Estimation of bright flat-field correction based on scanned radiographs.

Abstract

Systems, methods, apparatus, and computer program products are provided for non-invasive scanning of an object using X-ray electromagnetic radiation. One method may include generating at least one two-dimensional X-ray radiographic image, generating composite flat-field data using the at least one two-dimensional X-ray radiographic image, a second two-dimensional X-ray radiographic image, or both, and applying flat-field image correction using the composite flat-field data to the at least one two-dimensional X-ray radiographic image.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This patent application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 429209, filed December 1, 2022.

[0002] Some example embodiments relate generally to detecting X-ray electromagnetic radiation using a scanning device, a scintillator, and an X-ray source. For example, certain example embodiments may relate to systems and / or methods for non-invasive scanning of an object using X-ray electromagnetic radiation. [Background technology]

[0003] X-ray devices, such as computed tomography (CT) devices, can be used to detect defects and / or damage in objects without disassembling the object. However, existing X-ray detection equipment is in need of improvement because it is too expensive for some analyses, too large or bulky to use in some situations, unable to image the interior of an object with adequate resolution, or other problems known in the art. Solutions to these and other problems known in the art are described herein. Summary of the Invention

[0004] According to certain example embodiments, the method may include generating at least one two-dimensional x-ray radiographic image. The method may further include applying flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0005] According to some example embodiments, the apparatus may include means for generating at least one two-dimensional x-ray radiographic image. The apparatus may further include means for applying flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0006] According to various exemplary embodiments, a non-transitory computer-readable medium may include program instructions that, when executed by an apparatus, cause the apparatus to perform at least a method. The method may include generating at least one two-dimensional x-ray radiographic image. The method may further include applying flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0007] According to certain example embodiments, a computer program product may be capable of performing a method. The method may include generating at least one two-dimensional x-ray radiographic image. The method may further include applying flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0008] According to some example embodiments, the apparatus may include at least one processor and at least one memory storing instructions that, when executed by the at least one processor, at least cause the apparatus to generate at least one two-dimensional x-ray radiographic image, the at least one memory and the instructions, when executed by the at least one processor, further cause the apparatus to apply at least flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0009] According to various exemplary embodiments, the device may include circuitry configured to generate at least one two-dimensional x-ray radiographic image. The device circuitry may further apply flat-field image correction using the composite flat-field data to the at least one two-dimensional x-ray radiographic image.

[0010] In certain example embodiments, the synthetic flat-field data may include at least one of unsynthesized data, incomplete data, partial data, and incorrect data.

[0011] In some exemplary embodiments, the synthetic flat-field data may include data generated from multiple tests.

[0012] In various exemplary embodiments, the synthetic flat-field data may include at least one of integrated data and directly collected data.

[0013] In certain exemplary embodiments, the synthetic flat-field data may include extrapolated data.

[0014] In some exemplary embodiments, the estimated composite flat-field data may include data estimated from at least a portion of the radiograph relative to the empty field and predetermined characteristics associated with the representative field.

[0015] In various exemplary embodiments, the synthetic flat-field data may include entirely direct data, entirely synthetic data, or a combination of direct and synthetic data.

[0016] In certain exemplary embodiments, the synthetic flat-field data may include at least one dark-field image, at least one bright-field image, or a combination thereof.

[0017] In some exemplary embodiments, the synthetic flat-field data may be associated with at least one of a low light condition, a low sensitivity condition, and a time of day condition.

[0018] In various exemplary embodiments, the synthetic flat-field data may include at least one pixel that is linearly sensitive to visible light.

[0019] In certain exemplary embodiments, the synthetic flat-field data can be configured for pixelation correction.

[0020] For a proper understanding of the exemplary embodiments, reference should be made to the accompanying drawings. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 1 illustrates an example flow diagram of a method according to certain example embodiments. [Figure 2] Figure 2 shows a flat-field image when no object is present. [Figure 3] Figure 3 shows an uncorrected CT scan of an asthma inhaler. [Figure 4] FIG. 4 shows a corrected image where flat-field correction has been applied to an uncorrected image of an asthma inhaler. [Figure 5] FIG. 5 illustrates an example of an X-ray imaging system according to some example embodiments. [Figure 6] Figure 6 shows an X-ray of an impact driver. [Figure 7] Figure 7 shows a trial flat-field corrected image. [Figure 8] FIG. 8 shows flat-field correction of the radiograph of FIG. 6 using the flat-field corrected image of FIG. [Figure 9] FIG. 9 shows another trial flat-field corrected image. [Figure 10] FIG. 10 shows a composite flat-field corrected image created by stitching together the trial flat-field corrected image of FIG. 7 and another trial flat-field corrected image of FIG. [Figure 11] FIG. 11 shows the flat-field correction of the radiograph of FIG. 6 using the composite flat-field corrected image of FIG. 10 as the bright-corrected image. DETAILED DESCRIPTION OF THE INVENTION

[0022] Flat-field correction (FFC) is a correction process that can be used to correct radiographs taken without the object being scanned in the image. FFC can normalize those radiographs to the same brightness value as if the object were not present in the radiograph. Flat-field images can vary based on scan setting parameters and temporal drift and are therefore traditionally re-imaged for each scan. Collecting these additional FFC images can require additional time to complete the total scan. This can also require moving the object beyond the detector's range, potentially increasing the scanner's envelope (i.e., the size of the scanner's housing) and potentially leading to disadvantages such as unexpected collision of the object with the scanner's interior, resulting in movement of the object, damage to the object, and / or damage to the scanning device.

[0023] Certain exemplary embodiments described herein may have various benefits and / or advantages that overcome the disadvantages discussed above. For example, some exemplary embodiments may improve the quality and efficiency of FFC. Furthermore, various exemplary embodiments may provide faster scans, smaller scanners, more accurate material density reconstruction, reduced ring artifacts, fewer user requirements, and FFC error correction. Accordingly, various exemplary embodiments described below are directed to improving computer-related technology.

[0024] Some example embodiments described herein relate to techniques for estimating FFC information from a scan of an object without requiring additional radiographs to be taken in the absence of the scanned object. In general, flat-field non-uniformity can result from low spatial frequency intensity reduction caused by camera vignetting (i.e., reducing image brightness or saturation toward the periphery of the image) and radial flux reduction from sources, as well as high spatial frequency fixed pattern noise caused by pixel response differences between pixels. Various example embodiments for estimating FFC can handle these two sources of flat-field non-uniformity separately and in different ways, thereby mitigating or eliminating flat-field non-uniformity in different ways.

[0025] FIG. 1 illustrates an example flow diagram of a method that can be performed by a CT scanning device and / or an X-ray imaging system, such as the X-ray imaging system 500 illustrated in FIG. 5, according to various exemplary embodiments. In some exemplary embodiments, the X-ray imaging system and / or scanning device can be configured to perform a CT scan by acquiring and combining multiple X-ray images (i.e., frames) of a scanned object, such as an asthma inhaler. However, multiple parts of multiple types can be scanned simultaneously, independent of source settings, detector settings, etc. Typically, at the start of a scan, for most objects, a motion stage can be moved to a predetermined position that can move the object out of the detector's field of view. Multiple images (e.g., 30 images) can be taken and combined to generate a flat-field image. Once the flat-field image is generated, the motion stage can return to a scan position, and the scan can begin.

[0026] The method may include generating at least one two-dimensional X-ray radiographic image at 101. For each generated radiographic image, the method may include identifying one or more regions in each radiographic image as corresponding to background (i.e., no asthma inhaler) (as shown in radiographic image 200 of FIG. 2) and identifying one or more regions in each radiographic image as corresponding to the scanned object (i.e., the asthma inhaler) (as shown in radiographic image 300 of FIG. 3). Identification may be performed using thresholding and / or machine learning.

[0027] The method may further include generating 110 synthetic flat-field data using at least one two-dimensional X-ray image. In some embodiments, the synthetic flat-field data may include a bright-field image, a dark-field image, or a combination of both. In some embodiments, the synthetic flat-field data may include at least one pixel linearly sensitive to visible light. In some embodiments, operation 110 may include operations 102, 103, and 104. The method may further include, at 102, expanding one or more regions identified as corresponding to the scanned object (identified in 101) by adding a margin of error. For example, the identification of a part compared to the background may be distorted. In some cases, the method may identify a very small boundary to include a portion of the part. While some of the regions identified as the scanned part may include some background, the method may only identify regions identified as background that are devoid of any portion of the scanned part. To avoid this distortion, the boundary between the scanned part and the background may be morphologically expanded to make the boundary larger, thereby increasing the probability that an area of ​​the radiograph identified as background is actually within the background.

[0028] As an example, FIG. 6 shows a radiograph 600 of an impact driver, which may be within the radiograph frame during FFC. Similarly, FIG. 7 shows a trial flat-field corrected image 700 with defects caused by one or more limitations of the X-ray scanner (e.g., spatial and / or size limitations). For example, the part is still partially within the detector's field of view, e.g., in the lower left corner of the detector's field of view. This is because there is not enough space inside the X-ray scanner to move the part completely outside the detector's field of view due to the size of the X-ray scanner. FIG. 8 shows flat-field correction of the radiograph 600 of FIG. 6 using the trial flat-field image 700 of FIG. 7, with saturated pixels in the lower left corner of the flat-field corrected radiograph 800 of FIG. 8.

[0029] FIG. 9 shows another trial flat-field-corrected image 900 with a defect. For example, the part is still partially within the detector's field of view, e.g., in the lower right corner of the detector's field of view. This is because there is not enough space inside the X-ray scanner to move the part completely outside the detector's field of view. The X-ray scanner and / or a computer communicatively connected to the X-ray scanner can generate a composite flat-field-corrected image using the systems and techniques described herein, thereby solving the problem of having the scanned object partially within the flat-field-corrected image. FIG. 10 shows the trial flat-field-corrected image 700 of FIG. 7 and another trial flat-field-corrected image 900 of FIG. 9 stitched together to create a composite flat-field-corrected image 1000 in which the impact driver is shown as if it were completely outside the detector's field of view relative to the FFC image. Furthermore, FIG. 11 shows flat-field correction of the radiograph 600 of FIG. 6 using the composite flat-field-corrected image 1000 of FIG. 10 as a light-corrected image, resulting in a flat-field-corrected radiograph 1100.

[0030] The method may further include, at 103, averaging together all measured pixel values ​​in all background images for pixels identified as background pixels in at least n radiographs (e.g., n=10). As a result, a 2D image may be generated with the average value of all pixels identified as background pixels at least n times, without information about other pixels.

[0031] The method may further include fitting an inverse parabola to background pixels in the resulting image at 104. In the coordinate system, the inverse parabola is represented by gray value = 1 / {a(xx c ) 2 +b(yy c ) 2 +c} and can be generated according to a, b, c, x c and y c is a constant corresponding to the flux drop in X-ray energy as a function of distance from the X-ray source focus, and a is R 2 is the horizontal magnification of the drop rate, and b is R 2 is the vertical magnification of the drop rate, c is the reciprocal of the maximum gray value of the inverse parabola, and x c is the horizontal distance from the origin of the coordinate system to the vertex of the inverse parabola, and y c is the vertical distance from the origin of the coordinate system to the vertex of the inverse parabola. Because the edges of the detector are farther from the X-ray source focus than the center of the detector, the edges may appear darker in the uncorrected radiograph. The generated 2D image can then display the entire interior of the detector, which may provide low-frequency information for the estimated bright FFC image. In some embodiments, the method may further include estimating flat-field information using fitting the inverse parabola to background pixels in the image.

[0032] In various exemplary embodiments, FFC can be applied to scan data using images created by an inverse parabola. Generally, FFC images can be acquired using two settings: a bright image can be acquired with the source on in the settings used for the scan, while a dark image can be acquired with the source off. Specifically, FFC with bright FFC can be performed by dividing each pixel of the scanned radiograph by each pixel of the corrected image and multiplying the result by a target brightness value (e.g., 60,000).

[0033] The method may include applying a flat-field correction (e.g., a pixelation correction) using the composite flat-field data to the at least one two-dimensional x-ray radiographic image at 105. In some examples, the method may include applying the flat-field correction using the composite flat-field data to other scan data collected under scanner conditions different from the scanner conditions of the at least one two-dimensional x-ray radiographic image.

[0034] In various exemplary embodiments, the composite flat-field data may include any combination of uncomposite data (e.g., radiographic images), incomplete data, partial data (e.g., radiographic images of a scanned object outside the field of view of the X-ray scanner), and incorrect data. In some examples, the incorrect data may be radiographic images collected under scanner conditions different from the scanner conditions under which the X-ray radiographic images to which the FFC is applied are collected. For example, the incorrect data may include radiographic images for flat-field correction collected under scanner conditions different from the scanner conditions of the object scan. The composite flat-field data may be generated from radiographic images collected under various scanner conditions. The composite flat-field image may represent flat-field data associated with the scanner conditions under which the X-ray radiographic images to which the FFC is applied are collected. In some examples, the various scanner conditions may include various X-ray source settings, e.g., various current conditions of the X-ray scanner, such as high current conditions and low current conditions. For example, the composite flat-field data under high current conditions may be estimated from the flat-field data under low current conditions, or the composite flat-field data under low current conditions may be estimated from the flat-field data under high current conditions. The estimation may be based on prior information that indicates how the parabola used to generate the flat-field data changes with changes in the X-ray source settings, for example, various current conditions.

[0035] For example, the scanner conditions may include various positions of a part-movement system of an X-ray scanner. The composite flat-field data can be generated from radiographic images collected under scanner conditions when the object is moved to the extreme positions of the part-movement system so that each portion of the detector is exposed to X-rays. The scanner conditions used to capture the radiographic images of the object can be conditions when the object is not moved to the extreme positions of the part-movement system and the detector is blocked by the object.

[0036] Synthetic flat-field data may include data where traditional flat-field data (i.e., taking multiple images with no objects in the field of view and averaging these images together) is augmented with additional information or, in the case of estimated FFC, may be omitted entirely.

[0037] Incorrect data may include cases where the object being scanned happens to be in the field of view of the detector when the image is being captured. Partial and incomplete data may correspond to entire flat-field images that cannot be captured simultaneously. Thus, any single image may be incomplete, and the object may have to be moved to gather the required information. The uncombined data can be used to generate a composite flat-field image, as described in more detail below.

[0038] Additionally or alternatively, the composite flat-field data may include any combination of data generated from multiple tests (e.g., generating flat-field images by interpolation from a look-up table based on a full factorial sweep of scan setting conditions), stitched data, and / or directly collected data (e.g., used to generate an estimated flat-field from the scan itself rather than a prior FFC). For example, the multiple tests may include generating directly collected radiographic images under scanner conditions, e.g., a sweep of various scanner conditions as described above, where the collected radiographic images under the sweep of scanner conditions may be combined, aggregated, and / or later processed to generate the composite flat-field data. This composite flat-field data may be collected before or after the 2D radiographs are generated in 101.

[0039] Additionally, the composite flat-field data may include estimated data derivable from the 2D radiograph generated in 101 including the scanned object. Specifically, the estimated composite flat-field data may include data estimated from at least a portion of the radiograph relative to an empty field and / or predetermined characteristics associated with the representative field. For example, an X-ray scanner or a computer communicatively connected to the X-ray scanner may be configured to obtain partial data in which a component occludes a portion of the radiographic image, fit an inverse parabola to the background region of the radiographic image, and estimate flat-field information behind the component by replacing it with the brightness fit determined from the inverse parabola. The representative field may be a flat-field image not occluded by the component. The predetermined characteristic associated with the representative field may be a coefficient of the inverse parabola fit.

[0040] Additionally, the synthetic flat-field data can include fully direct data, fully synthetic data, or a combination of direct and synthetic data. The synthetic flat-field data can also include any combination of at least one dark-field image and at least one bright-field image. For example, two flat-field images can be used for FFC. The bright-field image can be generated with the source on and the scanner set to the settings used to acquire the scan, with no object and / or a partial object in the field of view. The dark-field image can be generated with the source off, with no object and / or a partial object in the field of view.

[0041] Data can be integrated by stitching together two or more conventionally generated flat-field images. In some embodiments, data can be integrated by stitching together two or more images, at least one of which is generated using the systems and techniques described herein. For example, scanning a large object does not entirely leave the field of view of the detector, regardless of the object's position. As a result, traditional methods of flat-field data generation result in erroneous flat-fields. The integrated data disclosed herein can address this by moving the part to the left and recording flat-field data with at least the right half of the detector unobstructed. The part can then be moved to the right, and flat-field data can be recorded with at least the left half of the detector unobstructed. The two images can then be stitched together, capturing the unobstructed half of each image, resulting in a flat-field image that appears as if it were captured in an empty field.

[0042] The composite flat-field data may be indicative of at least one of a low-light condition (e.g., a 10% decrease in light) and a time condition (e.g., the amount of time elapsed since the FFC measurement was taken). Additionally, the composite flat-field data may include at least one pixel that is linearly sensitive to visible light and may be configured for pixelation correction, e.g., pixel-by-pixel correction or pixel-by-pixel correction. For example, the pixelation correction may include a unique correction for each pixel. In some examples, flat-field correction using the composite flat-field data may be applied to one or more pixels that are linearly sensitive to visible light, one or more pixels that are non-linearly sensitive to visible light, or a combination of both. For example, each pixel may respond linearly to light input, such as in a camera detector of an X-ray scanner using a complementary metal-oxide semiconductor (CMOS) sensor, although each pixel may have a different linear response. Certain exemplary embodiments may measure representative bright sky-field images and dark images that can be used to correct each pixel so that, after applying the correction, all pixels are zero when no light is measured and all pixels with no object present are a constant value.

[0043] At 106, following application of the estimated FFC, in some embodiments, the method may include attributing any remaining artifacts to fixed pattern noise due to the unique responsivity of each pixel and generating a composite image, such as image 400 shown in Figure 4. This can be corrected by applying a ring artifact correction method. Because some or all pixels may be slightly miscalibrated, ring artifact correction may normalize pixels to neighboring pixels, which may represent fixed pattern noise still present after removal of low-frequency inhomogeneities.

[0044] 5 illustrates an example of an X-ray imaging system 500. The X-ray imaging system 500 includes a CT scanning device 510 that can be configured to perform CT imaging. The X-ray imaging system 500 can include a computer 512 communicatively coupled to the CT scanning device 510. The computer 512 can include a hardware processor, e.g., one or more processors 514, and a non-transitory computer-readable medium, e.g., memory 516. The CT scanning device 510, the computer 512, or a combination of both, can perform the flat-field correction described herein. For example, the memory 516 of the computer 512 can encode instructions configured to cause the processor 514 to perform the flat-field correction described herein.

[0045] The CT scanning device 510 may include a scintillator 501 and an X-ray source 502 configured to emit X-rays 503 through a scan target 504 to a front surface 505 of the scintillator 501. The CT scanning device 510 may further include a detector 506 configured to detect at least one fluorescence signal 507 (i.e., infrared, ultraviolet, or visible light) from a rear surface 508 of the scintillator 501. In various exemplary embodiments, the detector 506 may be aimed directly at the rear surface 508 (as shown in FIG. 5 ), or the scintillator 501 may be oriented perpendicular to the X-ray source 502.

[0046] In some exemplary embodiments, scintillator 501 may include a substrate layer, which may be composed of any of polycarbonate, polyacrylate, polyethylene terephthalate (PET), and barrier films including metal oxides.

[0047] In certain exemplary embodiments, the x-ray source 502 may be at least one of a sealed tube x-ray source, an open tube x-ray source, a cold cathode x-ray source, a rotating anode x-ray source, a fixed anode x-ray source, a liquid metal anode x-ray source, and a triboluminescence x-ray source.

[0048] The scan target 504 may include any of inorganic materials, organic materials, metals, plastics, composites, carbon, non-carbon, multi-component and multi-layer parts.

[0049] In certain exemplary embodiments, detector 506 may include any combination of a complementary metal-oxide semiconductor (CMOS) digital camera sensor, a red-green-green-blue (RGGB) Bayer filter, an optical camera, a monochrome optical camera, a back-illuminated sensor, a front-illuminated sensor, a charge-coupled device (CCD) detector, a photodiode, an X-ray flat panel detector, etc. In certain exemplary embodiments, detector 506 may be configured to detect fluorescent signals 507 from front surface 505 and / or back surface 508.

[0050] Any of the devices of the X-ray imaging system 500 may include at least one processor, which may be realized by any computing or data processing device, such as a central processing unit (CPU), an application specific integrated circuit (ASIC), or equivalent device. The processor may be implemented as a single controller or multiple controllers or processors.

[0051] At least one memory may be provided in one or more of the devices of the X-ray imaging system 500. The memory may be fixed or removable. The memory may include computer program instructions or computer code therein. The memory may independently be any suitable storage device, such as a non-transitory computer-readable medium. The term "non-transitory" as used herein may correspond to a limitation of the medium itself (i.e., tangible, not signal), as opposed to a limitation on data storage permanence (e.g., random access memory (RAM) vs. read-only memory (ROM)). A hard disk drive (HDD), random access memory (RAM), flash memory, or other suitable memory may be used. The memory may be combined with the processor in a single integrated circuit or may be separate from one or more processors. Furthermore, the computer program instructions stored in the memory and processable by the processor may be any suitable form of computer program code, for example, a compiled or interpreted computer program written in any suitable programming language.

[0052] The processor and memory can be configured to provide means corresponding to the various blocks in Figure 1. Although not shown, the device may also include location determination hardware, such as GPS or microelectromechanical systems (MSMS) hardware that can be used to determine the location of the device. Other sensors are possible and can be configured to determine location, altitude, speed, heading, etc., such as a barometer, compass, etc.

[0053] The memory and computer program instructions may be configured by a processor for a particular device to cause a hardware apparatus, such as a UE, to perform any of the processes described above (i.e., FIG. 1). Thus, in certain example embodiments, a non-transitory computer-readable medium may be encoded with computer instructions that, when executed in hardware, perform a process, such as one of the processes described herein. Alternatively, certain example embodiments may be performed entirely in hardware.

[0054] In certain exemplary embodiments, a device may include circuitry configured to perform any of the processes or functions shown in FIG. 1 . As used herein, the term “circuitry” refers to one or more or all of the following: (a) a hardware-only circuit implementation (e.g., an implementation with only analog and / or digital circuitry); (b) a combination of hardware circuitry and software, including (where applicable) (i) a combination of analog and / or digital hardware circuitry and software / firmware; and (ii) any portion of a hardware processor with software (including digital signal processors, software, and memory that interact to cause a device, such as a cell phone or server, to perform various functions); and (c) a hardware circuit and / or processor, such as a microprocessor or portion of a microprocessor, that requires software (e.g., firmware) for operation, although software may be absent if not necessary for operation. This definition of circuitry applies to all uses of the term in this application, including any claims. As a further example, as used herein, the term “circuitry” also encompasses implementations of simply a hardware circuit or processor (or processors) or portion of a hardware circuit or processor and its (or their) accompanying software and / or firmware. The term "circuitry" also encompasses, for example, and where applicable to particular claim elements, baseband or processor integrated circuits for similar integrated circuits in mobile devices or servers, cellular network devices, or other computing or network devices.

[0055] In some exemplary embodiments, the X-ray imaging system 500 (and any of the devices within the X-ray imaging system 500) may include means for performing any of the methods, processes, or variations described herein. Examples of means may include one or more processors, memories, controllers, transmitters, receivers, and / or computer program code that cause the operations to be performed.

[0056] In various exemplary embodiments, the X-ray imaging system 500 (and any of the devices within the X-ray imaging system 500) may be controlled by a memory and a processor to adjust at least one operating parameter based on the material composition of the scan target, calculate an exposure time parameter per frame based on the total number of frames and the total time elapsed between acquiring the frames, and acquire at least one X-ray frame of the scan target based on the at least one adjusted operating parameter and the calculated exposure time parameter.

[0057] Certain example embodiments may be directed to an apparatus including means for performing any of the methods described herein, including, for example, means for adjusting at least one operating parameter based on a material composition of the scan target, calculating an exposure time parameter per frame based on a total number of frames and a total time elapsed between acquiring the frames, and acquiring at least one X-ray frame of the scan target based on the at least one adjusted operating parameter and the calculated exposure time parameter.

[0058] The features, structures, or characteristics of the exemplary embodiments described throughout this specification may be combined in any suitable manner in one or more exemplary embodiments. For example, the use of the phrases "various embodiments," "particular embodiments," "some embodiments," or other similar terms throughout this specification means that a particular feature, structure, or characteristic described in connection with an exemplary embodiment may be included in at least one exemplary embodiment. Thus, appearances of the phrases "in / various embodiments," "in / particular embodiments," "in / some embodiments," or other similar terms throughout this specification do not necessarily all refer to the same group of exemplary embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more exemplary embodiments.

[0059] Moreover, if desired, the various functions or procedures described may be performed in different orders and / or concurrently with one another. Still further, if desired, one or more of the functions or procedures described may be optional or combined. As such, the foregoing description should be interpreted as illustrative of the principles and teachings of particular exemplary embodiments, and not as a limitation thereof.

[0060] It should be readily understood that the components of the specific exemplary embodiments, as generally described and illustrated in the Figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the above detailed description of certain exemplary embodiments of systems, methods, apparatuses and computer program products for non-invasive scanning of objects using X-ray electromagnetic radiation is not intended to limit the scope of the specific exemplary embodiments, but rather to represent selected exemplary embodiments.

[0061] Those skilled in the art will readily appreciate that the above exemplary embodiments may be implemented using steps in a different order and / or with hardware elements in different configurations than those disclosed. Thus, while certain embodiments have been described in terms of those exemplary embodiments, it will be apparent to those skilled in the art that certain modifications, variations, and alternative configurations will be apparent while remaining within the spirit and scope of the exemplary embodiments.

[0062] The above embodiments and examples are merely illustrative and not limiting. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, numerous equivalents to the specific compounds, materials, and procedures. All such equivalents are considered to be within the scope and are encompassed by the appended claims. [Example]

[0063] While the present application is defined in the appended claims, it should be understood that the invention may also be defined (additionally or alternatively) by the following examples.

[0064] Example 1: A method for flat-field image correction, comprising: generating at least one two-dimensional x-ray radiographic image; applying flat-field image correction using the composite flat-field data to at least one two-dimensional x-ray radiographic image; A method for providing

[0065] Example 2: The method of example 1, wherein the synthetic flat-field data includes at least one of unsynthesized data, incomplete data, partial data, and incorrect data.

[0066] Example 3: The method of any of Examples 1 and 2, wherein the synthetic flatfield data comprises data generated from multiple tests.

[0067] Example 4: The method of any of Examples 1 to 3, wherein the synthetic flat-field data comprises stitched data.

[0068] Example 5: The method of any of Examples 1 to 4, wherein the synthetic flatfield data includes at least one of integrated data and directly collected data.

[0069] Example 6: The method of any of Examples 1 to 5, wherein the synthetic flatfield data includes extrapolated data.

[0070] Example 7: The method of Example 6, wherein the estimated composite flat-field data includes data estimated from at least a portion of the radiograph relative to the empty field and predetermined characteristics associated with the representative field.

[0071] Example 8: The method of any of Examples 1 to 7, wherein the synthetic flatfield data comprises entirely direct data, entirely synthetic data, or a combination of direct data and synthetic data.

[0072] Example 9: The method of any of Examples 1 to 8, wherein the synthetic flat-field data includes at least one dark-field image, at least one bright-field image, or a combination thereof.

[0073] Example 10: The method of any of Examples 1 to 9, wherein the synthetic flat-field data is associated with at least one of a low light condition, a low sensitivity condition, and a time of day condition.

[0074] Example 11: The method of any of Examples 1 to 10, wherein the synthetic flat-field data includes at least one pixel that is linearly sensitive to visible light.

[0075] Example 12: The method of example 11, wherein the synthetic flat-field data is configured for pixelation correction.

[0076] Similar operations and processes described in Examples 1-12 can be performed in a system including at least one processor and a memory communicatively coupled to the at least one processor, the memory storing instructions that, when executed, cause the at least one processor to perform the operations. Also possible is a non-transitory computer-readable medium storing instructions that, when executed, cause the at least one processor to perform the operations described in any one of Examples 1-12.

[0077] Example 13: A method for flat-field image correction, comprising: generating at least one two-dimensional x-ray radiographic image; generating composite flat-field data using at least one two-dimensional radiographic image, a second two-dimensional radiographic image, or both; applying flat-field image correction using the composite flat-field data to at least one two-dimensional x-ray radiographic image; A method for providing

[0078] Example 14: The method of Example 13, wherein the step of generating the synthetic flat-field data includes a step of generating the synthetic flat-field data using at least a second two-dimensional X-ray radiographic image of the object to be scanned that is partially outside the field of view of an X-ray scanner that scans the object to be scanned.

[0079] Example 15: The step of generating synthetic flat-field data comprises: generating a two-dimensional image including background pixels that do not include the scanned object, the background pixels of the two-dimensional image being generated using one or more background pixels in at least one two-dimensional radiographic image, a second two-dimensional radiographic image, or both; fitting an inverse parabolic function to background pixels of the two-dimensional image; generating synthetic flat-field data using an inverse parabolic function fitted to background pixels of the two-dimensional image; 15. The method of any of Examples 13 or 14, comprising:

[0080] Example 16: The method of Example 15, wherein the pixel value of a background pixel in the two-dimensional image is the average of the values ​​of corresponding background pixels in at least two radiographic images.

[0081] Example 17: The method of any of Examples 13 to 16, wherein the synthetic flat-field data includes data generated from a second two-dimensional x-ray radiographic image collected under scanner conditions different from the scanner conditions under which the at least one two-dimensional x-ray radiographic image was collected.

[0082] Example 18: The method of any of Examples 13 to 17, wherein the synthetic flat-field data includes data generated from stitched data.

[0083] Example 19: The method of any of Examples 13 to 18, wherein the composite flat-field data comprises data generated from multiple radiographic images collected under multiple scanner conditions.

[0084] Example 20: The method of Example 19, wherein generating the composite flat-field data comprises generating the composite flat-field data by integrating multiple radiographic images collected under multiple scanner conditions.

[0085] Example 21: The method of any of Examples 13 to 20, wherein the synthetic flatfield data comprises estimated synthetic flatfield data.

[0086] Example 22: The method of Example 21, wherein the estimated composite flat-field data includes data estimated from at least a portion of the radiograph relative to the empty field and predetermined characteristics associated with the representative field.

[0087] Example 23: The method of any of Examples 13 to 22, wherein the synthetic flat-field data comprises at least one dark-field image, at least one bright-field image, or a combination thereof.

[0088] Example 24: The method of any of Examples 13 to 23, wherein the synthetic flat-field data is associated with at least one of a low light condition, a low sensitivity condition, and a time of day condition.

[0089] Example 25: The method of any of Examples 13 to 24, wherein the synthetic flat-field data includes at least one pixel that is linearly sensitive to visible light.

[0090] Example 26: The method of any of Examples 13 to 25, wherein the synthetic flat-field data is configured for pixelation correction.

[0091] Similar operations and processes described in Examples 13 to 26 can be performed in a system including an X-ray scanner and a computer communicatively connected to the X-ray scanner, the computer including a hardware processor and a non-transitory computer-readable medium encoding instructions configured to cause the hardware processor to perform the operations and processes. Also possible is a non-transitory computer-readable medium comprising instructions that, when executed by an apparatus, cause the apparatus to perform the operations described in any of Examples 13 to 26. In some embodiments, features of Examples 13 to 26 may be combined with features according to Examples 1 to 12 described above.

[0092] Partial glossary CMOS Complementary Metal Oxide Semiconductor CT Computed Tomography dB decibel FFC Flat Field Correction GV Gray Value kV kilovolts mA milliampere ML Machine Learning

Claims

1. 1. A method of flat-field image correction, comprising: generating (101) at least one two-dimensional X-ray radiographic image; for each radiographic image of the at least one two-dimensional x-ray radiographic image, identifying one or more regions of each radiographic image as corresponding to background, and one or more other regions of each radiographic image corresponding to the scanned object; generating (110) composite flat-field data based on pixels in the one or more regions of each radiographic image of the at least one two-dimensional x-ray radiographic image corresponding to the background; applying (105) flat-field image correction using said composite flat-field data to i) said at least one 2D X-ray radiographic image or ii) another 2D X-ray radiographic image; A method for providing

2. 2. The method of claim 1, wherein the at least one two-dimensional x-ray radiographic image comprises a two-dimensional x-ray radiographic image of the object that is partially outside the field of view of an x-ray scanner that scans the object.

3. The step of generating synthetic flat-field data comprises: generating a two-dimensional image including background pixels not including the scanned object, the background pixels of the two-dimensional image being generated using pixels in the one or more regions of each radiographic image of the at least one two-dimensional x-ray radiographic image that correspond to the background; fitting an inverse parabolic function to the background pixels of the two-dimensional image; generating the synthetic flat-field data using the inverse parabolic function fitted to the background pixels of the two-dimensional image; The method of claim 1 , comprising:

4. 4. The method of claim 3, wherein the pixel values ​​of the background pixels of the two-dimensional image are an average of values ​​of corresponding pixels in the one or more regions corresponding to the background in at least two radiographic images of the at least one two-dimensional x-ray radiographic image.

5. 10. The method of claim 1, wherein the composite flat-field data comprises data generated from at least two radiographic images of the at least one two-dimensional x-ray radiographic image, the at least two radiographic images being acquired under different scanner conditions.

6. The method of claim 1 , wherein the synthetic flat-field data comprises data generated from stitched data.

7. The method of claim 1 , wherein the synthetic flat-field data comprises data generated from multiple radiographic images acquired under multiple scanner conditions.

8. 8. The method of claim 7, wherein generating the composite flat-field data comprises generating the composite flat-field data by integrating the multiple radiographic images acquired under the multiple scanner conditions.

9. The method of claim 1 , wherein the synthetic flat-field data comprises estimated synthetic flat-field data.

10. 10. The method of claim 9, wherein the estimated composite flat-field data comprises data estimated from predetermined characteristics associated with at least a portion of a radiograph relative to an empty field and a representative field, the representative field including a flat-field image not occluded by the scanned object.

11. The method of any one of claims 1 to 10, wherein the synthetic flat-field data comprises at least one dark-field image, at least one bright-field image, or a combination thereof.

12. The method of any one of claims 1 to 10, wherein the synthetic flat-field data is associated with at least one of a low light condition, a low sensitivity condition, and a time of day condition.

13. The method of any one of claims 1 to 10, wherein the synthetic flat-field data comprises at least one pixel that is linearly sensitive to visible light.

14. The method of any one of claims 1 to 10, wherein the synthetic flat-field data is configured for pixelation correction.

15. 1. A system comprising: An X-ray scanner; a computer communicatively connected to the X-ray scanner, the computer comprising a hardware processor; receiving or generating at least one two-dimensional x-ray radiographic image from or using said x-ray scanner; for each radiographic image of the at least one two-dimensional x-ray radiographic image, identifying one or more regions of each radiographic image as corresponding to background, and one or more other regions of each radiographic image corresponding to the scanned object; generating composite flat-field data based on pixels in the one or more regions of each radiographic image of the at least one two-dimensional x-ray radiographic image corresponding to the background; applying flat-field image correction using the composite flat-field data to i) the at least one two-dimensional x-ray radiographic image or ii) another two-dimensional x-ray radiographic image; a non-transitory computer-readable storage medium having stored thereon computer program instructions configured to cause a computer to perform operations comprising: A system comprising:

16. 16. The system of claim 15, wherein the at least one two-dimensional x-ray radiographic image comprises a two-dimensional x-ray radiographic image of the object that is partially outside the field of view of the x-ray scanner that scans the object.

17. The step of generating synthetic flat-field data comprises: generating a two-dimensional image including background pixels not including the scanned object, the background pixels of the two-dimensional image being generated using pixels in the one or more regions of each radiographic image of the at least one two-dimensional x-ray radiographic image that correspond to the background; fitting an inverse parabolic function to the background pixels of the two-dimensional image; generating the synthetic flat-field data using the inverse parabolic function fitted to the background pixels of the two-dimensional image; The system of claim 15, comprising:

18. 18. The system of claim 17, wherein the pixel values ​​of the background pixels of the two-dimensional image are an average of values ​​of corresponding pixels in the one or more regions corresponding to the background in at least two radiographic images of the at least one two-dimensional x-ray radiographic image.

19. 16. The system of claim 15, wherein the composite flat-field data comprises data generated from at least two radiographic images of the at least one two-dimensional x-ray radiographic image, the at least two radiographic images being acquired under different scanner conditions.

20. The system of claim 15 , wherein the synthetic flat-field data comprises data generated from stitched data.

21. 16. The system of claim 15, wherein the synthetic flat-field data comprises data generated from multiple radiographic images acquired under multiple scanner conditions.

22. 22. The system of claim 21, wherein generating the composite flat-field data comprises generating the composite flat-field data by integrating the multiple radiographic images acquired under the multiple scanner conditions.

23. The system of claim 15 , wherein the synthetic flat-field data comprises estimated synthetic flat-field data.

24. 24. The system of claim 23, wherein the estimated composite flat-field data comprises data estimated from predetermined characteristics associated with at least a portion of a radiograph relative to an empty field and a representative field, the representative field including a flat-field image not occluded by the scanned object.

25. The system of any one of claims 15 to 24, wherein the synthetic flat-field data comprises at least one dark-field image, at least one bright-field image, or a combination thereof.

26. The system of any one of claims 15 to 24, wherein the synthetic flat-field data is associated with at least one of a low light condition, a low sensitivity condition, and a time of day condition.

27. The system of any one of claims 15 to 24, wherein the synthetic flat-field data includes at least one pixel that is linearly sensitive to visible light.

28. The system of any one of claims 15 to 24, wherein the synthetic flat-field data is configured for pixelation correction.

29. A non-transitory computer readable storage medium having stored thereon computer program instructions operable to cause a data processing apparatus to perform the method of any one of claims 1 to 9.

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