Processing system for OCT imaging, OCT imaging system, and method for OCT imaging

Abstract

The present invention provides a processing system for use with an optical coherence tomography imaging means for imaging an object, the processing system configured to repeatedly perform an image processing process (300) comprising the following steps: receiving (312) a scan data set from an object (190) acquired using optical coherence tomography; performing (314) data processing on the scan data set including applying (316) a dispersion correction based on a current set (370) of dispersion coefficients; and providing (318) a dispersion-corrected image data set of the object for an image of the object to be displayed; and the processing system performing dispersion coefficient adaptation at least partially in parallel with the image processing process (300). and a processing system configured to iteratively perform a dispersion coefficient adaptation process (340) comprising the steps of receiving (342) a scan dataset from an object acquired using optical coherence tomography, adapting (344) the dispersion coefficients using an optimization process (346) performed on the scan dataset, and providing (348) an adapted set of dispersion coefficients (372) that are used to update (350) the current set of dispersion coefficients (370), and the present invention further relates to an optical coherence tomography imaging system and a corresponding method.

Description

Technical Field

[0001] The present invention relates substantially to a processing system for use with optical coherence tomography (OCT) imaging means for imaging an object, an OCT imaging system including such a processing system, and a method for imaging an object using OCT.

Background Art

[0002] Optical coherence tomography (hereinafter also referred to by its typical abbreviation OCT) is an imaging technique that uses low-coherence light to capture high-resolution secondary and three-dimensional images from within a light-scattering medium (such as biological tissue), which is used especially for imaging in the medical field. Optical coherence tomography is based on the low-coherence interferometry method, and typically near-infrared light is used. By using light with a relatively long wavelength, the light can penetrate into the scattering medium. A medical field of particular interest in OCT is ophthalmology, which is a branch of medicine related to the eye (especially of humans), its disorders, and related surgeries.

Summary of the Invention

Means for Solving the Problems

[0003] According to the present invention, a processing system, an OCT imaging system, and a method for imaging an object are proposed, which have the features of the independent claims. Preferred further developments form the subject matter of the dependent claims and the following description.

[0004] The present invention relates to a processing system for use with optical coherence tomography (OCT) imaging means for imaging an object, particularly for real-time imaging of an object. The object preferably includes or is an eye. The type of OCT used is preferably spectral-region OCT (also known as Fourier-region OCT). The processing system may be included in a control unit configured to control the OCT imaging means. However, as will be described later, only a portion of the processing system may be included in such a control unit (and thus the control unit may be part of the processing system). Spectral or Fourier-region OCT may be based on a broadband light source and spectrometer system (e.g., one with a diffraction grating or other dispersion detector), but wavelength-swept OCT (SS-OCT) (i.e., spectral scanning system), where the frequency of light changes over time, can also be used.

[0005] In OCT, areas of a sample (object) or tissue that reflect a lot of light cause greater interference than areas that do not reflect light. Any light outside a short coherence length does not interfere. This reflectance profile is called an A scan and contains information about the spatial dimensions and location of structural parts within the sample or tissue. Cross-sectional tomography, called a B scan, can be achieved by a lateral combination of these series of axial depth scans (A scans). These A and B scans can be used to create a two-dimensional OCT image to be visualized.

[0006] The processing system receives a scan dataset from an object acquired using optical coherence tomography (OCT). This scan dataset may include intensity data for depth-resolved reflectance profiles of one or more samples, known as A-scans. These raw data must be processed, for example, to create images that can be visualized on a display device by an OCT system operator. OCT data processing typically requires resampling and Fourier transforming the real-valued spectral interferogram (spectrums included in the scan dataset) to generate depth-resolved reflectance profiles (A-scans) of the samples.

[0007] In particular, Fourier-domain optical coherence tomography (FD-OCT) uses the principle of low-coherence interferometry to generate two-dimensional or three-dimensional images of an object (sample). In OCT systems, mismatches often occur in the optics used in the sample arm and reference arm due to the optical specifications and requirements of the system. This mismatch may also be caused by the sample itself under inquiry. These differences cause an effect known as dispersion, where the speed of different wavelengths depends on the refractive index of the medium. Thus, light can travel through each arm at a variable speed, resulting in a temporary broadening of the coherent wave packet interfering in the detector. This leads to a wavelength-dependent phase shift in the interferogram (spectrum), causing blurring along the axial dimensions of the final OCT image.

[0008] Therefore, data processing involves applying dispersion correction based on a set of dispersion coefficients (such a set typically includes multiple coefficients, although it may, depending on the context, include only a single coefficient). A dispersion-corrected image dataset of the object to be displayed is then provided. Such an image processing process (including the steps of receiving the scan dataset, performing data processing, and providing the dispersion-corrected image dataset) is typically performed repeatedly, thus enabling real-time imaging of the object.

[0009] Dispersion effects may be compensated by using numerical corrections involving the application of second- and / or third-order phase terms to the acquired interference spectrum. This typically requires determining the correction coefficients for each phase order using an iterative optimization process that adjusts the coefficients, such as maximizing or minimizing an image quality metric. Such techniques are described, for example, in the literature "Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation" by M. Wojtkowski, VJ Srinivasan, TH Ko, JG Fujimoto, A. Kowalczyk, and JS Duker et al., Optics Express, 12(11), 2004, U.S. Patent Nos. 8018598, 8401257, and 7719692. This process is usually performed once at the start of acquisition or calculated for a given imaging configuration during pre-acquisition calibration.

[0010] However, it has been found that this method may result in an optimal lower limit of variance correction, especially in situations where the optical medium of the sample (object) changes during acquisition, such as during surgical procedures involving gas or fluid exchange.

[0011] Within the framework of the present invention, a novel technique is proposed for better correcting or compensating for such dispersion effects. This proposal includes a coefficient fitting process that is repeatedly performed on a processing system. In each cycle of this coefficient fitting process, a scan dataset from an object acquired using optical coherence tomography is received by the processing system, the dispersion coefficients are fitted using an optimization process performed on the scan dataset, and then a set of fitted dispersions is provided which is used to update the current set of dispersion coefficients used in the aforementioned image processing process.

[0012] The repeatedly performed variance coefficient fitting process runs at least partially in parallel with the repeatedly performed image processing process. Preferably, both processes run in full parallel, i.e., simultaneously. This allows for image processing to be performed as usual, however the variance coefficients used therein can be updated whenever an updated version becomes available from the concurrently running fitting process.

[0013] In summary, this allows for the dynamic updating of dispersion correction coefficients, for example, in response to changes in the optical medium of a given sample (object). This method uses separate calculation or fitting processes to perform standard processing of OCT images while simultaneously determining the optimal (or at least better or better fitted) coefficients to enable continuous real-time display. These coefficients are preferably continuously updated to provide the best correction for dispersion in a given sample without the need to separately calibrate and stop acquisition.

[0014] Logic can be used to determine whether the coefficients are continuously updated, or only updated once a predetermined criterion is met, such as when the magnitude of the change in the coefficients exceeds a predetermined threshold. Additional checks can also be used to ensure that the OCT image of the region of interest is corrected and not the conjugate image resulting from the Fourier transform being processed.

[0015] To execute two processes simultaneously, the processing system preferably includes multiple processing units configured to run in parallel, and more preferably to run independently of each other, and each processing unit is configured to run one of two processes: an image processing process and a variance coefficient fitting process. Each of these processing units may be either a CPU or a GPU. Thus, the processing system may include two CPUs, two GPUs, or one CPU and one GPU. It should also be noted that multiple CPUs or GPUs can be combined to form processing units that provide sufficient computing power.

[0016] As mentioned above, these two processes can be performed either on the same computer system (or control unit) used to run the software that controls the OCT means or OCT system, or on a separate computer system external to the OCT system. In the first case, the processing system is included in the control unit, and in the second case, only the processing unit that runs the image processing system is included in the control unit, with other processing units provided separately and remotely. These other processing units that run the variance coefficient fitting process may be separate computers or PCs in the same space as the OCT system, however, they can also be formed by servers or cloud computing systems connected via the internet or the like.

[0017] A further advantage of the proposed technique lies in the fact that the two processes do not need to be synchronized. This means that each cycle of the image processing process uses a new (and subsequently acquired) scan dataset, while each cycle of the variance coefficient fitting process uses only the most recently available scan dataset. A simple example is that the duration of the variance coefficient fitting process performed on the scan dataset is twice the duration of the image processing process. Thus, two cycles of image processing are performed until the set of variance coefficients is updated. In other words, two cycles of image processing are performed based on the same set of variance coefficients (although it should be noted that the logic may decide not to update the variance coefficients if, for example, there has been no significant change).

[0018] Variance optimization may be performed on data from the entire OCT scan (which thus corresponds to the scan dataset) or from a subset of such scans (or scan dataset). Furthermore, the optimization process is preferably performed on the image based on the scan dataset and uses image quality metrics. Such metrics may be based on at least one of the following: maximum image intensity, image sharpness, image brightness, and the overall signal-to-noise ratio of the image. In other words, the optimization process may use image quality metrics to evaluate the effect of coefficient changes and may include considering maximum image intensity, image sharpness, the overall signal-to-noise ratio of the image, or other numerical methods to quantify image quality.

[0019] The optimal coefficient can be determined from second-order numerical corrections, or (additionally) higher-order (third-order or higher) numerical corrections may be included. These corrections may be applied by calculating different resampling parameters, with or without separate variance coefficients. Logic for determining the effectiveness of the calculated variance coefficients may include considering changes in sign in the coefficients, or analyzing image features such as gradients, histograms, or sample-specific features that may indicate the presence of conjugate images.

[0020] The present invention also relates to an optical coherence tomography (OCT) imaging system for imaging an object, such as an eye, (particularly in real time), and comprising the processing system according to the present invention described above, and optical coherence tomography imaging means for performing OCT scanning (see the drawings and corresponding descriptions for a more detailed description of such OCT imaging means). Preferably, the OCT imaging system is configured to display an image of the object on a display means. Such a display means may be part of the OCT imaging system.

[0021] Such an OCT imaging system typically also includes a control unit configured to control the optical coherence tomography imaging means. As mentioned above, the control unit may include a processing system, in particular the two processing units described above. However, the control unit may also include only processing units configured to perform image processing processes, in which case other processing units are provided separately.

[0022] The present invention also relates to a method for imaging an object such as an eye using optical coherence tomography (OCT), preferably spectral region OCT. The method includes repeatedly performing the following steps of an image processing process: acquiring a scan dataset from an object using optical coherence tomography; performing data processing on the scan dataset, which includes applying dispersion correction to the scan dataset based on a current set of dispersion coefficients; and providing a dispersion-corrected image dataset of the object for an image of the object, preferably displaying an image of the object. Furthermore, the method includes repeatedly performing a dispersion coefficient fitting process at least partially in parallel with the image processing process, the dispersion coefficient fitting process including the following steps: receiving a scan dataset from an object acquired using optical coherence tomography; fitting the dispersion coefficients using an optimization process performed on the scan dataset; and providing a set of fitted dispersion coefficients. The method also includes updating the current set of dispersion coefficients based on the set of fitted dispersion coefficients. Both the image processing process and the dispersion coefficient fitting process are preferably performed on different processing units. The step of updating the coefficients is typically a step that links both the process and the processing unit.

[0023] For further preferred details and advantages of this OCT imaging system and method, please also refer to the notes on the processing system described herein as applicable.

[0024] The present invention also relates, in particular, to a computer program comprising program code for causing a computer program to perform a method according to the present invention when the computer program is executed on a processor, processing system, or control unit or system, as described above.

[0025] Further advantages and embodiments of the present invention will become apparent from the description and accompanying drawings.

[0026] It should be noted that the foregoing features and the features further described below can be used not only in the combinations shown respectively, but also in further combinations or individually, without departing from the scope of the present invention.

Brief Description of the Drawings

[0027] [Figure 1] It is a schematic diagram showing a preferred embodiment of an OCT imaging system according to the present invention. [Figure 2] It is a schematic diagram showing a further preferred embodiment of an OCT imaging system according to the present invention. [Figure 3] It is a schematic flowchart showing a preferred embodiment of the method according to the present invention. [Figure 4] It is a schematic flowchart showing a preferred embodiment of a part of the method according to the present invention. [[ID=1捌]] [Figure 5] It is a schematic flowchart showing a preferred embodiment of a further part of the method according to the present invention.

Mode for Carrying Out the Invention

[0028] In FIG. 1, a preferred embodiment of an optical coherence tomography (OCT) imaging system 100 according to the present invention is schematically shown. This OCT imaging system 100 includes a light source 102 (for example, a low coherence light source), a beam splitter 104, a reference arm 106, a sample arm 112, a diffraction grating 118, a detector 120 (for example, a camera), a control unit 130, and display means 140 (for example, a display or a monitor).

[0029] <~ The light generated from the light source 102 is guided to the beam splitter 104 through, for example, an optical fiber cable 150. The first part of the light is transmitted through the beam splitter 104 and then guided to the reference mirror 110 to create a light beam 109 through an optical system 108 (only schematically shown and represented by a lens). Here, the optical system 108 and the reference mirror 110 are part of the reference arm 106.

[0030] Light reflected from the reference mirror 110 is guided back to the beam splitter 104, transmitted through this beam splitter 104, and then guided to the diffraction grating 118 to create a light beam 117 via the optical system 116 (shown schematically only and represented by lenses).

[0031] A second portion of the light generated from the light source 102 and transmitted through the beam splitter 104 is guided through an optical system 114 (shown schematically only and represented by a lens) to an object 190 to be imaged in order to create a (scanning) light beam 115. This object 190 is, for example, an eye. The optical system 114 is part of the sample arm 112.

[0032] Light reflected from the object 190 or the tissue material within it is guided back to the beam splitter 104, transmitted through this beam splitter 104, and then guided to the diffraction grating 118 via the optical system 116. Thus, the light reflected from the reference arm 106 and the light reflected from the sample arm 112 are combined using the beam splitter 104 and guided to the diffraction grating 118 in the combined light beam 117, for example via an optical fiber cable 150.

[0033] Light reaching the diffraction grating 118 is diffracted and captured by the detector 120. In this way, the detector 120, which functions as a spectrometer, creates or acquires scanning data or scanning dataset 122, which is transmitted to the control unit 130, for example, via an electrical cable 152. The control unit 130 includes a processing system 132, which includes two processing units 134 and 136, which are, for example, a CPU or a GPU. For example, the control unit 130 may be equivalent to the processing system 132. The scanning dataset 122 is then processed to obtain an image dataset 142, which is transmitted to the display means 140, for example, via an electrical cable 152, and displayed as a real-time image 144, i.e., an image representing the object 190 being scanned in real time.

[0034] The process by which the intensity scanning dataset 122 is processed or converted into an image dataset 142 that allows the scanned object 190 to be displayed on the display means 140 will be described in more detail below. Note that there are two processes: an image processing process performed on processing unit 134 and a variance coefficient fitting process performed on processing unit 136.

[0035] Figure 2 shows a schematic diagram of a further preferred embodiment of the optical coherence tomography (OCT) imaging system 200 according to the present invention. This OCT imaging system 200 basically corresponds to the OCT imaging system 100 shown in and described in relation to Figure 1. However, the processing system 232 is different from the processing system 132 in Figure 1. The control unit 130 is included in the processing system 232, and the processing system 232 includes a processing unit 134. In particular, the processing unit 134 may be equivalent to the control unit 130. However, the processing unit 136 is provided separately from the processing unit 134 and is connected via a connection such as an Ethernet connection or via the Internet.

[0036] The process by which the intensity scanning dataset 122 is processed or converted into an image dataset 142 that allows the scanned object 190 to be displayed on the display means 140 is equivalent to, or may be equivalent to, the OCT imaging system 100 in Figure 1, and will be described in more detail below. Note that in this embodiment as well, the image processing process is performed on the processing unit 134, and the variance coefficient fitting process is performed on the processing unit 136.

[0037] Figure 3 schematically shows a flowchart illustrating a preferred embodiment of the method according to the present invention. To provide real-time OCT images, an image processing process 300 is repeatedly executed, in which scan data is acquired and image data is provided that is displayed on a display means as a picture or OCT image, as described in relation to Figures 1 and 2. This image processing process 300 is repeatedly executed on or using the processing unit 134 (see Figures 1 and 2).

[0038] The image processing process 300 begins with step 310, which involves acquiring a scan dataset from an object using optical coherence tomography. The scan dataset (see reference numeral 122 in Figures 1 and 2) contains one or more spectra, each corresponding to an A scan of the object. In step 312, the scan dataset contained therein is received by the processing system, in particular the corresponding (first) processing unit 134. It should be noted that step 310, which involves acquiring the scan dataset (as defined), may be considered not to be part of the image processing process, in which case it may be considered to be performed prior to the actual image processing. However, this is not essential to the present invention.

[0039] Step 314 performs data processing on the scanned dataset or the spectra contained therein. Typically, such data processing includes DC or baseline removal, spectral filtering, wavenumber resampling, dispersion correction, Fourier transform, scaling, image filtering, and optionally additional image enhancement steps. Step 316, in particular, which applies dispersion correction, is important in relation to the present invention. This dispersion correction is based on the current set of dispersion coefficients 370, i.e., the set of dispersion coefficients currently present in the image processing process used for dispersion correction. The process for whether or not to update such dispersion coefficients will be described later. In this step, a phase correction with respect to the spectrum is calculated and applied to compensate for dispersion. For example, the dispersion cross-spectral density function (essentially the intensity as a function of wavelength or frequency corresponding to the spectrum) can be multiplied by the phase term.

[0040] The dispersion coefficient is used, for example, in second- and third-order polynomials that add a constant amount of phase across each wavelength acquired in OCT spectral data. At this stage, the image is either sharpened or blurred depending on how closely it is matched to the effects of dispersion within the sample. For further information on how to apply such dispersion correction to spectral or scanning data based on the dispersion coefficient, please refer to the literature mentioned above.

[0041] After applying dispersion correction, step 318 provides the dispersion-corrected image dataset (see reference number 142 in Figures 1 and 2). This image dataset is used in step 320 to display the corresponding OCT images on the display means, as described in relation to Figures 1 and 2.

[0042] The variance coefficient fitting process 340 is executed repeatedly on or using the processing unit 136 (see Figures 1 and 2). As previously mentioned, this process is executed concurrently with the image processing process 300. In the variance coefficient fitting process 340, the most recent available scan dataset acquired in step 310 is received in step 342. At this point, step 360 can be performed to check whether the buffer used for the variance coefficient fitting process 340 is free, i.e., whether the variance coefficient fitting process can start in a new cycle (after the previous cycle has finished).

[0043] Next, in step 344, the variance coefficients are fitted using an optimization process 346 performed on the received scan dataset. As a result, a set of fitted variance coefficients 372 is obtained. A more detailed explanation of step 344 is provided hereafter in relation to Figure 4. Then, the set of fitted variance coefficients 372 is provided in step 348, and these fitted coefficients are used to update the current set of variance coefficients 370.

[0044] In step 350, the current set of variance coefficients 370 is updated based on the adapted set of variance coefficients 372. Preferably, a check step 362 is performed prior to the update to determine whether one or more criteria are met in order to determine whether the current set of variance coefficients should be updated. A more detailed explanation of this check and criteria is provided hereafter in relation to Figure 5.

[0045] Figure 4 shows a flowchart illustrating some preferred embodiments of the method according to the present invention, in particular illustrating step 344, which involves fitting the coefficient of variance, including an optimization process 346. After the most recent available scan dataset is received in step 342 (see Figure 3), step 410 performs spectral preprocessing on this data. Such preprocessing may include baseline or DC removal from the (raw) spectrum (typically performed for each of multiple spectra or A scans), filtering, and resampling.

[0046] Next, in step 412, a set of dispersion coefficients is used to calculate and apply phase correction to the scan dataset. The set of dispersion coefficients used in this step may be a set provided in a preceding cycle and provided to the image processing process in step 348 (see Figure 3). Next, in step 414, a Fourier transform of the data with the applied phase correction is performed, resulting in an OCT image. Note that this may include a combination of transformed data from multiple A scans. In step 416, image quality metrics are applied to this OCT image. This may be based on maximum image intensity, image sharpness, image brightness and the overall signal-to-noise ratio of the image, or on another metric to check whether the OCT image is of high quality, for example, with respect to sharpness.

[0047] In step 420, it is checked whether the metric or its result is stable or, for example, improved compared to previous results of the metric. If the metric is stable, the set of dispersion coefficients used for the underlying correction of the OCT image can be considered sufficiently good for further use. Thus, this set of dispersion coefficients can be provided in step 348 as the set of adapted dispersion coefficients 372, as referred to in relation to Figure 3.

[0048] However, if the metric is not stable or improved in step 420, the set of dispersion coefficients used for the underlying correction of the OCT image is considered not good enough for further use and is improved or further optimized in step 430. This may include, for example, a gradient dispersion process or a Nelder-Mead process. The thus improved (or modified) set of dispersion coefficients is then used again in step 412 and the following steps. The process described (as optimization process 346) is run until the metric is stable when checked in step 420. A new cycle of the dispersion coefficient fitting process 340 can then be started using the most recent available scan dataset at that time.

[0049] From this description of optimization process 346, it is clear that this is an iterative process, and that its duration may differ from cycle to cycle, depending on the length of time or number of iterations required for the metric to stabilize. Note that the fitted set of variance coefficients may not differ from the current set 370. In that case, no update is necessary.

[0050] Figure 5 illustrates a preferred embodiment of a further part of the method according to the present invention, in particular a flowchart illustrating a check step 362 for determining whether criteria for deciding whether or not to update the coefficients are met.

[0051] A first criterion 510, which can be checked for satisfaction, requires that the magnitude of the change in the coefficient of variance of the current set exceeds a threshold. This can be applied cumulatively, for example, to each coefficient in the set (if the set contains multiple coefficients) or to each coefficient within the set. For example, criterion 510 may be considered satisfied if at least one of the coefficients has changed in magnitude by at least 5% (or any other appropriate value, e.g., 2%, 3%, 10%, 15%, or 20%). If criterion 510 is not satisfied, update 350 (see Figure 3) is not performed, as shown in step 552. Thus, minor or unnecessary updates or changes are avoided.

[0052] If criterion 510 is met, it may be required to meet an additional criterion 520. This additional criterion may require a verification step to ensure that the optimized OCT image is an upright (or real) image and not an inverted image (which is also obtained within OCT). If criterion 520 is not met, update 350 (see Figure 3) is not performed, as shown in step 552. Thus, inaccurate variance correction is avoided. However, if criterion 520 is also met, update 350 can be performed, or will be performed.

[0053] Such inspection step 362 can be omitted, and it should be noted that the update is performed after each cycle of the variance coefficient fitting process. Alternatively, only one of the criteria mentioned in relation to Figure 5 can be used.

[0054] By using the adaptation (or improvement) of the dispersion coefficient, which is performed continuously and simultaneously, it is possible to image with sufficiently good quality in OCT cases where the dispersion characteristics of the sample (object) change dynamically during live or real-time imaging. For example, dynamic dispersion can occur when air or fluid is introduced into the sample (e.g., into a human eye) during a surgical procedure, and therefore the dispersion characteristics of the optical medium in the sample arm change. Typically, if the dispersion in the sample changes, it is necessary to manually perform the optimization process and recalculate the new optimization coefficient, and it may be necessary to stop imaging until this optimization is complete. This problem is overcome by the proposed technique.

[0055] As used herein, the term "and / or" includes all possible combinations of one or more of the items listed herein and may be abbreviated as " / ".

[0056] While several embodiments have been described in the context of the apparatus, it is clear that these embodiments also represent descriptions of the corresponding methods, where blocks or apparatus correspond to steps or features of steps. Similarly, embodiments described in the context of steps also represent descriptions of the corresponding blocks, items, or features of the corresponding apparatus.

[0057] Some embodiments relate to OCT imaging systems that include a processing system as described in relation to one or more of Figures 1 to 4. Alternatively, the OCT imaging system may be part of a processing system as described in relation to one or more of Figures 1 to 4, or it may be connected to a system as described in relation to one or more of Figures 1 to 4. Figure 1 shows a schematic diagram of an OCT imaging system 100 configured to perform the methods described herein. The OCT imaging system 100 includes an OCT imaging means and a processing or computer system 132. The OCT imaging means is configured to perform imaging and is connected to the processing system 132. The processing system 132 is configured to perform at least a portion of the methods described herein. The processing system 132 may be configured to perform machine learning algorithms. The processing system 132 and the OCT imaging system 100 may be separate entities or may be integrated within a single common housing. The processing system 132 may be part of the central processing system of the OCT imaging system, and / or the processing system 132 may be part of a dependent component of the OCT imaging system 100, such as a sensor, actuator, camera, or lighting unit of the OCT imaging system 100.

[0058] The processing system 132 may be a local computer device (e.g., a personal computer, laptop, tablet computer, or mobile phone) comprising one or more processors and one or more storage devices, or it may be a distributed computer system (e.g., a cloud computing system comprising one or more processors and one or more storage devices distributed to various locations such as local clients and / or one or more remote server farms and / or data centers). The processing system 132 may include any circuit or combination of circuits. In one embodiment, the processing system 132 may include one or more processors, which can be of any kind. As used herein, the processor may be intended to be any kind of computing circuit, such as a microprocessor for a microscope or microscopic component (e.g., a camera), a microcontroller, a composite instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor (DSP), a multicore processor, a field-programmable gate array (FPGA), or any other kind of processor or processing circuit. Other types of circuits that may be included in the processing system 132 may be custom circuits, application-specific integrated circuits (ASICs), etc., such as one or more circuits (communication circuits, etc.) used in wireless devices such as mobile phones, tablet computers, laptop computers, two-way radios, and similar electronic systems. The processing system 132 may also include one or more storage devices that may include one or more memory elements suitable for a particular application, such as main memory in the form of random access memory (RAM), one or more hard drives and / or one or more drives that handle removable media such as compact discs (CDs), flash memory cards, digital video discs (DVDs), etc.The processing system 132 may also include a display device, one or more speakers and a controller which may include a keyboard and / or mouse, trackball, touchscreen, voice recognition device, or any other device which enables the user of the system to input information into and receive information from the processing system 132.

[0059] Some or all of the method steps may be performed by a hardware device (or by using a hardware device), such as a processor, microprocessor, programmable computer, or electronic circuit. In some embodiments, one or more of the most important method steps may be performed by such a device.

[0060] Depending on certain implementation requirements, embodiments of the present invention may be implemented in hardware or software. This implementation is feasible using a non-transient recording medium, which is a digital recording medium, etc., that stores electronically readable control signals and cooperates (or can cooperate) with a programmable computer system to carry out each method. Examples include floppy disks, DVDs, Blu-rays, CDs, ROMs, PROMs and EPROMs, EEPROMs, or FLASH memory. Thus, the digital recording medium may be computer-readable.

[0061] Some embodiments of the present invention include a data carrier having electronically readable control signals that can cooperate with a programmable computer system so as to carry out any of the methods described herein.

[0062] Generally, embodiments of the present invention can be implemented as a computer program product comprising program code, which operates to perform one of the methods when the computer program product is executed on a computer. This program code may be stored, for example, on a machine-readable carrier.

[0063] Another embodiment includes a computer program stored in a machine-readable carrier for carrying out any of the methods described herein.

[0064] Therefore, in other words, embodiments of the present invention are computer programs having program code for carrying out any of the methods described herein when the computer program is executed on a computer.

[0065] Accordingly, another embodiment of the present invention is a recording medium (or data carrier or computer-readable medium) containing a stored computer program for carrying out any of the methods described herein when executed by a processor. The data carrier, digital recording medium, or recording medium is typically tangible and / or non-transient. Another embodiment of the present invention is an apparatus, such as those described herein, comprising a processor and a recording medium.

[0066] Therefore, another embodiment of the present invention is a data stream or signal sequence representing a computer program for carrying out any of the methods described herein. The data stream or signal sequence may be configured to be transmitted, for example, over a data communication connection, such as the Internet.

[0067] Another embodiment includes processing means, for example, a computer or programmable logic device configured or adapted to carry out any of the methods described herein.

[0068] Another embodiment includes a computer having an installed computer program for carrying out any of the methods described herein.

[0069] Another embodiment of the present invention includes an apparatus or system configured to transfer (e.g., electronically or optically) a computer program for carrying out any of the methods described herein to a receiver. The receiver may be, for example, a computer, a mobile device, a storage device, etc. The apparatus or system may include, for example, a file server for transferring the computer program to the receiver.

[0070] In some embodiments, a programmable logic device (e.g., a field-programmable gate array) may be used to perform some or all of the functions of the methods described herein. In some embodiments, the field-programmable gate array may cooperate with a microprocessor to carry out any of the methods described herein. Generally, the methods are advantageously carried out by any hardware device. [Explanation of symbols]

[0071] 100,200 OCT imaging systems 102 Light source 104 Beam Splitter 106 Reference Arm 108,114,116 Optical system 109,115,117 Light beams 110 Reference Mirror 112 Sample Arm 118 Diffraction grating 120 detectors 122 Intensity scanning data 130 Control Unit 132,232 processing systems 134,136 processing units 140 Display means 142 image dataset 150 fiber optic cables 152 Electrical Cables 190 Object 300 Image Processing Processes 310-320 Method Steps 340 Variance coefficient fitting process 342-350 Method Steps 360,362 inspection steps 370 Current set of variance coefficients 372 Set of adapted variance coefficients Steps 410-430, 552 510,520 criteria

Claims

1. A processing system (132, 232) for use with optical coherence tomography imaging means for imaging an object (190), The processing system (132, 232) includes a first processing unit (134) and a second processing unit (136) configured to run in parallel and independently of each other, wherein the first processing unit (134) is configured to repeatedly run an image processing process (300), and the second processing unit (136) is configured to repeatedly run a variance coefficient fitting process (340). The image processing process (300) consists of the following steps, namely: The steps include receiving a new scan dataset (122) from the object (190) acquired using optical coherence tomography (optical coherence tomography) (312), Step (314) of performing data processing on the new scan dataset (122), including step (316) of applying variance correction based on the current set of variance coefficients (370), The steps include providing a variance-corrected image dataset (142) of the object (190) to be displayed, (318), Includes, The aforementioned variance coefficient fitting process (340) consists of the following steps, namely: The steps include receiving the latest available scan dataset (122) from the object (190) acquired using optical coherence tomography (optical coherence tomography) (342), Step (344) of fitting the variance coefficient using an optimization process (346) performed on the latest available scan dataset (122), Step (348) provides a set of adapted variance coefficients (372) used to update the current set of variance coefficients (370), Includes, The processing system (132, 232) is further configured to update the current set of variance coefficients (370) based on the adapted set of variance coefficients (372) whenever the adapted set of variance coefficients (372) becomes available from the variance coefficient adaptation process (340) being performed (350). Processing system (132,232).

2. The processing system (132, 232) is configured to update the current set of dispersion coefficients (370) based on the adapted set of dispersion coefficients (372) after each cycle of the dispersion coefficient adaptation process (340). The processing system according to claim 1 (132, 232).

3. The processing system (132, 232) is configured to update the current set of variance coefficients (370) based on the adapted set of variance coefficients (372) if at least one update criterion (362) is met. The processing system according to claim 1 or 2 (132, 232).

4. The at least one update criterion (362) includes checking whether the magnitude of the change in at least one coefficient between the current update criterion and the adapted update criterion exceeds a threshold. The processing system according to claim 3 (132, 232).

5. The optimization process (346) is performed on the image based on the scan dataset (122) and uses an image quality metric (416), which is based on at least one of the following: maximum image intensity, image sharpness, image brightness, and overall signal-to-noise ratio of the image. The processing system according to any one of claims 1 to 4 (132, 232).

6. The scanning dataset (122) from the object (190) is acquired using spectral region optical coherence tomography. The processing system according to any one of claims 1 to 5 (132, 232).

7. An optical coherence tomography imaging system (100, 200) for imaging an object (190), A processing system (132, 232) according to any one of claims 1 to 6, an optical coherence tomography imaging means, and a display means (140) configured to display an image (144) of the object (190), Optical coherence tomography imaging system (100, 200).

8. The optical coherence tomography imaging system (100) includes a control unit (130) configured to control the optical coherence tomography imaging means, the control unit (130) includes a first processing unit (134) configured to perform the image processing process (300), and a second processing unit (136) configured to perform the variance coefficient fitting process (340). The optical coherence tomography imaging system (100) according to claim 7.

9. The optical coherence tomography imaging system (200) includes a control unit (230) configured to control the optical coherence tomography imaging means, the control unit (230) includes a first processing unit (134) configured to perform the image processing process (300), the optical coherence tomography imaging system (200) includes a second processing unit (136) configured to perform the variance coefficient fitting process (340), the second processing unit (136) is provided separately from the control unit (230), The optical coherence tomography imaging system (200) according to claim 7.

10. The optical coherence tomography imaging system (100, 200) is intended for use during surgical procedures performed on the object (190). The optical coherence tomography imaging system (100, 200) according to any one of claims 7 to 9.

11. A method for imaging an object using optical coherence tomography, The method includes the steps of repeatedly executing an image processing process (300) using a first processing unit (134) and repeatedly executing a variance coefficient fitting process (340) using a second processing unit (136), wherein the first processing unit (134) and the second processing unit (136) are executed in parallel and independently of each other. The image processing process (300) consists of the following steps, namely: The steps include: (310) acquiring a new scanning dataset (122) from the object using optical coherence tomography; Steps (314) include performing data processing on the new scan dataset (122), which includes step (316) applying a variance correction to the new scan dataset (122) based on the current set of variance coefficients (370), The steps include providing a variance-corrected image dataset (142) of the object (190) for the image (144) of the object (190), and displaying the image (144) of the object (190), Includes, The aforementioned variance coefficient fitting process (340) consists of the following steps, namely: The steps include receiving the latest available scan dataset (122) from the object (190) acquired using optical coherence tomography (optical coherence tomography) (342), Step (344) of fitting the variance coefficient using an optimization process (346) performed on the latest available scan dataset (122), The steps include providing a set of adapted variance coefficients (372) (348), Includes, The method further includes the step (350) of updating the current set (370) of the adapted set of variance coefficients (372) based on the adapted set of variance coefficients (372) whenever the adapted set of variance coefficients (372) becomes available from the variance coefficient adaptation process (340) being performed. method.

12. A computer program comprising program code for causing the method described in claim 11 to be executed when the computer program is executed on a processing system (132, 232), Computer program.

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