Method for automatically setting computed tomography scan parameters - Patent Application 20070122963

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 adjusting, by a computed tomography scanning device, at least one operating parameter including a gray value threshold based on a material composition of the scanned object, calculating, by the computed tomography scanning device, an exposure time, optionally including calculating an exposure time per frame based on at least one of a total number of frames and a total elapsed time while acquiring the frames, and acquiring, by the computed tomography scanning device, at least one X-ray frame of the scanned object based on the adjusted at least one operating parameter and the calculated exposure time.

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 / 403,161, filed September 1, 2022, which is incorporated herein by reference in its entirety.

[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 a system and / or method for non-invasive scanning of an object using X-ray electromagnetic radiation. [Background technology]

[0003] X-ray equipment, such as computed tomography (CT) devices, can be used to detect defects and / or damage within an object without disassembling the object. However, current X-ray detection equipment is in need of improvement because it is prohibitively expensive for certain analyses, too large or bulky to be used in certain situations, unable to image the interior of an object with adequate resolution, or due to 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 adjusting at least one operational parameter based on a material composition of the scanned object. The method may further include calculating a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The method may further include acquiring at least one x-ray frame of the scanned object based on the adjusted at least one operational parameter and the calculated exposure time parameter.

[0005] According to some example embodiments, the method may further include setting at least one of the source beam energy parameters to a predetermined maximum value.

[0006] According to various exemplary embodiments, the method may further include setting a camera gain parameter to a high value based on a predetermined threshold.

[0007] According to certain example embodiments, the method may further include positioning and magnifying the image of the scanned object according to an object detection algorithm.

[0008] According to some example embodiments, the method may further include determining whether the scanned object is one material or multiple materials.

[0009] According to various exemplary embodiments, the method may further include determining whether a minimum valid gray value associated with the image to be scanned is greater than a gray value threshold.

[0010] According to certain example embodiments, the method may further include determining whether the focus is static or dynamic in response to determining that the filtering parameter is set to a maximum filtering value or that the minimum valid gray value is higher than the gray value threshold.

[0011] According to some example embodiments, the method may further include reducing the source beam current parameter until focal spot size≦pixel size / (magnification−1) is satisfied.

[0012] According to various exemplary embodiments, the method may further include calculating the source beam current parameter until focal spot size≦pixel size / (magnification−1) is satisfied.

[0013] According to certain example embodiments, the method may further include calculating an exposure time per frame based on at least one of a total number of frames and a total elapsed time while acquiring the frames.

[0014] According to some example embodiments, the method may further include determining whether the exposure time per frame is greater than a maximum exposure time per frame threshold.

[0015] According to various exemplary embodiments, the method may further include, in response to determining that the exposure time per frame is less than or equal to the maximum exposure time per frame threshold, determining whether the exposure time per frame is less than a minimum exposure limit threshold.

[0016] According to certain example embodiments, the method may further include, in response to determining that the exposure time per frame is less than or equal to the maximum exposure time per frame threshold, determining whether the exposure time per frame is less than a minimum exposure limit threshold.

[0017] According to some example embodiments, the method may further include adjusting the camera gain to set the effective maximum grey value to the effective maximum grey value threshold.

[0018] According to various exemplary embodiments, the method may further include determining whether the camera gain satisfies a valid maximum gray value.

[0019] According to certain example embodiments, the method may further include determining whether the total number of projections is less than a maximum total number of projections threshold.

[0020] According to some exemplary embodiments, the method may further include, in response to determining that the total number of projections is less than a maximum total number of projections threshold, calculating any one of a noise-optimal distribution of the scan projections, the bright flat-field corrected projections, and the dark flat-field corrected projections based on the total number of projections.

[0021] According to various exemplary embodiments, the method may further include scanning the scan object according to the at least one determined parameter.

[0022] According to some example embodiments, the method may include adjusting, by the computed tomography scanning device, at least one operating parameter based on a material composition of the scan object. The method may further include calculating, by the computed tomography scanning device, a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The method may further include acquiring, by the computed tomography scanning device, at least one X-ray frame of the scan object based on the adjusted at least one operating parameter and the calculated exposure time parameter.

[0023] According to certain exemplary embodiments, the apparatus may include means for adjusting at least one operating parameter based on a material composition of the scanned object. The apparatus may further include means for calculating a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The apparatus may further include means for acquiring at least one x-ray frame of the scanned object based on the adjusted at least one operating parameter and the calculated exposure time parameter.

[0024] According to various exemplary embodiments, a non-transitory computer-readable medium may be encoded with instructions that, when executed on hardware, may perform a method. The method may include adjusting at least one operational parameter based on a material composition of the scanned object. The method may further include calculating a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The method may further include acquiring at least one x-ray frame of the scanned object based on the adjusted at least one operational parameter and the calculated exposure time parameter.

[0025] According to some example embodiments, the computer program product may perform a method. The method may include adjusting at least one operational parameter based on a material composition of the scanned object. The method may further include calculating a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The method may further include acquiring at least one x-ray frame of the scanned object based on the adjusted at least one operational parameter and the calculated exposure time parameter.

[0026] According to certain example embodiments, the apparatus may include at least one processor and at least one memory containing computer program code. The at least one memory and computer program code may be configured by the at least one processor to cause the apparatus to at least adjust at least one operating parameter based on a material composition of the scanned object. The at least one memory and computer program code may be further configured by the at least one processor to cause the apparatus to at least calculate a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The at least one memory and computer program code may be further configured by the at least one processor to cause the apparatus to at least acquire at least one x-ray frame of the scanned object based on the adjusted at least one operating parameter and the calculated exposure time parameter.

[0027] According to various exemplary embodiments, the apparatus may include circuitry configured to adjust at least one operating parameter based on a material composition of the scanned object. The circuitry may be further configured to calculate a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring the frames. The circuitry may be further configured to acquire at least one x-ray frame of the scanned object based on the adjusted at least one operating parameter and the calculated exposure time parameter.

[0028] For a proper understanding of the exemplary embodiments, reference should be made to the accompanying drawings. [Brief explanation of the drawings]

[0029] [Figure 1A] 1 illustrates an example flow diagram of a method according to various exemplary embodiments. [Figure 1B] 1 illustrates an example flow diagram of a method according to various exemplary embodiments. [Figure 1C] 1 illustrates an example flow diagram of a method according to various exemplary embodiments. [Figure 2A] 10 shows a radiograph of a single image of an aluminum step wedge (top) and a polymer step wedge (bottom), according to some example embodiments. [Figure 2B] 1 shows an example of a scatter plot of a scene with a multi-material scanned object, distinguishing between different materials. [Figure 3] 1 illustrates an example of an X-ray imaging system in accordance with certain illustrative embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0030] It should be readily understood that the components of the specific exemplary embodiments, as generally described and illustrated herein, could be arranged and designed in a wide variety of different configurations. Thus, the following 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 is merely representative of selected exemplary embodiments.

[0031] In the CT scanning art, and as used throughout this disclosure, a "projection" can refer to an image used as input to a reconstruction algorithm, and a "frame" can refer to an image captured by a detector. In a one frame per projection setting, a projection can comprise a single frame. With more frames per projection, multiple images can be taken that can then be averaged together into a single projection.

[0032] Certain exemplary embodiments described herein may have various advantages and / or benefits that overcome the disadvantages described above. For example, certain exemplary embodiments may improve the quality of images of the interior of an object at an appropriate resolution. In some examples, systems and techniques may improve the contrast-to-noise ratio of CT reconstructed images. In some examples, systems and techniques may reduce one or more artifacts in CT reconstructed images, such as reducing beam-hardening artifacts. Furthermore, various automatic adjustment methods may improve the resolution of fine features for both the interior and exterior of a scanned object, improve the discrimination of different materials in a multi-material scanned object, improve dimensional accuracy measurements, and reduce artifacts related to beam hardening. Some exemplary embodiments may also lead to time-optimized scans, where automatic adjustment may enable a given scan quality to be achieved in a one-hour scan instead of a two-hour scan. Various exemplary embodiments may improve setting beam energy parameters, setting the amount of filtering, and distinguishing between single-material and multi-material characteristics of a scanned portion. Accordingly, certain exemplary embodiments described below are directed to advances in computer-related technology.

[0033] 1A-1C illustrate an example flow diagram of a method that may be performed by a scanning device, such as the CT scanning device 300 shown in FIG. 3 according to various exemplary embodiments. In some exemplary embodiments, the scanning device may be configured to perform a CT scan by acquiring and combining multiple X-ray images (i.e., frames).

[0034] At 100, the method may include receiving input from a user related to scan parameters to initiate the scan process. For example, the received input may include any combination of scan time and scan quality (e.g., fine feature resolution, multi-material discrimination).

[0035] At 101, the method may include setting at least one of the source beam energy parameters to a specified source beam energy maximum (e.g., 120 kV, 190 kV), which may be the maximum beam energy achievable by the scanning device.

[0036] Additionally or alternatively, the method may include setting the source beam current parameter to a predetermined maximum source beam current achievable by the scanning device (e.g., 0.3 mA, 0.5 mA, 0.75 mA) and / or setting the filtering parameter to a minimum value (e.g., 0). As an example, the scanning device may include an X-ray source with a fixed focal spot size and / or an X-ray source with a dynamic focal spot size. Generally, a fixed focal spot X-ray source will have a focal spot that does not change as a function of the X-ray source parameters. The focal spot size of a dynamic focal spot X-ray source will increase as the X-ray power increases. Therefore, for a fixed focal spot size, increasing the source beam current will not degrade scan performance. In contrast, a dynamic focal spot size will have a larger focal spot for higher X-ray power. Therefore, at a preselected beam energy, increasing the beam current will increase the focal spot size.

[0037] At 102, the method may include setting a camera gain parameter (i.e., amplification factor) to a high value based on a predetermined threshold (e.g., 30 dB, 40 dB, 50 dB). As an example, the camera gain parameter may be set so that the 98th percentile luminance of the scanning device is between 57,000 and 63,000 counts (i.e., a 16-bit image ranging from 0 counts to 65,535 counts). Additionally or alternatively, the method may include setting a camera exposure parameter based on a predetermined threshold; for example, the camera exposure parameter may be set to 0.5 seconds or less.

[0038] At 103, the method may include automatically positioning and magnifying the image of the scanned object. In some example embodiments, the positioning of the scanned object may be performed using an object detection algorithm, such as an object machine learning (ML)-based bounding box algorithm. The ML bounding box algorithm may set the magnification and positioning of the image of the scanned object such that the boundary of the scanned object does not extend outside the scanning device.

[0039] At 104, the method may include determining the material composition of the scanned object, i.e., whether the scanned object is mono- or poly-material (e.g., 100% aluminum, or 45% tin, 15% carbon, and 40% iron). In one example, the scanning device may receive user input specifying whether the scanned object has a mono- or poly-material material composition. Alternatively, the scanning device may automatically determine whether the scanned object has a mono- or poly-material material composition using a material detection algorithm. Specifically, the material detection algorithm may include a series of data collection steps. The scanned object is rotated a predetermined minimum number of times (e.g., two times), and the scanning device captures images of the scanned object with varying levels of filtering or beam energy (e.g., two levels). Once the images are captured, the scanning device may classify the scanned object based on a scatter plot of the unfiltered gray values ​​(GV) of all pixels plotted against the filtered GV of all pixels, such as those shown in FIGS. 2A-2B.

[0040] FIG. 2A shows a single-image radiograph of an aluminum step wedge (top) and a polymer step wedge (bottom). In this example, the step wedge can be a wedge with multiple steps of varying thickness. The radiograph was taken with the x-ray source beam energy set at a relatively high and low value. After taking the two images, each pixel in the radiograph can have two recorded GVs. One GV corresponds to the high x-ray source beam energy value, and the other GV corresponds to the low x-ray source beam energy value.

[0041] The scatter plot shown in FIG. 2B can be generated by plotting a point for each pixel. The x value represents the GV value when the beam energy is below a threshold value, and the y value represents the GV value when the beam energy is above the threshold value (e.g., the maximum beam energy (130 kV) for high values ​​and half the maximum beam energy (65 kV) for low values). As a result, if the material composition of the scanned portion (i.e., the step wedge) is one material, all of the pixels may form a single compact curve on the scatter plot. Alternatively, if the scanned portion is multi-material, the scatter plot may depict multiple well-defined curves (as shown in FIG. 2B), or if different materials overlap each other, the scatter plot may depict a single thick curve. In this way, the thickness of the curves on the scatter plot indicates the range of materials comprising the scanned portion. For example, the scattered points may be grouped into one curve for a one-material scan target, two curves for a two-material scan target, three curves for a three-material scan target, and so on. The method may accordingly include setting an operational parameter (e.g., a GV threshold) to a first predetermined GV value (e.g., 7000 counts) if the scanned object is a single material, or may alternatively include setting the GV threshold to a second predetermined GV value (e.g., 15000 counts) in response to determining that the scanned object is a multi-material. In some exemplary embodiments, the first / second GV thresholds may be related to luminance, such as pixel luminance or pixel brightness. For example, in a monochrome 16-bit image, each pixel may have 16 bits corresponding to luminance, where a value of 0 may be pure black and a value of 65535 may be pure white.

[0042] At 105, the method may include determining whether the minimum effective GV is greater than a GV threshold. The minimum effective gray value is a representative value for how dark the detector gray values ​​can be throughout the scan and may vary based on the scanned part and scanner settings (e.g., 2,000 to 45,000 gray value counts). For example, the minimum effective GV may be determined by a scanning device rotating the object on a rotating table within the scanning device, taking images of the object from multiple angles, and calculating the first percentile of the GVs recorded from all images, thereby avoiding artifacts from noise and / or defective pixels.

[0043] In some exemplary embodiments, the method may further include, in response to determining that the minimum effective GV is less than or equal to the GV threshold, determining that the filtering parameters (e.g., 0 mm, 0.5 mm, 1 mm, 1.5 mm, 2.5 mm, and 6 mm) are not set to a maximum filtering value (e.g., 6 mm), and incrementally increasing the filtering thickness parameters and / or adjusting the camera exposure parameters so that the effective maximum GV is a predetermined value (e.g., 60,000 counts).

[0044] The method may further include determining whether the focus is static or dynamic (as described above in 101) at 106, which may be based on the hardware capabilities of the scanning device, in response to determining that the filtering parameters are set to maximum filtering values ​​or determining that the minimum effective GV is higher than the GV threshold at 105. Based on the determination that the focus is dynamic, the method may further include decreasing the source beam current parameters until focus size≦pixel size / (magnification−1) is satisfied.

[0045] At 107, the method may further include calculating an exposure time minimum soft limit, which may be based at least in part on the minimum duty cycle and / or the overhead per frame. In some exemplary embodiments, the exposure time minimum soft limit may be set to an exposure time that results in a 60% duty cycle. Duty cycle = exposure time / (exposure time + overhead), and therefore exposure time = overhead × duty cycle / (1 - duty cycle). For example, if the minimum duty cycle is 0.6 and the projection overhead is 1 second, then the soft limit for the minimum exposure time is 1 × 0.6 / (1 - 0.6) = 1.5 seconds. Similarly, if the minimum duty cycle is 0.8 and the overhead is 2 seconds, then the minimum exposure time is 2 × 0.8 / (1 - 0.8) = 8 seconds.

[0046] At 108, the method may include calculating an exposure time per frame based on the total number of frames and / or the total elapsed time while acquiring the frames. As an example, the exposure time per frame may be calculated according to: exposure time per frame = total scan time / total number of frames - overhead per frame.

[0047] At 109, the method may include determining whether the exposure time per frame is higher than a maximum exposure time per frame threshold. If the exposure time per frame is higher than the maximum exposure time per frame threshold, the method may include setting the exposure to an upper limit for the scanning device and recalculating the total number of frames based on at least one new exposure time per frame and the total scan time. This may be similar to the calculation described above at 108.

[0048] If the exposure time per frame is less than or equal to the maximum exposure time per frame threshold, the method may include determining whether the exposure time per frame is less than a minimum exposure limit threshold at 110. If the exposure time per frame is less than the minimum exposure limit threshold, the method may include setting the exposure to a minimum exposure soft limit threshold and recalculating the total number of frames again based on the at least one new exposure time per frame and the total scan time.

[0049] The method may include, in response to determining that the exposure time per frame is equal to or greater than the minimum exposure soft limit or recalculating the total number of frames based on at least one new exposure time per frame and total scan time, adjusting the camera gain at 111 to set the effective maximum GV to an effective maximum GV threshold value (e.g., 60,000 counts).

[0050] At 112, the method may include determining whether the camera gain meets the maximum available GV. For example, if the maximum available GV is approximately 60,000 counts, the method may determine whether the gain required to achieve approximately 60,000 counts is less than the minimum gain (0 dB) and / or greater than the maximum gain (60 dB).

[0051] In some exemplary embodiments, if the camera gain does not meet the effective maximum GV, the method may include setting the gain as the closest in-range gain from step 111 above (e.g., if a particular setting requires a gain of 65 dB and the maximum gain is 60 dB, the gain may be set to 60 dB) and / or setting an adjusted exposure time such that the effective maximum GV of the scanning device reaches a predetermined value (e.g., 60,000 counts). Generally, the exposure time may be proportional to the effective maximum GV. The total number of frames may then be recalculated based on the new exposure time per frame value.

[0052] At 113, the method may include determining whether the total number of projections is less than a maximum total number of projections threshold. If the total number of projections is less than the maximum total number of projections threshold, the method may include incrementing the number of frames per projection and resetting the total number of projections to an initial value (e.g., 930), and recalculating the exposure time per frame based on the total number of frames and / or the total elapsed time while acquiring the frames at 108.

[0053] At 114, if the total number of projections is less than the maximum total number of projections threshold, the method may include calculating any of noise-optimal distributions of scan projections, bright flat-field correction (FFC) projections, and dark FFC projections based on the total number of projections. In some example embodiments, reconstruction noise may be minimized when the number of FFC projections = (√ total number of projections) - 1. The number of dark FFC projections may also be set to zero.

[0054] At 115, the method may include the scanning device scanning the scan object according to the determined parameters, which may be held constant throughout the scan.

[0055] 3 shows an example of a CT scanning device 300 that may be configured to perform CT imaging. The CT scanning device 300 may include a scintillator 301 and an X-ray source 302 configured to emit X-rays 303 through a scan object 304 to a front surface 305 of the scintillator 301. The CT scanning device 300 may further include a detector 306 configured to detect at least one fluorescence signal 307 (i.e., visible light) from the scintillator 301. In various exemplary embodiments, the detector 306 may be directed directly at the back surface of the scintillator 301, or the scintillator 301 may be oriented perpendicular to the X-ray source 302.

[0056] In some exemplary embodiments, the scintillator 301 may include a substrate layer that may be made of polycarbonate, polyacrylate, or polyethylene terephthalate (PET), and a barrier film that includes a metal oxide.

[0057] In certain exemplary embodiments, the x-ray source 302 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 triboluminescent x-ray source.

[0058] The scanned object 304 may include any of inorganic materials, organic materials, metals, plastics, composites, carbon, non-carbon, multi-parts, and multi-layered parts.

[0059] In certain exemplary embodiments, the detector 306 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, the detector 306 may be configured to detect the fluorescent signal 307 from the front / back surface of the scintillator 301.

[0060] Any of the devices comprising the CT scanning device 300 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.

[0061] At least one memory may be provided in one or more of the devices that make up the CT scanning device 300. The memory may be fixed or removable. The memory may include computer program instructions or computer code contained 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 on the medium itself (i.e., tangible, not a signal) as opposed to a limitation on data storage persistence (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 on a single integrated circuit as the processor or may be separate from one or more processors. Furthermore, the computer program instructions stored in the memory and processed by the processor may be any suitable form of computer program code, such as a compiled or interpreted computer program written in any suitable programming language.

[0062] The processor and memory may be configured to provide means corresponding to the various blocks in Figures 1-3. Although not shown, the device may also include location determination hardware, such as GPS or microelectromechanical systems (MEMS) hardware, that may be used to determine the device's location. Other sensors, such as a barometer, compass, etc., are also permissible and may be configured to determine location, altitude, speed, orientation, etc.

[0063] 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., FIGS. 1-3). 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.

[0064] In certain exemplary embodiments, a device may include circuitry configured to perform any of the processes or functions illustrated in Figures 1-3. As used herein, the term "circuitry" may refer to one or more or all of the following: (a) a hardware-only circuit implementation (e.g., an implementation using only analog and / or digital circuitry); (b) a combination of hardware circuitry and software, such as (i) and (ii) (where applicable): (i) a combination of analog and / or digital hardware circuitry with software / firmware; and (ii) a hardware processor (including a digital signal processor) with software, software, and any portion of memory that work together to cause a device, such as a mobile phone or server, to perform various functions; and (c) a processor, such as a hardware circuit and / or microprocessor or portion of a microprocessor, that requires software (e.g., firmware) for operation (although software may be absent if it is not necessary for operation). This definition of circuitry applies to all uses of the term in this application, including in any claims. As a further example, as used in this application, the term circuitry also encompasses simply a hardware circuit or processor(s) or portion of a hardware circuit or processor and its(their) accompanying software and / or firmware implementation. The term circuitry also encompasses, for example, and where applicable to the particular declared element, a baseband integrated circuit or processor integrated circuit for a mobile device, or a similar integrated circuit in a server, cellular network device, or other computing or network device.

[0065] In some exemplary embodiments, CT scanning device 300 (and any of the devices within CT scanning device 300) 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 for causing the execution of each operation.

[0066] In various exemplary embodiments, the CT scanning device 300 (and any of the devices within the CT scanning device 300) may be controlled by a memory and a processor to adjust at least one operating parameter based on the material composition of the scanned object, calculate an exposure time parameter per frame based on the total number of frames and the total elapsed time while acquiring the frames, and acquire at least one X-ray frame of the scanned object based on the at least one adjusted operating parameter and the calculated exposure time parameter.

[0067] 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 scanned object, calculating an exposure time parameter per frame based on a total number of frames and a total elapsed time while acquiring the frames, and acquiring at least one X-ray frame of the scanned object based on the at least one adjusted operating parameter and the calculated exposure time parameter.

[0068] Features, structures, or characteristics of example embodiments described throughout this specification may be combined in any suitable manner in one or more example embodiments. For example, the use of the phrases "various embodiments," "particular embodiments," "some embodiments," or other similar phrases throughout this specification refers to a particular feature, structure, or characteristic described in connection with example embodiments that may be included in at least one example embodiment. Thus, appearances of the phrases "in various embodiments," "in particular embodiments," "in some embodiments," or other similar phrases throughout this specification do not necessarily all refer to the same group of example embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments.

[0069] Moreover, if desired, various of the functions or procedures described may be performed in differing orders and / or concurrently with one another. Still further, if desired, one or more of the functions or procedures described may be optional or may be combined. As such, the foregoing description should be considered as an illustration of the principles and teachings of particular exemplary embodiments, and not as a limitation thereof. Those skilled in the art will readily appreciate that the above exemplary embodiments may be implemented with steps in a different order and / or with hardware elements in different configurations than those disclosed. Thus, while certain embodiments have been described in accordance with these 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.

[0070] While the present application is defined by the appended claims, it should be understood that the invention may also (additionally or alternatively) be defined by the following examples.

[0071] Example 1: A method comprising: adjusting, by the computed tomography scanning device, at least one operating parameter based on a material composition of the scanned object; calculating a per-frame exposure time parameter based on a total number of frames and a total elapsed time while acquiring frames with the computed tomography scanning device; acquiring, with the computed tomography scanning device, at least one X-ray frame of the scan object based on the adjusted at least one operating parameter and the calculated exposure time parameter; A method for providing

[0072] Example 2: The method of Example 1, further comprising setting, by the computed tomography scanning device, at least one of the source beam energy parameters to a predetermined maximum value.

[0073] Example 3: The method of any one of the preceding examples, wherein the specified maximum value comprises a maximum beam energy achievable by the computed tomography scanning device.

[0074] Example 4: The method of any one of the preceding Examples, further comprising setting, by the computed tomography scanning device, a camera gain parameter to a high value based on a predetermined threshold.

[0075] Example 5: The method of any one of the preceding examples, wherein the camera gain parameter is associated with an amplification factor.

[0076] Example 6: The method of any one of the preceding examples, further comprising the step of positioning and magnifying, by the computed tomography scanning device, an image of the scanned object according to an object detection algorithm.

[0077] Example 7: The method of any one of the preceding Examples, further comprising determining, by the computed tomography scanning device, whether the scanned object is one material or multiple materials.

[0078] Example 8: The method of any one of the preceding examples, further comprising determining, by the computed tomography scanning device, whether a minimum valid gray value associated with the image of the scanned object is higher than a gray value threshold.

[0079] Example 9: The method of any one of the above examples, further comprising a step of determining, by the computed tomography scanning device, whether the focus is static or dynamic in response to determining that the filtering parameters are set to the maximum filtering value or that the minimum valid gray value is higher than the gray value threshold.

[0080] Example 10: The method of any one of the preceding examples, further comprising the step of reducing a source beam current parameter by the computed tomography scanning device until focal spot size≦pixel size / (magnification−1) is satisfied.

[0081] Example 11: The method of any one of the preceding examples, further comprising calculating, by the computed tomography scanning device, source beam current parameters until focal spot size≦pixel size / (magnification−1) is satisfied.

[0082] Example 12: The method of any one of the preceding examples, further comprising calculating an exposure time per frame based on at least one of a total number of frames and a total elapsed time while acquiring the frames by the computed tomography scanning device.

[0083] Example 13: The method of any one of the preceding examples, further comprising determining, by the computed tomography scanning device, whether the exposure time per frame is greater than a maximum exposure time per frame threshold.

[0084] Example 14: The method of any one of the preceding examples, further comprising a step of determining, by the computed tomography scanning device, whether the exposure time per frame is less than a minimum exposure limit threshold in response to determining that the exposure time per frame is less than or equal to a maximum exposure time threshold per frame.

[0085] Example 15: The method of any one of the preceding examples, further comprising a step of determining, by the computed tomography scanning device, whether the exposure time per frame is less than a minimum exposure limit threshold in response to determining that the exposure time per frame is less than or equal to a maximum exposure time threshold per frame.

[0086] Example 16: The method of any one of the preceding examples, further comprising the step of adjusting a camera gain by the computed tomography scanning device to set the effective maximum gray value to an effective maximum gray value threshold.

[0087] Example 17: The method of any one of the preceding examples, further comprising determining, by the computed tomography scanning device, whether a camera gain satisfies a valid maximum gray value.

[0088] Example 18: The method of any one of the preceding examples, further comprising determining, by the computed tomography scanning device, whether the total number of projections is less than a maximum total number of projections threshold.

[0089] Example 19: The method of Example 18, further comprising a step of calculating, by the computed tomography scanning device, any of a noise-optimal distribution of scan projections, bright flat-field corrected projections, and dark flat-field corrected projections based on the total number of projections in response to determining that the total number of projections is less than the maximum total number of projections threshold.

[0090] Example 20: The method of any one of the preceding examples, further comprising scanning a scan object according to at least one determined parameter by the computed tomography scanning device.

[0091] Operations and processes similar to those described in Examples 1-20 can be implemented in an apparatus having at least one processor and at least one memory containing computer program code, the at least one memory and the computer program code being configured by the at least one processor to cause the apparatus to at least perform the operations.

[0092] Also possible is a non-transitory computer-readable medium having program instructions stored thereon for performing the operations recited in any one of Examples 1-20. Also possible is an apparatus having circuitry configured to perform the operations recited in any one of Examples 1-20. Also possible is a computer program product encoded with instructions for performing the operations recited in any one of Examples 1-20.

[0093] Example 21: A method comprising: adjusting, by the computed tomography scanning device, at least one operating parameter comprising a gray value threshold based on a material composition of the scanned object; calculating, by the computed tomography scanning device, an exposure time, optionally comprising calculating an exposure time per frame based on at least one of a total number of frames and a total elapsed time while acquiring the frames; acquiring, with the computed tomography scanning device, at least one X-ray frame of the scan object based on the adjusted at least one operating parameter and the calculated exposure time; A method for providing

[0094] Example 22: The method of Example 21, further comprising the step of setting, by the computed tomography scanning device, at least one of the source beam energy parameters to a predetermined maximum value.

[0095] Example 23: The method of example 21 or 22, wherein the specified maximum value comprises a maximum beam energy achievable by the computed tomography scanning device.

[0096] Example 24: The method of Example 21, 22 or 23, further comprising the step of setting, by the computed tomography scanning device, a camera gain parameter to a high value based on a predetermined threshold.

[0097] Example 25: The method of example 21, 22, 23 or 24, wherein the camera gain parameter is associated with an amplification factor.

[0098] Example 26: The method of Example 21, 22, 23, 24 or 25, further comprising the step of positioning and magnifying, by the computed tomography scanning device, an image of the scanned object according to an object detection algorithm.

[0099] Example 27: The method of Example 21, 22, 23, 24, 25 or 26, further comprising a step of identifying the material composition of the scanned object, comprising a step of determining whether the scanned object is one material or multiple materials by the computed tomography scanning device.

[0100] Example 28: The method of Examples 21, 22, 23, 24, 25, 26 or 27, further comprising a step of determining, by the computed tomography scanning device, whether a minimum valid gray value associated with the image of the scanned object is higher than the gray value threshold.

[0101] Example 29: The method of Examples 21, 22, 23, 24, 25, 26, 27 or 28, further comprising a step of determining, by the computed tomography scanning device, whether the focus is static or dynamic in response to determining that the filtering parameters are set to the maximum filtering value or that the minimum valid gray value is higher than the gray value threshold.

[0102] Example 30: The method of Examples 21, 22, 23, 24, 25, 26, 27, 28 or 29, further comprising a step of calculating source beam current parameters by the computed tomography scanning device until focal spot size≦pixel size / (magnification−1) is satisfied.

[0103] Example 31: The method of Examples 21, 22, 23, 24, 25, 26, 27, 28, 29 or 30, further comprising determining, by the computed tomography scanning device, whether the exposure time per frame is greater than a maximum exposure time per frame threshold.

[0104] Example 32: The method of Example 31, further comprising a step of determining, by the computed tomography scanning device, whether the exposure time per frame is less than a minimum exposure limit threshold in response to determining that the exposure time per frame is less than or equal to the maximum exposure time per frame threshold.

[0105] Example 33: In response to determining that the per-frame exposure time is higher than the per-frame maximum exposure time threshold, setting, by the computed tomography scanning device, the exposure time per frame to an upper limit of the computed tomography scanning device; calculating the total number of frames based on at least the exposure time per frame and a total scan time; The method of Example 31, further comprising:

[0106] Example 34: The method of Examples 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32 or 33, further comprising determining, by the computed tomography scanning device, whether the total number of projections is less than a maximum total number of projections threshold.

[0107] Example 35: The method of Examples 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33 or 34, further comprising a step of calculating, by the computed tomography scanning device, any of a noise-optimized distribution of scan projections, bright flat-field corrected projections and dark flat-field corrected projections based on the total number of projections in response to determining that the total number of projections is less than the maximum total number of projections threshold.

[0108] Similar operations and processes as described in Examples 21-35 can be implemented 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 implemented 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 21-35.

[0109] Example 36: A method comprising: setting at least one scan parameter comprising a source beam energy parameter of a computed tomography scanning device to a predetermined maximum value; scanning a scan object according to the at least one scan parameter; A method for providing

[0110] Example 37: The method of Example 36, wherein the specified maximum value comprises a maximum beam energy achievable by the computed tomography scanning device.

[0111] Example 38: The method of Example 36 or 37, wherein the at least one scan parameter comprises a source beam current parameter, and the specified maximum value comprises a specified maximum source beam current achievable by the computed tomography scanning device.

[0112] Example 39: determining that the filtering parameters are set to a maximum filtering value or that the minimum valid grey value is greater than a grey value threshold; determining that the focus of the computed tomography scanning device is dynamic in response to determining that the filtering parameter is set to the maximum filtering value or that the minimum valid gray value is higher than the gray value threshold; In response to determining that the focal spot of the computed tomography scanning device is dynamic, reducing the source beam current parameter until focal spot size≦pixel size / (magnification−1) is satisfied; The method of Example 36, 37 or 38, further comprising:

[0113] Example 40: 40. The method of example 36, 37, 38 or 39, comprising adjusting a gray value threshold based on a material composition of the scanned object.

[0114] Operations and processes similar to those described in Examples 36 to 40 can be implemented in a system including at least one processor and a memory communicatively connected to the at least one processor, the memory storing instructions that, when executed, cause the at least one processor to perform the operations. Also implemented 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 36 to 40. In some embodiments, the features of Examples 36 to 40 can be combined with the features of Examples 1 to 35 above.

[0115] Example 41: A method comprising: obtaining a total number of projections; calculating a noise optimal distribution of the scan projections and the flat-field corrected projections based on the total number of projections, the noise optimal distribution being calculated for noise reduction; acquiring at least one X-ray frame of the scanned object based on the distribution of the scan projections and the flat-field corrected projections using a computed tomography scanning device; A method for providing

[0116] Example 42: The method of Example 41, wherein the flat-field corrected projection comprises at least one of a bright flat-field corrected projection and a dark flat-field corrected projection.

[0117] Example 43: The method of Example 41 or 42, wherein the step of calculating the noise optimal distribution comprises a step of determining the number of scan projections, the number of bright flat-field correction projections, and the number of dark flat-field correction projections to minimize reconstruction noise.

[0118] Example 44: determining whether the total number of projections is less than a maximum total number of projections threshold; calculating the noise optimal distribution in response to determining that the total number of projections is less than the maximum total number of projections threshold; 44. The method of example 41, 42 or 43, comprising:

[0119] Example 45: obtaining a second total number of projections; adjusting a number of frames per projection in response to determining that the second total number of projections is greater than or equal to the maximum total number of projections threshold; resetting the second total number of projections to an initial value; Calculating an exposure time per frame; 45. The method of example 44, comprising:

[0120] Similar operations and processes as described in Examples 41 to 45 can be implemented 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 implemented 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 41 to 45. In some embodiments, the features of Examples 41 to 45 may be combined with the features of Examples 1 to 40 described above.

[0121] Part of the 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 PET: Polyethylene terephthalate RGGB: Red-Green-Green-Blue

Claims

1. 1. A method comprising: adjusting, by the computed tomography scanning device, at least one operating parameter comprising a gray value threshold based on a material composition of the scanned object; calculating, by the computed tomography scanning device, an exposure time, optionally comprising calculating an exposure time per frame based on at least one of a total number of frames and a total elapsed time while acquiring the frames; acquiring, with the computed tomography scanning device, at least one X-ray frame of the scan object based on the adjusted at least one operating parameter and the calculated exposure time; A method for providing

2. The method of claim 1 , further comprising setting at least one source beam energy parameter to a predetermined maximum value by the computed tomography scanning device.

3. The method of claim 2 , wherein the specified maximum value comprises a maximum beam energy achievable by the computed tomography scanning device.

4. The method of claim 1 , further comprising setting, by the computed tomography scanning device, a camera gain parameter to a high value based on a predetermined threshold.

5. The method of claim 4 , wherein the camera gain parameter is associated with an amplification factor.

6. The method of claim 1 , further comprising the step of positioning and magnifying, by the computed tomography scanning device, an image of the scanned object according to an object detection algorithm.

7. 7. The method of claim 1, further comprising identifying the material composition of the scanned object by the computed tomography scanning device, the method comprising determining whether the scanned object is one-material or multi-material.

8. 7. The method of claim 1, further comprising determining, by the computed tomography scanning device, whether a minimum valid grey value associated with the image of the scanned object is higher than the grey value threshold.

9. 7. The method of claim 1, further comprising determining by the computed tomography scanning device whether the focal point is static or dynamic in response to determining that a filtering parameter is set to a maximum filtering value or that a minimum valid gray value is higher than the gray value threshold.

10. 7. The method of claim 1, further comprising the step of calculating, by the computed tomography scanning device, source beam current parameters until focal spot size≦pixel size / (magnification−1).

11. The method of claim 1 , further comprising determining, by the computed tomography scanning device, whether the exposure time per frame is greater than a maximum exposure time per frame threshold.

12. 12. The method of claim 11, further comprising, in response to determining that the exposure time per frame is less than or equal to the maximum exposure time per frame threshold, determining, by the computed tomography scanning device, whether the exposure time per frame is less than a minimum exposure limit threshold.

13. In response to determining that the per-frame exposure time is greater than the per-frame maximum exposure time threshold, setting, by the computed tomography scanning device, the exposure time per frame to an upper limit of the computed tomography scanning device; calculating the total number of frames based on at least the exposure time per frame and a total scan time; The method of claim 11 further comprising:

14. The method of claim 1 , further comprising determining, by the computed tomography scanning device, whether the total number of projections is less than a maximum total number of projections threshold.

15. 15. The method of claim 14, further comprising, in response to determining that the total number of projections is less than the maximum total number of projections threshold, calculating, by the computed tomography scanning device, one of a noise optimal distribution of scan projections, bright flat-field corrected projections, and dark flat-field corrected projections based on the total number of projections.

16. 1. A system comprising: a data processing device including at least one processor; A non-transitory computer-readable medium, comprising: setting at least one scan parameter comprising a source beam energy parameter of a computed tomography scanning device to a predetermined maximum value; scanning a scan object according to the at least one scan parameter; a non-transitory computer-readable medium encoding instructions configured to cause the data processing apparatus to perform operations comprising: A system comprising:

17. The system of claim 16 , wherein the specified maximum value comprises a maximum beam energy achievable by the computed tomography scanning device.

18. 18. The system of claim 16 or 17, wherein the at least one scan parameter comprises a source beam current parameter, and the predetermined maximum value comprises a predetermined maximum source beam current achievable by the computed tomography scanning device.

19. The operation is determining that the filtering parameters are set to a maximum filtering value or that the minimum valid grey value is greater than a grey value threshold; determining that a focus of the computed tomography scanning device is dynamic in response to determining that the filtering parameter is set to the maximum filtering value or that the minimum valid gray value is higher than the gray value threshold; In response to determining that the focal spot of the computed tomography scanning device is dynamic, reducing the source beam current parameter until focal spot size≦pixel size / (magnification−1) is satisfied; 20. The system of claim 18, further comprising:

20. The operation is 18. The system of claim 16 or 17, comprising adjusting a grey value threshold based on the material composition of the scanned object.

21. A non-transitory computer-readable medium encoding instructions operable to cause a data processing apparatus to perform operations, the operations comprising: obtaining a total number of projections; calculating a noise optimal distribution of the scan projections and the flat-field corrected projections based on the total number of projections, the noise optimal distribution being calculated for noise reduction; acquiring at least one x-ray frame of a scanned object based on the distribution of the scan projections and the flat-field corrected projections using a computed tomography scanning device; 1. A non-transitory computer-readable medium comprising:

22. 22. The non-transitory computer-readable medium of claim 21, wherein the flat-field corrected projection comprises at least one of a bright flat-field corrected projection and a dark flat-field corrected projection.

23. 23. The non-transitory computer-readable medium of claim 21 or 22, wherein calculating the noise optimal distribution comprises determining a number of scan projections, a number of bright flat-field correction projections, and a number of dark flat-field correction projections for minimizing reconstruction noise.

24. The operation is determining whether the total number of projections is less than a maximum total number of projections threshold; calculating the noise optimal distribution in response to determining that the total number of projections is less than the maximum total number of projections threshold; 23. The non-transitory computer-readable medium of claim 21 or 22, comprising:

25. The operation is obtaining a second total number of projections; adjusting a number of frames per projection in response to determining that the second total number of projections is greater than or equal to a maximum total number of projections threshold; resetting the second total number of projections to an initial value; Calculating an exposure time per frame; 25. The non-transitory computer-readable medium of claim 24, comprising:

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