Multi-power x-ray imaging

Abstract

The invention relates to a method for pluripotent X-ray imaging of an examination object, comprising:-acquiring a first X-ray image dataset having a first spatial resolution, the first X-ray image dataset being acquired in a first X-ray spectrum,-acquiring a second X-ray image dataset having a second spatial resolution, the second X-ray image dataset being acquired in a second X-ray spectrum, the first X-ray image dataset is acquired with a first X-ray spectrum, the second X-ray image dataset is acquired with a second X-ray spectrum, the first X-ray image dataset and the second X-ray image dataset present an at least partially common examination region of the examination object, the first X-ray spectrum and the second X-ray spectrum differ from each other, and the second spatial resolution is smaller than the first spatial resolution. -adjusting the spatial modulation of the second X-ray image dataset on the basis of the geometric and / or anatomical features of the examination object presented in the first X-ray image dataset and the second X-ray image dataset,-providing a result dataset on the basis of the adjusted second X-ray image dataset. The invention also relates to a medical X-ray device and a computer program product.

Description

[0001] This invention relates to a method for performing multi-energy X-ray imaging on an object to be examined, a medical X-ray device, and a computer program product.

[0002] To differentiate materials with different absorption characteristics, such as iodine and / or calcium, multi-energy X-ray images of the subject can be acquired. In multi-energy X-ray imaging, such as multi-energy computed tomography (CT) and / or multi-energy fluorescence fluoroscopy or multi-energy X-ray imaging, multiple X-ray image datasets can be acquired under different X-ray spectra, especially those with different energy distributions. In dual-energy X-ray imaging, a special case of multi-energy X-ray imaging, two X-ray image datasets with different X-ray spectra, especially with different maximum energies, can be acquired. For example, in dual-energy X-ray imaging, low-energy and high-energy spectra can be used, generated by applying different tube voltages to the X-ray source. Especially in cases of time-staggered acquisition, different X-ray spectra with different maximum energies can be generated using a single X-ray source. Alternatively, two dedicated X-ray sources can be used to simultaneously acquire X-ray image datasets with different X-ray spectra. For example, iodine staining and / or hemorrhage can be deduced from the combination of X-ray image datasets based on material decomposition techniques.

[0003] Typically, one of the two X-ray spectra is power-limited due to limitations of the X-ray source and / or filtering and / or high absorption by the object being examined. Disadvantageously, this can lead to insufficient signal strength at the X-ray detector. For example, voltage modulation of the X-ray tube can be used when image quality is below predetermined standards. However, this can reduce the uniformity of the detected X-ray image dataset. Furthermore, the spectral separability between the low-energy and high-energy spectra may deteriorate. Both of these effects can lead to reduced sensitivity for material decomposition.

[0004] Therefore, the technical problem to be solved by the present invention is to achieve a multi-energy X-ray imaging method with high X-ray dose efficiency for the object being examined.

[0005] The technical problem described herein is solved by the technical solution of the independent claim. Advantageous embodiments with appropriate modifications are the technical solutions of the dependent claims. In this patent application, nouns and pronouns referring to persons generally do not specify a particular gender.

[0006] In a first aspect, the present invention relates particularly to a computer-implemented method for multi-energy X-ray imaging of an object under examination. In a first step, a first X-ray image dataset with a first spatial resolution is acquired. Furthermore, the first X-ray image dataset is acquired using first X-ray light. In another step, a second X-ray image dataset with a second spatial resolution is acquired. The second X-ray image dataset is acquired using a second X-ray spectrum. The first and second X-ray image datasets present at least a partially common examination area of ​​the object under examination. The first and second X-ray spectra are different from each other. Furthermore, the second spatial resolution is smaller than the first spatial resolution. In another step, the spatial modulation of the second X-ray image dataset is adjusted based on the geometric and / or anatomical features of the object under examination presented in the first and second X-ray image datasets. Thereafter, the adjusted second X-ray image dataset is provided.

[0007] The steps of the methods suggested above can be performed at least partially simultaneously or sequentially.

[0008] The subjects of examination may be, for example, human female patients and / or animal female patients and / or human male patients and / or animal male patients and / or examination phantoms.

[0009] The acquisition of the first and second X-ray image datasets may respectively include receiving and / or acquiring the corresponding X-ray image datasets. Receiving the first and / or second X-ray image datasets may particularly include acquiring and / or reading from computer-readable data storage and / or receiving from a data storage unit, such as a database. Furthermore, the first and / or second X-ray image datasets may be provided by a medical imaging device providing unit. Alternatively or additionally, the first and second X-ray image datasets may be acquired using a common medical X-ray device or different medical X-ray devices.

[0010] Advantageously, the first X-ray image dataset may have a first image with two-dimensional (2D) and / or three-dimensional (3D) spatial resolution of the area to be examined. The 2D spatial resolution first image can present the area to be examined as a 2D projection. The first image of the area to be examined may in particular have a plurality of image points, in particular pixels and / or voxels, representing the area to be examined, having image values, in particular attenuation values ​​and / or intensity values. The first X-ray image dataset may also be time-resolved. Here, the first X-ray image dataset may have a first spatial resolution. The first X-ray image dataset may in particular present the area to be examined at a first spatial resolution.

[0011] Advantageously, the second X-ray image dataset can have a second image with two-dimensional (2D) and / or three-dimensional (3D) spatial resolution of the area to be examined. The 2D spatially resolved second image can present the area to be examined as a 2D projection. The second image of the area to be examined can, in particular, have multiple image points, in particular pixels and / or voxels, representing the area to be examined, with image values, in particular attenuation values ​​and / or intensity values. The second X-ray image dataset can also be time-resolved. Here, the second X-ray image dataset can have a second spatial resolution. The second X-ray image dataset can, in particular, present the area to be examined at a second spatial resolution.

[0012] Advantageously, the second spatial resolution is smaller than the first spatial resolution. In particular, the image points of the second X-ray image dataset, which presents at least a partially common examination area, have larger side lengths, and especially larger areas and / or volumes, compared to the image points of the first X-ray image dataset.

[0013] The first and second X-ray spectra can include low-energy and high-energy spectra. The first X-ray spectrum particularly can include low-energy spectra, and the second X-ray spectrum can include high-energy spectra. The first and second X-ray spectra can be generated by applying different tube voltages to the X-ray source. Especially in the case of time-staggered acquisition, different X-ray spectra with different maximum energies can be generated using a single X-ray source.

[0014] For example, a tube voltage of 70 kV can be used to generate low-energy spectra, and a tube voltage of 125 kV can be used to generate high-energy spectra. Advantageously, filters, especially those containing tin and / or molybdenum, can be introduced in the beam path between the X-ray source and the X-ray detector to harden the high-energy spectra and improve spectral separability.

[0015] Advantageously, the first and second X-ray image datasets can present at least a portion, and in particular a completely common, examination area of ​​the object under examination. Here, the examination area can include, in particular, a three-dimensional spatial region of the object under examination, especially its volume. Advantageously, the examination area can contain anatomical and / or medical objects of interest, such as tissues and / or organs of the object under examination, and / or diagnostic and / or surgical instruments and / or implants.

[0016] Advantageously, the first and second X-ray image datasets can present the examined area with substantially consistent imaging geometry, such as imaging orientation and / or imaging range.

[0017] Advantageously, the spatial modulation of the second X-ray image dataset is adjusted based on the geometric and / or anatomical features of the object under examination presented in the first and second X-ray image datasets. For example, the width and / or shape of edges in the first X-ray image dataset can be determined. Furthermore, the width and / or shape of corresponding edges in the second X-ray image dataset can be adjusted, in particular, to make them consistent, based on the width and / or shape of the edges in the first X-ray image dataset.

[0018] For example, high-frequency components can be extracted from a first X-ray image dataset and used in a second X-ray image dataset to enhance the high frequencies. For example, an edge image can be generated from the first X-ray image dataset, particularly using gradient and / or Sobel filters and / or Canny edge detection, and then weighted using it on the second X-ray image dataset. Alternatively or additionally, the first X-ray image dataset, especially the edge image, can be used as a common filter, such as a guide filter and / or a reference image, especially a guide image, in a joint bilateral filter.

[0019] The common geometric features of the examined objects may include, for example, edges and / or contours and / or marked structures and / or contrast transitions presented in the first and second X-ray image datasets. The common anatomical features may include, for example, tissue boundaries and / or structures and / or anatomical landmarks, particularly openings, and / or implants presented in the first and second X-ray image datasets.

[0020] Advantageously, the result dataset may include an adjusted second result dataset and / or processing results based on the adjusted second X-ray image dataset.

[0021] The provided result dataset may include storage on a computer-readable storage medium and / or display on a display unit and / or transfer to the providing unit. In particular, graphical images of the result dataset may be displayed using the display unit.

[0022] Advantageously, this avoids modulation of the tube voltage. Furthermore, the X-ray dose can be advantageously minimized when acquiring the second X-ray image dataset. Modulation of the second X-ray image dataset also allows for higher spatial resolution.

[0023] In another advantageous embodiment of the proposed method, acquiring the second X-ray image dataset may include binning the image points.

[0024] Advantageously, acquiring the second X-ray image dataset may include acquiring second raw X-ray image data. The second raw X-ray image data, in particular, may possess all the features and attributes described for the second X-ray image dataset, except for the second spatial resolution. Here, the second raw X-ray image data may have a higher spatial resolution than the second spatial resolution, especially a first spatial resolution. Advantageously, the second X-ray image dataset (binning) can be provided by merging image points from the second raw X-ray image data. Here, each image point in the second X-ray image dataset may be formed from multiple adjacent image points of the second raw X-ray image data, for example, by summing the image values ​​of the image points to be merged and / or applying a smoothing algorithm and / or an averaging algorithm in the image space.

[0025] The spatial resolution of the raw X-ray image data can include digital resolution, for example, through oversampling and / or, in particular, actual imaging resolution, especially measured by modulation transfer function (MTF). Specifically, if the second raw X-ray image data is acquired at a larger focal point than the first X-ray image dataset, the second raw X-ray image data may have a higher spatial resolution, especially digital resolution, than the second spatial resolution.

[0026] In another advantageous embodiment of the proposed method, the second X-ray image dataset can be acquired with a larger focal point than the first X-ray image dataset.

[0027] Advantageously, the first and second X-ray image datasets can be acquired using a medical X-ray device. The medical X-ray device may include an X-ray source and an X-ray detector. Here, the X-ray source may be designed to emit X-rays to visualize the object being examined, particularly the area being examined. Furthermore, the X-ray detector may be designed to detect X-rays, especially after they interact with the area being examined. The first and second X-ray image datasets can be acquired, in particular, using a cone-beam computed tomography (CBCT) device.

[0028] To emit X-rays, the X-ray source may include a cathode and an anode, wherein electrons are released from the cathode and accelerated under high voltage to a region of the anode. The high voltage between the cathode and anode may also be called the tube voltage of the X-ray tube. The region where electrons strike the anode may be called the focal spot.

[0029] Advantageously, the second X-ray image dataset can be acquired with a larger focal spot, particularly a larger spatial focal spot size, and / or a larger focal spot diameter than the first X-ray image dataset. In this way, a higher tube voltage can be advantageously used to acquire the second X-ray image dataset compared to acquiring the first X-ray image dataset. Advantageously, this allows for the use of a shorter illumination time to acquire the second X-ray image dataset.

[0030] In another advantageous embodiment of the proposed method, the first X-ray image dataset and the second X-ray image dataset can be registered with each other.

[0031] Registration of a first X-ray image dataset and a second X-ray image dataset may advantageously include applying transformation rules to the first and / or second X-ray image datasets. Advantageously, the transformation rules may include instructions for translation and / or rotation and / or scaling and / or deformation of the first and / or second X-ray image datasets. Advantageously, the registration of the first and second X-ray image datasets may be based on common geometric and / or anatomical features of the examination area presented in the first and second X-ray image datasets. Registration of the first and second X-ray image datasets may advantageously include minimizing the deviation between the imaging of common geometric and / or anatomical features in the first and second X-ray image datasets.

[0032] Advantageously, this can reduce artifacts, such as motion artifacts, especially when adjusting the spatial modulation of the second X-ray image dataset and / or providing a result dataset based on the first and second X-ray image datasets.

[0033] In another advantageous embodiment of the proposed method, acquiring the first X-ray image dataset may include acquiring multiple first X-ray projection images. Here, the first X-ray image dataset can be reconstructed from the multiple first X-ray projection images. Furthermore, acquiring the second X-ray image dataset may include acquiring multiple second X-ray projection images. Here, the second X-ray image dataset can be reconstructed from the multiple second X-ray projection images.

[0034] The first and second X-ray projection images can be acquired from different projection directions along a 3D trajectory using one or more different medical X-ray devices, especially medical C-arm X-ray devices. The projection directions used to acquire the first and second X-ray projection images can, in particular, be paired and aligned.

[0035] The projection direction, and in particular the irradiation angle, can describe the path of the X-ray device, especially the central ray, between the X-ray source and the X-ray detector, particularly the center point of the detector, at the moment of acquiring each X-ray projection image. The projection direction can also describe the irradiation angle of the X-ray device relative to the object being examined and / or the isocenter, particularly the center of rotation, where the isocenter refers to the defined arrangement of the X-ray source and the X-ray detector. Here, the isocenter can describe a spatial point around which the defined arrangement of the X-ray source and the X-ray detector is movable, particularly rotatable, especially during the acquisition of the first and / or second X-ray projection images. Advantageously, different projection directions can pass through a particularly common isocenter. The 3D trajectory can describe a reference point, such as the spatial path of the focal point within the defined arrangement of the X-ray source and the X-ray detector. Advantageously, multiple first and second X-ray projection images can respectively present the object being examined, particularly the area being examined, at 2D spatial resolution.

[0036] Advantageously, a first X-ray image dataset can be reconstructed from multiple first X-ray projection images, for example, through particularly filtered backprojection. Advantageously, a second X-ray image dataset can be reconstructed from multiple second X-ray projection images, for example, through particularly filtered backprojection. Here, the first and second X-ray image datasets can each have 3D spatially resolved imaging of the examination area.

[0037] The proposed implementation method enables improved 3D multi-energy X-ray imaging of the object being examined.

[0038] In another advantageous embodiment of the proposed method, adjusting the spatial modulation of the second X-ray image dataset may include transferring the first spatial resolution to the second X-ray image dataset.

[0039] The following describes an advantageous implementation of transferring a first spatial resolution to a second X-ray image dataset, but the method of the invention should not be limited to a specific adjustment of spatial modulation.

[0040] The first and second X-ray image datasets can, for example, each present the tissue of the examined object. Here, at least one blood vessel, at least partially filled with contrast agent, can pass through the tissue. The blood vessel may, for example, include arteries and / or veins. The blood vessel may have a relatively small diameter. The contrast agent, such as iodine, may have a different spectral dependence than the surrounding soft tissue and / or blood. Advantageously, the distribution of the contrast agent is substantially confined within the blood vessel. For example, the spectrum of X-ray absorption caused by soft tissue, especially the relative variation, can be obtained by lookup table and / or calibration measurements. Due to the higher spatial resolution, the resolution of the blood vessel in the first X-ray image dataset can be more precise, and especially more detailed, than in the second X-ray image dataset.

[0041] For example, a first image point, particularly a pixel or voxel, in a first X-ray image dataset may represent a portion of a blood vessel, which may contain an unknown proportion of soft tissue and / or a mixture of blood and contrast agent. A second image point in the first X-ray image dataset may represent only soft tissue. With image segmentation, image points in the first X-ray image dataset that are at least partially attributable to blood vessels, such as the first image point, or that are only attributable to soft tissue, such as the second image point, can be identified.

[0042] Attenuation value A of the first image point 1,1 It can have the following components:

[0043] A 1,1 = c·A Kontrast,1 + (1 - c)·A Blut,1

[0044] Where c represents the concentration of contrast agent in the blood vessel, and A Kontrast,1 A represents the attenuation value of the contrast agent in the first X-ray spectrum. Blut,1 This indicates the attenuation value of blood in the first X-ray spectrum.

[0045] Attenuation value A of the second image point 2,1 It can have the following components:

[0046] A 2,1 = A WG,1

[0047] Among them, A WG,1 This represents the attenuation value of soft tissue in the first X-ray spectrum.

[0048] The second X-ray image dataset can have a lower spatial resolution than the first X-ray image dataset. Here, the image points, particularly pixels or voxels, of the second X-ray image dataset can fully represent the examination area presented by the first and second image points of the first X-ray image dataset. Therefore, this image point of the second X-ray image dataset can contain signal components from blood vessels (especially blood and contrast agents) and soft tissue. The vascular component A in the image points of the second X-ray image dataset... 1,2 and soft tissue component A 2,2 The respective proportions can be determined as follows:

[0049] A 1,2 = c·A Kontrast,2 + (1 - c)·A Blut,2

[0050] A 2,2 = A WG,2

[0051] in, A represents the attenuation value of an image point in the second X-ray image dataset. Kontrast,2 A represents the attenuation value of the contrast agent in the second X-ray spectrum. Blut,2 This represents the attenuation value of blood in the second X-ray spectrum, and A WG,2 This represents the attenuation value of soft tissue in the second X-ray spectrum. Used to determine A... 0,2 The arithmetic mean calculation method is applicable to low contrast agent concentrations c or attenuation values ​​A. Kontrast A Blut and A WG For cases where the differences are small, this simplified notation is used here. Otherwise, the correct average calculation should be based on the linear detector count rate or the corresponding exponential and logarithmic functions according to the Beer-Lambert law.

[0052] For example, A WG,2 From the known changes in the X-ray absorption spectrum of soft tissue, we can obtain information from A WG,1 = A 2,1 It was deduced. A Kontrast,1 A Kontrast,2 A Blut,1 and A Blut,2 This can be obtained as a known value from previous calibration measurements and / or literature values. Therefore, we can obtain:

[0053] A 1,2 = 2·A 0,2 - A 2,2 = 2·A 0,2 - A WG,2 = c·A Kontrast,2 + (1 - c)·A Blut,2

[0054]

[0055] By utilizing known correlations and known, in particular, spectral absorption characteristics, the unknown contrast agent concentration c can be determined. Furthermore, the modulation of the second X-ray image dataset can be adjusted to consistently achieve higher spatial resolution.

[0056] In another advantageous embodiment of the proposed method, the second X-ray image dataset can present a spatial intensity variation curve. Here, the spatial modulation of the second X-ray image dataset can be adjusted so that the amplitude and / or integral of the spatial intensity variation curve are preserved.

[0057] For example, adjusting the spatial modulation of a second X-ray image dataset can include adjusting the rise of the spatial intensity variation curve, for example, at the edges, while preserving the amplitude and / or integral of the spatial intensity variation curve. This adjustment can be made so that when the spatial modulation or spatial resolution is reduced again, particularly through simulated merging and / or simulated averaging and / or simulated downsampling, the second X-ray image dataset, which is “overestimated” in terms of resolution, can be converted back to the original, lower-resolution second X-ray image dataset as unchanged as possible.

[0058] In another advantageous embodiment of the proposed method, the first and second X-ray image datasets can present a contrast agent disposed within the examination area. Here, the geometric and / or anatomical features of the examined object can include respective imaging of the contrast agent.

[0059] Advantageously, the first and second X-ray image datasets can present contrast agents, particularly those that are X-ray opaque, in the examined object, especially in the examined area, such as flow and / or diffusion of the contrast agent and / or contrast agent clumps. Alternatively or additionally, the first and second X-ray image datasets can present static and / or quasi-static contrast agent deposits in the examined object, especially in the examined area. Here, the contrast agent may be located in the organ of the examined object, especially a hollow organ, such as a segment of blood vessel and / or tissue.

[0060] Advantageously, common geometric and / or anatomical features of the examined objects may include respective imaging of the contrast agent in the first X-ray image dataset and the second X-ray image dataset.

[0061] The proposed implementation method enables particularly reliable adjustment of the spatial modulation of the second X-ray image dataset.

[0062] In another advantageous embodiment of the proposed method, the first X-ray image dataset and the second X-ray image dataset can simultaneously present the at least partially common examination area.

[0063] Advantageously, the first and second X-ray image datasets can be acquired substantially simultaneously. In particular, the first and second X-ray image datasets can contain substantially the same acquisition time points. If acquiring the first X-ray image dataset includes acquiring multiple first X-ray projection images, and acquiring the second X-ray image dataset includes acquiring multiple second X-ray projection images, then each pair of first and second X-ray projection images can simultaneously present the examination area in pairs, particularly from a consistent projection direction.

[0064] The proposed implementation enables improved multi-energy X-ray imaging of rapidly changing processes of the object being examined, such as motion.

[0065] In another advantageous embodiment of the proposed method, the resulting dataset may also be provided based on a first X-ray image dataset.

[0066] Advantageously, the resulting dataset can be provided based on a first X-ray image dataset and a second X-ray image dataset. Providing the resulting dataset may include performing multi-energy calculations, such as filtering and / or segmentation and / or contrast, based on the first and second X-ray image datasets.

[0067] The proposed implementation method enables precise material decomposition, particularly concentration determination. For example, a results dataset containing information on the material composition and / or concentration in the examined area, especially calcium and / or iodine concentrations, can be provided.

[0068] In another advantageous embodiment of the proposed method, the first X-ray image dataset and the second X-ray image dataset can be obtained using a medical X-ray device.

[0069] The medical X-ray device may include an X-ray source and an X-ray detector. Here, the X-ray source may be designed to emit X-rays to visualize the object being examined, particularly the area being examined. Furthermore, the X-ray detector may be designed to detect X-rays, especially after they interact with the area being examined. The first and second X-ray image datasets can be acquired, in particular, by a multi-energy cone-beam computed tomography (CBCT) device, such as a dual-energy CBCT.

[0070] Here, the first X-ray image dataset and the second X-ray image dataset can be acquired by X-ray equipment in a sequential or staggered manner.

[0071] In a second aspect, the present invention relates to a medical X-ray apparatus designed to perform the proposed method for multi-energy X-ray imaging of an examination subject.

[0072] The advantages of this X-ray device essentially correspond to the advantages of the proposed multi-energy X-ray imaging method for examining the object. The features, advantages, or alternative embodiments mentioned herein can also be applied to other claimed technical solutions, and vice versa.

[0073] In another advantageous embodiment of the proposed X-ray device, the X-ray device can be designed as a multi-energy cone-beam computed tomography (CBCT) device, especially a dual-energy cone-beam computed tomography (DBC) device.

[0074] Therefore, the first X-ray image dataset and the second X-ray image dataset can be acquired using the same multi-functional CBCT.

[0075] In a third aspect, the present invention relates to a computer program product comprising a computer program directly loadable into the memory of a providing unit, having program code segments for performing all steps of a proposed method for multi-energy X-ray imaging of an examination object when the program code segments are executed by the providing unit. The computer program product may herein include software having source code that still requires compilation and linking or only requires interpretation, or executable software code that only needs to be loaded into the providing unit for execution. With this computer program product, the method for multi-energy X-ray imaging of an examination object can be performed quickly, repeatably, and robustly by the providing unit. This computer program product is designed to perform the method steps of the present invention by the providing unit.

[0076] The computer program product, for example, is stored on a computer-readable storage medium or on a network or server, and can be loaded from there into the processor of the providing unit, which may be directly connected to the providing unit or be part of the providing unit. Furthermore, the control information of the computer program product can be stored on an electronically readable data carrier. The control information on the electronically readable data carrier can be designed to execute the method according to the invention when the data carrier is used in the providing unit. Examples of electronically readable data carriers include DVDs, magnetic tapes, or USB flash drives, on which electronically readable control information, especially software, is stored. When this control information is read from the data carrier and stored in the providing unit, all embodiments of the aforementioned method according to the invention can be executed.

[0077] The software-based implementation offers the following advantages: existing supply units can be modified through simple software updates to operate in the manner described in this invention. In addition to the computer program, this computer program product may optionally include other components, such as documentation and / or add-ons, and hardware components, such as hardware keys (dongles, etc.) for using the software.

[0078] Embodiments of the present invention are shown in the accompanying drawings and described in detail below. The same features are referred to by the same reference numerals in different drawings. In the drawings:

[0079] Figures 1 to 4 Schematic diagrams illustrating different implementations of the proposed multi-energy X-ray imaging method for examining the object are shown.

[0080] Figure 5 A schematic diagram showing the spatial intensity variation curves of the first X-ray image dataset, the second X-ray image dataset, and the result dataset is provided.

[0081] Figure 6 A schematic diagram illustrating an advantageous implementation of the proposed medical X-ray device is shown.

[0082] Figure 1 A schematic diagram illustrating an advantageous implementation of the proposed multi-energy X-ray imaging method for examining an object is shown. Here, a first X-ray image dataset RBD1 with a first spatial resolution (CAP-RBD1) can be acquired. Advantageously, the first X-ray image dataset RBD1 is acquired using a first X-ray spectrum. In another step, a second X-ray image dataset RBD2 with a second spatial resolution (CAP-RBD2) can be acquired. The first and second X-ray image datasets RBD1 and RBD2 can be acquired, particularly using a medical X-ray device. Here, the second X-ray image dataset RBD2 can be acquired using a second X-ray spectrum. Furthermore, the first and second X-ray image datasets RBD1 and RBD2 can present at least a partially common examination area of ​​the object. Additionally, the first and second X-ray spectra can be different from each other. Advantageously, the second spatial resolution can be smaller than the first spatial resolution. In another step, the spatial modulation of the second X-ray image dataset RBD2 (ADJ-RBD2) can be adjusted based on the geometric and / or anatomical features of the object presented in the first and second X-ray image datasets RBD1 and RBD2. Subsequently, a PROV-ED result dataset ED can be provided based on the adjusted second X-ray image dataset RBD2.A. Advantageously, a PROV-ED result dataset ED can also be provided based on the first X-ray image dataset RBD1.

[0083] Advantageously, acquiring the CAP-RBD2 second X-ray image dataset RBD2 may include binning the image points.

[0084] Advantageously, the second X-ray image dataset RBD2 can be acquired with a larger focal size than the first X-ray image dataset RBD1.

[0085] Advantageously, the first X-ray image dataset RBD1 and the second X-ray image dataset RBD2 can present the contrast agent disposed within the examination area. Here, the geometric and / or anatomical features of the examined object can include the respective imaging of the contrast agent. Furthermore, the first X-ray image dataset RBD1 and the second X-ray image dataset RBD2 can simultaneously present the at least partially common examination area.

[0086] Figure 2 A schematic diagram illustrating another advantageous embodiment of the proposed method for multi-energy X-ray imaging of an object under examination is shown. Here, the first X-ray image dataset RBD1 and the second X-ray image dataset RBD2 can be registered with each other (REG-RBD1-RBD2).

[0087] Figure 3 A schematic diagram illustrating another advantageous embodiment of the proposed multi-energy X-ray imaging method for examining an object is shown. Here, acquiring the first X-ray image dataset RBD1 (CAP-RBD1) may include acquiring multiple first X-ray projection images PD1 (CAP-PD1). Furthermore, the first X-ray image dataset RBD1 can be reconstructed from the multiple first X-ray projection images PD1. Similarly, acquiring the second X-ray image dataset RBD2 (CAP-RBD2) may include acquiring multiple second X-ray projection images PD2 (CAP-PD2). Here, the second X-ray image dataset RBD2 can be reconstructed from the multiple second X-ray projection images PD2.

[0088] Figure 4 A schematic diagram illustrating another advantageous embodiment of the proposed method for multi-energy X-ray imaging of the object under examination is shown. Here, the PROV-ED result dataset ED can additionally be provided based on the first X-ray image dataset RBD1.

[0089] exist Figure 5The diagram schematically illustrates the spatial intensity variation curves IV1 of the first X-ray image dataset RBD1 and IV2 of the second X-ray image dataset RBD2. The maximum heights AH1 and AH2, and especially the peak amplitudes, of each intensity variation curve IV1 and IV2 can depend on the attenuation of X-rays in each X-ray spectrum, particularly the first and second X-ray spectra, after interaction with the examined area, especially the contrast agent. Furthermore, the edge widths EW1 and EW2 of each intensity variation curve IV1 and IV2 can depend on the respective spatial resolutions of the first and second X-ray image datasets RBD1 and RBD2.

[0090] Advantageously, adjusting the spatial modulation of the second X-ray image dataset RBD2, particularly the spatial intensity variation curve IV2, may include transferring the first spatial resolution to the second X-ray image dataset RBD2. Here, the spatial modulation of the second X-ray image dataset RBD2 can be adjusted such that the amplitude and / or integral of the spatial intensity variation curve IV2 is preserved. The adjusted intensity variation curve IV2.A of the second X-ray image dataset RBD2.A may, for example, have the edge width EW1 of the first X-ray image dataset, and the amplitude peak AH2 and / or integral of the intensity variation curve IV2 of the second X-ray image dataset RBD2.

[0091] Figure 6 A schematic diagram illustrating an advantageous embodiment of the proposed medical X-ray device is shown here. Figure 6 Taking the proposed X-ray device as an example, a medical C-arm X-ray device 37 is schematically shown, which includes a providing unit PRVS, a display unit 41, and an input unit 42. The medical C-arm X-ray device 37 may advantageously have an X-ray detector 34 and an X-ray source 33, which are arranged in a defined configuration on a C-arm 38. The C-arm 38 of the C-arm X-ray device 37 may be movably supported about one or more axes. Furthermore, the C-arm X-ray device 37 may include a movement unit 39, such as a wheeled system and / or a robotic arm and / or a track system, enabling the C-arm X-ray device to move in space. Figure 6 The schematically shown C-arm X-ray device 37 can be advantageously designed as a multi-functional CBCT.

[0092] To acquire a first X-ray image dataset RBD1 and a second X-ray image dataset RBD2, particularly the first and second X-ray projection images PD1 and PD2, positioned on the patient positioning device 32, the providing unit PRVS can send a signal 24 to the X-ray source 33. The X-ray source 33 can then emit a beam of X-rays. When this beam of X-rays interacts with the object 31 and irradiates the surface of the detector 34, the detector 34 can send a signal 21 to the providing unit PRVS. The providing unit PRVS can then acquire the first X-ray image dataset RBD1 and the second X-ray image dataset RBD2, particularly the first and second X-ray projection images PD1 and PD2, based on the signal 21.

[0093] Input unit 42 may include, for example, a keyboard and / or pointing device and / or an acquisition unit, such as a voice acquisition unit and / or a gesture acquisition unit. Furthermore, display unit 41 may include, for example, a monitor and / or display and / or a projector. Input unit 42 is preferably integrated into display unit 41, for example, in a capacitive and / or resistive input display screen. Input unit 42 may be advantageously designed to acquire user input. For this purpose, input unit 42 may, for example, send signal 26 to providing unit PRVS. Providing unit PRVS may be designed to control the acquisition of a first X-ray image dataset RBD1 and a second X-ray image dataset RBD2, particularly the first and second X-ray projection images PD1 and PD2, based on user input.

[0094] Display unit 41 can be advantageously designed to graphically display the result dataset. For this purpose, providing unit PRVS can send signal 25 to display unit 41.

[0095] The schematic diagrams included in the figures do not represent any scale or size ratio.

[0096] Finally, it should be reiterated that the methods and devices described in the foregoing description are merely implementation methods, and those skilled in the art can make various modifications to them without departing from the scope of the invention. Furthermore, the use of the indefinite article "a" does not preclude the possibility that a mentioned feature may exist multiple times. Similarly, the terms "unit" and "element" do not preclude the possibility that a mentioned component consists of multiple cooperating sub-components, which may also be spatially distributed.

[0097] In the context of this application, the term "based on" can be understood in particular as "utilizing". In particular, the statement "generating (alternatively: obtaining, determining, etc.) the first feature based on the second feature" does not preclude the first feature from being generated (alternatively: obtaining, determining, etc.) based on the third feature.

Claims

1. A method for performing multi-energy X-ray imaging on an object (31) under examination, comprising: - Acquire (CAP-RBD1) a first X-ray image dataset (RBD1) with a first spatial resolution, wherein the first X-ray image dataset (RBD1) is acquired using a first X-ray spectrum. - Acquire (CAP-RBD2) a second X-ray image dataset (RBD2) with a second spatial resolution, wherein the second X-ray image dataset (RBD2) is acquired using a second X-ray spectrum. The first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2) present at least a portion of the common inspection area of ​​the object under inspection (31). The first X-ray spectrum and the second X-ray spectrum are different from each other. The second spatial resolution is smaller than the first spatial resolution. - Based on the geometric and / or anatomical features of the object under examination (31) presented in the first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2), adjust the spatial modulation of the second X-ray image dataset (RBD2) (ADJ-RBD2). - Providing a (PROV-ED) results dataset (ED) based on the adjusted second X-ray image dataset (RBD2.A).

2. The method according to claim 1, wherein, The acquisition of the second X-ray image dataset (RBD2) (CAP-RBD2) includes binning of image points.

3. The method according to claim 1 or 2, wherein, The second X-ray image dataset (RBD2) is acquired with a larger focus relative to the first X-ray image dataset (RBD1).

4. The method according to any one of the preceding claims, wherein, The first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2) are registered with each other (REG-RBD1-RBD2).

5. The method according to any one of the preceding claims, wherein, The acquisition (CAP-RBD1) of the first X-ray image dataset (RBD1) includes the acquisition (CAP-PD1) of multiple first X-ray projection images (PD1). The first X-ray image dataset (RBD1) is reconstructed from multiple first X-ray projection images (PD1) (RECO-RBD1). The acquisition of the second X-ray image dataset (RBD2) (CAP-RBD2) includes the acquisition (CAP-PD2) of multiple second X-ray projection images (PD2). The second X-ray image dataset (RBD2) is reconstructed from multiple second X-ray projection images (PD2) (RECO-RBD2).

6. The method according to any one of the preceding claims, wherein, The adjustment of the spatial modulation of the second X-ray image dataset (RBD2) (ADJ-RBD2) includes transferring the first spatial resolution to the second X-ray image dataset (RBD2).

7. The method according to any one of the preceding claims, wherein, The second X-ray image dataset (RBD2) presents spatial intensity variation curves. Specifically, the spatial modulation of the second X-ray image dataset (RBD2) (ADJ-RBD2) is adjusted so that the amplitude and / or integral of the spatial intensity variation curve are preserved.

8. The method according to any one of the preceding claims, wherein, The first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2) present contrast agents arranged within the examination area. The geometric and / or anatomical features of the object under examination (31) include various imaging features of the contrast agent.

9. The method according to any one of the preceding claims, wherein, The first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2) simultaneously present the at least partially common examination area.

10. The method according to any one of the preceding claims, wherein, Additionally, the resulting dataset (ED) is provided (PROV-ED) based on the first X-ray image dataset (RBD1).

11. The method according to any one of the preceding claims, wherein, The first X-ray image dataset (RBD1) and the second X-ray image dataset (RBD2) were acquired using medical X-ray equipment.

12. A medical X-ray device designed to perform the method according to any one of the preceding claims.

13. The medical X-ray device according to claim 12, wherein, The X-ray equipment is designed as a multi-energy cone-beam computed tomography (CT) scanner.

14. A computer program product having a computer program capable of being directly loaded into a memory of a providing unit (PRVS), having a program code segment for performing all the steps of the method according to any one of claims 1 to 11 when the program code segment is executed by the providing unit (PRVS).

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