmental mapping. FIG. 10 is a flowchart that illustrates a non-limiting example embodiment of a method of scanning a scene using an OCT system, according to various aspects of the present disclosure. The method 1000 provides a structured and efficient processing pipeline optimized for computational performance and effective data reduction, thus making the OCT system 900 suitable for use for real-time or near-real-time applications.

[0095] From a start block, the method 1000 proceeds to block 1002, where a processing computing device 904 receives raw OCT interferometric signals. As shown in FIG. 9, the raw OCT interferometric signals are received from the digitizer 922. At block 1004, the processing computing device 904 transforms the raw OCT interferometric signals to a spatial domain by applying a Fourier transformation to create spatial signals. The linearity of the akinetic swept laser 902 allows the Fourier transformation to be applied to the raw OCT interferometric signals without additional spectral calibration.

[0096] At block 1006, the processing computing device 904 extracts amplitude data from the spatial signals. In some embodiments, the amplitude data may be converted into ordisplayed in a logarithmic scale (e.g., a decibel scale) to enhance visualization of object features within the imaged scene.

[0097] At block 1008, the processing computing device 904 produces a binary mask based on the amplitude data. In some embodiments, the binary mask may be produced by applying a predetermined threshold to the amplitude data to suppress background noise and clearly delineate objects within the scene. This thresholding effectively isolates significant object signals from irrelevant background data.

[0098] At optional block 1010, the processing computing device 904 conducts point cloud compression on the binary mask to create a compressed point cloud. The binary mask produced at block 1008 may still contain extensive sparse background information, which results in large, inefficient amounts of data. Accordingly, using a point cloud compression technique on the resulting data can help mitigate these issues. In some embodiments, spatial coordinates corresponding to signal-positive voxels (those representing actual imaging objects within the scene) are retained, while data associated with other spatial coordinates are discarded. This effectively discards the extensive non-informative background data. Any suitable point cloud compression technique known to those of skill in the art may be used, including but not limited to techniques described in Lu et al., “Efficient Large-Scale Point Cloud Geometry Compression,” Sensors 25, no. 5: 1325 (2025), the entire disclosure of which is hereby incorporated by reference herein for all purposes. Such point cloud compression techniques can achieve data reduction of approximately three orders of magnitude, reducing the size of the data for storage and further processing from gigabytes to a few megabytes, greatly facilitating efficient storage, transfer, and further analysis.

[0099] At optional block 1012, the processing computing device 904 applies geometric distortion correction to the compressed point cloud to create a corrected compressed point cloud. The geometric distortion correction compensates for the spherical scanning geometry introduced by scanning the scene from substantially a single location using the galvanometer 916. Using known scan angles and measured axial depths, Cartesian coordinates are calculated for each voxel to accurately reconstruct three-dimensional spatial relationships within the scanned scene. This distortion correction provides accurate and precise spatial representation, which is useful for accurate metrological assessment and quantitative analyses.

[0100] At optional block 1014, the processing computing device 904 denoises the corrected compressed point cloud using a sparse outlier removal technique. Inherent OCT speckle noise can degrade image quality, which complicates the identification of subtlestructures. By conducting sparse outlier removal against the corrected point cloud data, visual clarity can be substantially enhanced, and robust feature identification can be ensured for subsequent measurements and assessments. Any suitable technique can be used to remove sparse outliers, including but not limited to the techniques described in Ning et al., “An Efficient Outlier Removal Method for Scattered Point Cloud Data,” PLoS ONE 13(8): e0201280 (2018), the entire disclosure of which is hereby incorporated by reference herein for all purposes.

[0101] The actions of optional block 1010 - optional block 1014 are illustrated and described as optional. Typically, all of these actions will be performed, but in some embodiments, the actions of one or more of these optional blocks may be skipped. For example, if adequate computing power and storage are available in the future to process all of the point cloud data in real-time or near real-time, then the point cloud compression of optional block 1010 may be skipped. As another example, if an en face presentation of the data from the point of view of the imaging probe is desired, then the distortion correction of optional block 1012 may not meaningfully change the data, and may be skipped. As yet another example, if the noise in the data is not significant, the denoising of optional block 1014 may be skipped.

[0102] At block 1016, the processing computing device 904 generates a representation of the scene based on the binary mask. The representation of the scene may then be used for any purpose. In some embodiments, the representation of the scene may be presented on a display device to a user. In some embodiments, the representation of the scene may be provided to a metrology system to conduct measurements of one or more objects in the imaged scene, which may then be used to control a device based on the measurements. In some embodiments, the representation of the scene may be provided as sensing input to a control system, including but not limited to a control system of an autonomous vehicle. The autonomous vehicle may then make control decisions (e.g., path planning, object avoidance, etc.) based on the representation of the scene.

[0103] The method 1000 then proceeds to an end block and terminates.

[0104] A non-limiting example embodiment of the OCT system 900 and method 1000 were evaluated across various real-world imaging scenarios to demonstrate their practical utility and versatility. First, to verify long-range human imaging capability, en face OCT images were acquired of a human subject. FIG. 11 illustrates a non-limiting example result of scanning a human subject in a hallway at distances incrementally ranging from 5 to 35 m, using the system illustrated in FIG. 9 and the techniques described in FIG. 10. Sections 1-7of FIG. 11 illustrate increments of 5, 10, 15, 20, 25, 30, and 35 m from the OCT probe, along with a reference photograph at 15 m for Section 8. Despite the expected reduction in signal strength due to sample-beam divergence at longer distances, the OCT system 900 maintained robust SNR, clearly resolving key anatomical features. Structural details such as clothing contours, body posture, and general anatomical landmarks remained identifiable at all distances tested. Depth was effectively conveyed via color-encoded distance wrapping, and the compact size of the OCT probe illustrated system portability, making it suitable for varied environments.

[0105] Next, to assess the system's resolution and metrological accuracy at closer range, detailed volumetric OCT images of a human face were obtained. At approximately 1 mm / pixel sampling density over a 30x20 cm field of view, facial features including eyes, nose, mouth, and glasses were clearly resolved. These results underscore the potential utility of the OCT system 900 in biometric applications, emotion recognition, and precise facial measurements relevant to ergonomic assessments or interaction with automated systems. Full-body volumetric imaging capabilities were evaluated by scanning a human subject at 5.2 meters distance using a 11.25° x 22.5° angular scan. The resulting point cloud data accurately depicted the human posture, arm positions, and overall body geometry, demonstrating the ability of the OCT system 900 to capture dynamic human poses with sufficient spatial resolution. This capability is especially relevant for applications in ergonomics, animation, virtual reality, and interactive gaming systems.

[0106] FIG. 12 illustrates a non-limiting example result of scanning within an uncontrolled outdoor environment using the system of FIG. 9 and the techniques of FIG. 10. Section 1 of FIG. 12 shows an annotated en face image of the scene. Section 2 shows a geometrically corrected 3D point cloud with labeled object distances. Section 3 is a reference photograph of the same scene showing image degradation due to direct sunlight. As shown, the OCT system 900 was used to scan a parking area, and objects such as vehicles, stationary lampposts, and pedestrians located up to ~50 m away from the OCT system 900 were accurately resolved and spatially localized. Unlike conventional photography, which was degraded by strong ambient sunlight, the OCT images were unaffected by lighting conditions, validating the system’s immunity to environmental illumination variability. Such characteristics make the OCT system 900 highly valuable for outdoor metrology, autonomous navigation, and security applications.

[0107] To illustrate dynamic imaging capabilities, a real-time OCT video sequence was recorded at 10 volumes per second, capturing a pedestrian interacting with a vehicle. Key events such as the pedestrian walking toward, entering, and driving away in a vehicle wereclearly captured. These results demonstrate the ability of the OCT system 900 to provide real-time, volumetric visual data for surveillance, autonomous vehicle navigation, and realtime behavioral monitoring. Finally, the capability of the OCT system 900 for structural imaging at large scales was shown through a detailed scan of a building facade from approximately 20 m away. Structural elements including walls, windows, and architectural features were well resolved in a dense volumetric scan spanning 46° x 41.4°. This application highlights the suitability of the OCT system 900 for architectural inspection, urban mapping, geospatial assessment, and structural health monitoring tasks.

[0108] Collectively, these experiments validate the versatility and robust performance of the OCT system 900 across diverse practical scenarios, reinforcing its potential as a reliable and precise optical sensing platform beyond biomedical contexts. The presented OCT system 900, enabled by an akinetic all-semiconductor swept source, achieves unprecedented imaging range while maintaining a compact form factor and practical acquisition rate. Supporting this capability are its ultra-narrow instantaneous linewidth, highly linear k-space tuning, and rapid digitization processes. The increasing demand for compact, portable optical imaging solutions capable of long-range, high-resolution measurements is particularly evident in autonomous vehicle navigation, robotic manipulation, industrial quality control, and environmental sensing. OCT’s inherent strengths — micron-level axial resolution, resilience to ambient lighting conditions, and coherent phase-sensitive detection — distinctly position it relative to other optical metrology technologies. Compared with traditional LiDAR systems that commonly employ mechanical scanning elements and exhibit limited axial resolution, the OCT system 900 offers significant operational advantages. The akinetic swept-source technology demonstrated above further underscores these advantages, enabling precise volumetric measurements useful for advanced robotic interactions, environmental monitoring, and precision manufacturing metrology.

[0109] FIG. 13 is a block diagram that illustrates aspects of a non-limiting example embodiment of a computing device 1300 appropriate for use as a computing device (e.g., a dispersion adjustment computing device 204, a controller computing device 604, and / or a processing computing device 904) of the present disclosure. While multiple different types of computing devices may be considered, the example computing device 1300 illustrates and describes various elements that are common to many different types of computing devices. While FIG. 13 is described with reference to a computing device that is implemented as a device on a network, the description below is applicable to servers, personal computers, mobile phones, smart phones, tablet computers, embedded computing devices, and other devices that may be used to implement portions of embodiments of thepresent disclosure. Some embodiments of a computing device may be implemented in or may include an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other customized device. Moreover, those of ordinary skill in the art and others will recognize that the computing device 1300 may be any one of any number of currently available or yet to be developed devices.

[0110] In its most basic configuration, the computing device 1300 includes at least one processor 1302 and a system memory 1310 connected by a communication bus 1308. Depending on the exact configuration and type of device, the system memory 1310 may be volatile or nonvolatile memory, such as read only memory (“ROM”), random access memory (“RAM”), EEPROM, flash memory, or similar memory technology. Those of ordinary skill in the art and others will recognize that system memory 1310 typically stores data and / or program modules that are immediately accessible to and / or currently being operated on by the processor 1302. In this regard, the processor 1302 may serve as a computational center of the computing device 1300 by supporting the execution of instructions.[OHl] As further illustrated in FIG. 13, the computing device 1300 may include a network interface 1306 comprising one or more components for communicating with other devices over a network. Embodiments of the present disclosure may access basic services that utilize the network interface 1306 to perform communications using common network protocols. The network interface 1306 may also include a wireless network interface configured to communicate via one or more wireless communication protocols, such as WiFi, 2G, 3G, LTE, WiMAX, Bluetooth, Bluetooth low energy, and / or the like. As will be appreciated by one of ordinary skill in the art, the network interface 1306 illustrated in FIG. 13 may represent one or more wireless interfaces or physical communication interfaces described and illustrated above with respect to particular components of the computing device 1300.

[0112] In the non-limiting example embodiment depicted in FIG. 13, the computing device 1300 also includes a storage medium 1304. However, services may be accessed using a computing device that does not include means for persisting data to a local storage medium. Therefore, the storage medium 1304 depicted in FIG. 13 is represented with a dashed line to indicate that the storage medium 1304 is optional. In any event, the storage medium 1304 may be volatile or nonvolatile, removable or nonremovable, implemented using any technology capable of storing information such as, but not limited to, a hard drive, solid state drive, CD ROM, DVD, or other disk storage, magnetic cassettes, magnetic tape, magnetic disk storage, and / or the like.

[0113] Suitable implementations of computing devices that include a processor 1302, system memory 1310, communication bus 1308, storage medium 1304, and network interface 1306 are known and commercially available. For ease of illustration and because it is not important for an understanding of the claimed subject matter, FIG. 13 does not show some of the typical components of many computing devices. In this regard, the computing device 1300 may include input devices, such as a keyboard, keypad, mouse, microphone, touch input device, touch screen, tablet, and / or the like. Such input devices may be coupled to the computing device 1300 by wired or wireless connections including RF, infrared, serial, parallel, Bluetooth, Bluetooth low energy, USB, or other suitable connections protocols using wireless or physical connections. Similarly, the computing device 1300 may also include output devices such as a display, speakers, printer, etc. Since these devices are well known in the art, they are not illustrated or described further herein.

[0114] The complete disclosure of all patents, patent applications, and publications, and electronically available material cited herein are incorporated by reference in their entirety. Supplementary materials referenced in publications (such as supplementary tables, supplementary figures, supplementary materials and methods, and / or supplementary experimental data) are likewise incorporated by reference in their entirety. In the event that any inconsistency exists between the disclosure of the present application and the disclosure(s) of any document incorporated herein by reference, the disclosure of the present application shall govern.

[0115] The foregoing detailed description and examples have been given for clarity of understanding only. No unnecessary limitations are to be understood therefrom. The disclosure is not limited to the exact details shown and described, for variations obvious to one skilled in the art will be included within the disclosure defined by the claims. For example, description of specific commercially available devices or products do not limit the description to the exact named product from the exact named manufacturer, but instead includes other products from the same or other manufacturers with similar capabilities.

[0116] The description of embodiments of the disclosure is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. While the specific embodiments of, and examples for, the disclosure are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the disclosure.

[0117] Specific elements of any foregoing embodiments can be combined or substituted for elements in other embodiments. Moreover, the inclusion of specific elements in at least some of these embodiments may be optional, wherein further embodiments may include oneor more embodiments that specifically exclude one or more of these specific elements. Furthermore, while advantages associated with certain embodiments of the disclosure have been described in the context of these embodiments, other embodiments may also exhibit such advantages, and not all embodiments need necessarily exhibit such advantages to fall within the scope of the disclosure.

[0118] As used herein and unless otherwise indicated, the terms “a” and “an” are taken to mean “one”, “at least one” or “one or more”. Unless otherwise required by context, singular terms used herein shall include pluralities and plural terms shall include the singular.

[0119] Unless the context clearly requires otherwise, throughout the description and the claims, the words ‘comprise’, ‘comprising’, and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to”. Words using the singular or plural number also include the plural and singular number, respectively. Additionally, the words “herein,” “above,” and “below” and words of similar import, 10 when used in this application, shall refer to this application as a whole and not to any particular portions of the application.

[0120] Unless otherwise indicated, all numbers expressing quantities of components, molecular weights, and so forth used in the specification and claims are to be understood as being modified in all instances by the term "about." Accordingly, unless otherwise indicated to the contrary, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the present disclosure. At the very least, and not as an attempt to limit the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.

[0121] Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the disclosure are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. All numerical values, however, inherently contain a range necessarily resulting from the standard deviation found in their respective testing measurements.

[0122] All headings are for the convenience of the reader and should not be used to limit the meaning of the text that follows the heading, unless so specified.

[0123] All of the references cited herein are incorporated by reference. Aspects of the disclosure can be modified, if necessary, to employ the systems, functions, and concepts ofthe above references and application to provide yet further embodiments of the disclosure. These and other changes can be made to the disclosure in light of the detailed description.

[0124] It will be appreciated that, although specific embodiments of the disclosure have been described herein for purposes of illustration, various modifications may be made without deviating from the spirit and scope of the disclosure. Accordingly, the disclosure is not limited except as by the claims.EXAMPLES

[0125] The following paragraphs provide a set of non-limiting example embodiments of the subject matter disclosed herein.

[0126] Example 1 : A system for scanning a scene using optical coherence tomography (OCT), the system comprising: a swept laser; a reference arm; a sample arm; a balanced photodetector; a computing device; a first fiber coupler configured to divide output of the swept laser between the reference arm and the sample arm; a second fiber coupler configured to provide signals from the reference arm and the sample arm to the balanced photodetector; and a digitizer configured to receive output from the balanced photodetector and to provide digitized signals to the computing device as raw OCT interferometric signals; wherein the computing device is configured to process the raw OCT interferometric signals to adjust for electrical dispersion by performing actions comprising: receiving, by the computing device, the raw OCT interferometric signals and a k-clock signal; determining, by the computing device, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k- shift; and sampling, by the computing device, the raw OCT interferometric signals using the adjusted k-clock signal.

[0127] Example 2: The system of example 1, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes approximating the non-linear k-shift using a polynomial equation.

[0128] Example 3: The system of example 2, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes finding a globally optimized non-linear k-shift vector using a minimum phase residual as a merit function.

[0129] Example 4: The system of example 3, wherein the minimum phase residual is represented by:

[0130]

[0131] Example 5: The system of any one of examples 1-4, wherein the computing device is further configured to process the raw OCT interferometric signals by performing actions comprising: receiving, by the computing device, the sampled raw OCT interferometric signals; transforming, by the computing device, the sampled raw OCT interferometric signals to a spatial domain to create spatial signals; extracting, by the computing device, amplitude data from the spatial signals; producing, by the computing device, a binary mask based on the amplitude data; and generating, by the computing device, a representation of the scene based on the binary mask.

[0132] Example 6: The system of example 5, wherein transforming the sampled raw OCT interferometric signals to the spatial domain to create spatial signals includes applying a Fourier transformation to the sampled raw OCT interferometric signals.

[0133] Example 7: The system of any one of examples 5-6, wherein producing the binary mask based on the amplitude data includes filtering the amplitude data based on a predetermined threshold amplitude value.

[0134] Example 8: The system of any one of examples 5-7, wherein the actions further comprise conducting point cloud compression on the binary mask to create a compressed point cloud.

[0135] Example 9: The system of example 8, wherein the actions further comprise applying geometric distortion correction to the compressed point cloud to create a corrected compressed point cloud.

[0136] Example 10: The system of example 9, wherein the actions further comprise denoising the corrected compressed point cloud using a sparse outlier removal technique.

[0137] Example 11 : The system of any one of examples 1-10, wherein the swept laser is an akinetic swept laser.

[0138] Example 12: The system of any one of examples 1-11, wherein the reference arm is configured to place a zero optical delay immediately after a scanning probe.

[0139] Example 13: The system of any one of examples 1-12, wherein the reference arm includes a polarization controller.

[0140] Example 14: The system of any one of examples 1-13, wherein the sample arm includes a collimator and a pair of galvanometer mirrors.

[0141] Example 15: A computer-implemented method of scanning a scene using an optical coherence tomography (OCT) system, the method comprising: receiving, by a computing device, raw OCT interferometric signals; transforming, by the computing device, the raw OCT interferometric signals to a spatial domain to create spatial signals; extracting, by the computing device, amplitude data from the spatial signals; producing, by the computing device, a binary mask based on the amplitude data; and generating, by the computing device, a representation of the scene based on the binary mask.

[0142] Example 16: The computer-implemented method of example 15, wherein transforming the raw OCT interferometric signals to the spatial domain to create spatial signals includes applying a Fourier transformation to the raw OCT interferometric signals.

[0143] Example 17: The computer-implemented method of any one of examples 15-16, wherein producing the binary mask based on the amplitude data includes filtering the amplitude data based on a predetermined threshold amplitude value.

[0144] Example 18: The computer-implemented method of any one of examples 15-17, further comprising conducting point cloud compression on the binary mask to create a compressed point cloud.

[0145] Example 19: The computer-implemented method of example 18, further comprising applying geometric distortion correction to the compressed point cloud to create a corrected compressed point cloud.

[0146] Example 20: The computer-implemented method of example 19, further comprising denoising the corrected compressed point cloud using a sparse outlier removal technique.

[0147] Example 21 : The computer-implemented method of any one of examples 15-20, wherein the raw OCT interferometric signals are generated using an akinetic swept laser.

[0148] Example 22: A non-transitory computer-readable medium having computerexecutable instructions stored thereon that, in response to execution by one or more processors of a computing device, cause the computing device to perform actions of a method as recited in any one of examples 15 to 21.

[0149] Example 23: A computing device configured to perform actions of a method as recited in any one of examples 15 to 21.

[0150] Example 24: A computer-implemented method of processing signals in an optical coherence tomography (OCT) system, the method comprising: receiving, by a computing device, an OCT interference signal and a k-clock signal; determining, by the computingdevice, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k-shift; and sampling, by the computing device, the OCT interference signal using the adjusted k-clock signal.

[0151] Example 25: The computer-implemented method of example 24, further comprising: transmitting, by the computing device, controlling signals for controlling components of the OCT system.

[0152] Example 26: The computer-implemented method of example 25, further comprising: determining, by the computing device, the controlling signals based on topological information of a target sample.

[0153] Example 27: The computer-implemented method of example 26, further comprising: determining, by the computing device, the topological information of the target sample using at least one fast surface profiling technique.

[0154] Example 28: The computer-implemented method of example 27, wherein the at least one fast surface profiling technique includes a fast OCT scan, a stereo camera technique, a structured illumination technique, or a time-of-flight technique.

[0155] Example 29: The computer-implemented method of any one of examples 26-28, wherein determining the controlling signals based on the topological information of the target sample includes determining the controlling signals based on an OCT system depth of focus.

[0156] Example 30: The computer-implemented method of example 29, wherein the OCT system depth of focus is a Raleigh length of the OCT system.

[0157] Example 31 : The computer-implemented method of any one of examples 24-30, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes approximating the non-linear k-shift using a polynomial equation.

[0158] Example 32: The computer-implemented method of example 31, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes finding a globally optimized non-linear k-shift vector using a minimum phase residual as a merit function.

[0159] Example 33: The computer-implemented method of example 32, wherein the minimum phase residual is represented by:

[0160]

[0161] Example 34: The computer-implemented method of any one of examples 24-33, further comprising: determining a linear k-shift based on the depth; and adjusting, by the computing device, the k-clock signal based on the linear k-shift.

[0162] Example 35: The computer-implemented method of any one of examples 24-34, further comprising: determining an optical dispersion k-shift; and adjusting, by the computing device, the k-clock signal based on the optical dispersion k-shift.

[0163] Example 36: The computer-implemented method of any one of examples 24-35, further comprising: generating, by the computing device, a rendering of a target based on the sampled OCT interference signal; and presenting, by the computing device, the rendering of the target.

[0164] Example 37: A non-transitory computer-readable medium having computerexecutable instructions stored thereon that, in response to execution by one or more processors of a computing device, cause the computing device to perform actions of a method as recited in any one of example 24 to example 36.

[0165] Example 38: A computing device configured to perform actions of a method as recited in any one of example 24 to example 36.

[0166] Example 39: A computer-implemented method of scanning a target in an optical coherence tomography (OCT) system, the method comprising: determining, by a computing device, a topology of the target; dividing, by the computing device, the target into segments based on the topology; for each segment: adjusting, by the computing device, the OCT system based on a depth of the segment; and causing, by the computing device, the OCT system to scan the segment to create a segment rendering; and combining, by the computing device, the segment renderings to create a combined rendering of the target.

[0167] Example 40: The computer-implemented method of example 39, wherein determining the topology of the target includes: using, by the computing device, the OCT system to perform a rough scan of the target and determining, by the computing device, the topology based on the rough scan of the target.

[0168] Example 41 : The computer-implemented method of any one of examples 39-40, wherein determining the topology of the target includes: using, by the computing device, signals received from a depth camera or a structured light camera to create a three- dimensional model of the target; and determining, by the computing device, the topology based on the three-dimensional model of the target.

[0169] Example 42: The computer-implemented method of any one of examples 39-41, wherein dividing the target into segments based on the topology includes determining a segment size based on a confocal length of the OCT system.

[0170] Example 43: The computer-implemented method of any one of examples 39-42, wherein adjusting the OCT system based on the depth of the segment includes one or more of: adjusting, by the computing device, k-clock generation within the OCT system; providing, by the computing device, an k-clock adjustment based on the depth of the segment using a method as recited in any one of example 24 to example 36; adjusting, by the computing device, an electrically tunable lens of the OCT system; or adjusting, by the computing device, an adjustable optical delay line of the OCT system.

[0171] Example 44: The computer-implemented method of any one of examples 39-43, wherein combining the segment renderings to create a combined rendering of the target includes removing confocal artifacts from the combined rendering.

[0172] Example 45: A non-transitory computer-readable medium having computerexecutable instructions stored thereon that, in response to execution by one or more processors of a computing device, cause the computing device to perform actions of a method as recited in any one of example 39 to example 44.

[0173] Example 46: A computing device configured to perform actions of a method as recited in any one of example 39 to example 44.

Claims

CLAIMSThe embodiments of the invention in which an exclusive property or privilege is claimed are defined as follows:

1. A system for scanning a scene using optical coherence tomography (OCT), the system comprising: a swept laser; a reference arm; a sample arm; a balanced photodetector; a computing device; a first fiber coupler configured to divide output of the swept laser between the reference arm and the sample arm; a second fiber coupler configured to provide signals from the reference arm and the sample arm to the balanced photodetector; and a digitizer configured to receive output from the balanced photodetector and to provide digitized signals to the computing device as raw OCT interferometric signals; wherein the computing device is configured to process the raw OCT interferometric signals to adjust for electrical dispersion by performing actions comprising: receiving, by the computing device, the raw OCT interferometric signals and a k-clock signal; determining, by the computing device, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k-shift; and sampling, by the computing device, the raw OCT interferometric signals using the adjusted k-clock signal.

2. The system of claim 1, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes approximating the non-linear k-shift using a polynomial equation.

3. The system of claim 2, wherein determining the non-linear k-shift caused by the electrical dispersion based on the depth includes finding a globally optimized non-linear k-shift vector using a minimum phase residual as a merit function.

4. The system of claim 3, wherein the minimum phase residual is represented by:

5. The system of claim 1, wherein the computing device is further configured to process the raw OCT interferometric signals by performing actions comprising: receiving, by the computing device, the sampled raw OCT interferometric signals; transforming, by the computing device, the sampled raw OCT interferometric signals to a spatial domain to create spatial signals; extracting, by the computing device, amplitude data from the spatial signals; producing, by the computing device, a binary mask based on the amplitude data; and generating, by the computing device, a representation of the scene based on the binary mask.

6. The system of claim 5, wherein transforming the sampled raw OCT interferometric signals to the spatial domain to create spatial signals includes applying a Fourier transformation to the sampled raw OCT interferometric signals.

7. The system of claim 5, wherein producing the binary mask based on the amplitude data includes filtering the amplitude data based on a predetermined threshold amplitude value.

8. The system of claim 5, wherein the actions further comprise conducting point cloud compression on the binary mask to create a compressed point cloud.

9. The system of claim 8, wherein the actions further comprise applying geometric distortion correction to the compressed point cloud to create a corrected compressed point cloud.

10. The system of claim 9, wherein the actions further comprise denoising the corrected compressed point cloud using a sparse outlier removal technique.

11. The system of claim 1, wherein the swept laser is an akinetic swept laser.

12. The system of claim 1, wherein the reference arm is configured to place a zero optical delay immediately after a scanning probe.

13. The system of claim 1, wherein the reference arm includes a polarization controller.

14. The system of claim 1, wherein the sample arm includes a collimator and a pair of galvanometer mirrors.

15. A computer-implemented method of scanning a scene using an optical coherence tomography (OCT) system, the method comprising: receiving, by a computing device, raw OCT interferometric signals; transforming, by the computing device, the raw OCT interferometric signals to a spatial domain to create spatial signals; extracting, by the computing device, amplitude data from the spatial signals; producing, by the computing device, a binary mask based on the amplitude data; and generating, by the computing device, a representation of the scene based on the binary mask.

16. The computer-implemented method of claim 15, wherein transforming the raw OCT interferometric signals to the spatial domain to create spatial signals includes applying a Fourier transformation to the raw OCT interferometric signals.

17. The computer-implemented method of claim 15, wherein producing the binary mask based on the amplitude data includes filtering the amplitude data based on a predetermined threshold amplitude value.

18. The computer-implemented method of claim 15, further comprising conducting point cloud compression on the binary mask to create a compressed point cloud.

19. The computer-implemented method of claim 18, further comprising applying geometric distortion correction to the compressed point cloud to create a corrected compressed point cloud.

20. The computer-implemented method of claim 19, further comprising denoising the corrected compressed point cloud using a sparse outlier removal technique.

21. The computer-implemented method of claim 15, wherein the raw OCT interferometric signals are generated using an akinetic swept laser.

22. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, in response to execution by one or more processors of a computingdevice, cause the computing device to perform actions of a method as recited in any one of claims 15 to 21.

23. A computing device configured to perform actions of a method as recited in any one of claims 15 to 21.

24. A computer-implemented method of processing signals in an optical coherence tomography (OCT) system, the method comprising: receiving, by a computing device, an OCT interference signal and a k-clock signal; determining, by the computing device, a non-linear k-shift caused by electrical dispersion based on a depth; adjusting, by the computing device, the k-clock signal based on the non-linear k- shift; and sampling, by the computing device, the OCT interference signal using the adjusted k- clock signal.

25. The computer-implemented method of claim 24, further comprising: transmitting, by the computing device, controlling signals for controlling components of the OCT system.

26. The computer-implemented method of claim 25, further comprising: determining, by the computing device, the controlling signals based on topological information of a target sample.

27. The computer-implemented method of claim 26, further comprising: determining, by the computing device, the topological information of the target sample using at least one fast surface profiling technique.

28. The computer-implemented method of claim 27, wherein the at least one fast surface profiling technique includes a fast OCT scan, a stereo camera technique, a structured illumination technique, or a time-of-flight technique.

29. The computer-implemented method of claim 26, wherein determining the controlling signals based on the topological information of the target sample includes determining the controlling signals based on an OCT system depth of focus.

30. The computer-implemented method of claim 29, wherein the OCT system depth of focus is a Raleigh length of the OCT system.

31. The computer-implemented method of claim 24, wherein determining the non-linear k- shift caused by the electrical dispersion based on the depth includes approximating the nonlinear k-shift using a polynomial equation.

32. The computer-implemented method of claim 31, wherein determining the non-linear k- shift caused by the electrical dispersion based on the depth includes finding a globally optimized non-linear k-shift vector using a minimum phase residual as a merit function.

33. The computer-implemented method of claim 32, wherein the minimum phase residual is represented by:

34. The computer-implemented method of claim 24, further comprising: determining a linear k-shift based on the depth; and adjusting, by the computing device, the k-clock signal based on the linear k-shift.

35. The computer-implemented method of claim 24, further comprising: determining an optical dispersion k-shift; and adjusting, by the computing device, the k-clock signal based on the optical dispersion k-shift.

36. The computer-implemented method of claim 24, further comprising: generating, by the computing device, a rendering of a target based on the sampled OCT interference signal; and presenting, by the computing device, the rendering of the target.

37. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, in response to execution by one or more processors of a computing device, cause the computing device to perform actions of a method as recited in any one of claim 24 to claim 36.

38. A computing device configured to perform actions of a method as recited in any one of claim 24 to claim 36.

39. A computer-implemented method of scanning a target in an optical coherence tomography (OCT) system, the method comprising: determining, by a computing device, a topology of the target; dividing, by the computing device, the target into segments based on the topology; for each segment: adjusting, by the computing device, the OCT system based on a depth of the segment; and causing, by the computing device, the OCT system to scan the segment to create a segment rendering; and combining, by the computing device, the segment renderings to create a combined rendering of the target.

40. The computer-implemented method of claim 39, wherein determining the topology of the target includes: using, by the computing device, the OCT system to perform a rough scan of the target and determining, by the computing device, the topology based on the rough scan of the target.

41. The computer-implemented method of claim 39, wherein determining the topology of the target includes: using, by the computing device, signals received from a depth camera or a structured light camera to create a three-dimensional model of the target; and determining, by the computing device, the topology based on the three-dimensional model of the target.

42. The computer-implemented method of claim 39, wherein dividing the target into segments based on the topology includes determining a segment size based on a confocal length of the OCT system.

43. The computer-implemented method of claim 39, wherein adjusting the OCT system based on the depth of the segment includes one or more of: adjusting, by the computing device, k-clock generation within the OCT system; providing, by the computing device, an k-clock adjustment based on the depth of the segment using a method as recited in any one of claim 24 to claim 36; adjusting, by the computing device, an electrically tunable lens of the OCT system; oradjusting, by the computing device, an adjustable optical delay line of the OCT system.

44. The computer-implemented method of claim 39, wherein combining the segment renderings to create a combined rendering of the target includes removing confocal artifacts from the combined rendering.

45. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, in response to execution by one or more processors of a computing device, cause the computing device to perform actions of a method as recited in any one of claim 39 to claim 44.

46. A computing device configured to perform actions of a method as recited in any one of claim 39 to claim 44.

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