Managing geometric misalignment in an X-ray imaging system
阅读说明：本技术 管理x射线成像系统中的几何失准 (Managing geometric misalignment in an X-ray imaging system ) 是由 马茨·丹尼尔松 刘学进 马丁·舍林 于 2018-06-20 设计创作，主要内容包括：本发明提供了一种用于管理X射线成像系统中的几何失准的方法,该X射线成像系统具有X射线源、光子计数的X射线检测器和在X射线源和X射线检测器之间的X射线路径上的中间准直器结构。X射线检测器包括多个像素,并且准直器结构包括多个准直器单元,其中准直器单元的至少一个子集中的每一个对应于像素的N×M矩阵,其中N和M中的至少一个大于1。该方法包括：针对包括至少两个像素的指定像素子集,监测(S1)来自指定像素子集的像素的输出信号,该至少两个像素由于几何失准而受到来自所述准直器结构的阴影的不同影响；以及基于来自所述指定像素子集的所述像素的所述监测输出信号来确定(S2)几何失准的发生。(The present invention provides a method for managing geometric misalignments in an X-ray imaging system having an X-ray source, a photon counting X-ray detector, and an intermediate collimator structure in the X-ray path between the X-ray source and the X-ray detector. The X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. The method comprises the following steps: monitoring (S1) output signals from pixels of a specified subset of pixels for a specified subset of pixels comprising at least two pixels which are differently affected by shadows from the collimator structure due to geometric misalignment; and determining (S2) an occurrence of a geometric misalignment based on the monitoring output signals from the pixels of the specified subset of pixels.)
1. A method for managing geometrical misalignments in an X-ray imaging system (100) having an X-ray source (10), a photon counting X-ray detector (20), and an intermediate collimator structure (22) in the X-ray path between the X-ray source and the X-ray detector,
wherein the X-ray detector (20) comprises a plurality of pixels (21) and the collimator structure (22) comprises a plurality of collimator units (23), wherein each of at least a subset of the collimator units corresponds to an N X M matrix of the pixels, wherein at least one of N and M is larger than 1, wherein the method comprises:
-monitoring (S1) output signals from a given pixel subset comprising at least two of the pixels for the pixel subset, at least two of the pixels being affected differently by shadows from the collimator structure due to the geometric misalignment; and is
-determining (S2) an occurrence of the geometric misalignment based on the monitored output signals of the pixels from the specified subset of pixels.
2. The method of claim 1, wherein at least two of the pixels have different responses to the shadow, and the different responses are monitored by measuring the output signals.
3. The method according to claim 1 or 2, wherein the method further comprises: i) estimating at least one parameter indicative of the geometric misalignment and/or ii) correcting the geometric misalignment based on the monitored output signals of the pixels from the specified subset of pixels and/or iii) performing post-processing of the output signals and/or iv) reconstructing an image based on the parameter indicative of the geometric misalignment and/or based on the monitored output signals of the pixels from the specified subset of pixels.
4. The method of any of claims 1 to 3, wherein an effect of the geometric misalignment on the output signal of at least one of the pixels or on a value of at least one of the pixels based on the output signal is corrected based on the monitored output signals of the pixels from the specified subset of pixels.
5. The method of claim 4, wherein at least one of the pixels is located behind an object/subject to be imaged during image acquisition.
6. The method of any one of claims 1 to 5, wherein the output signal from the pixel represents a photon count of the pixel.
7. The method of any of claims 1 to 6, wherein the output signals from the pixels of the specified subset of pixels are measured during image acquisition of an object/subject and are located outside the object/subject to be imaged during measurement.
8. The method of any of claims 1 to 7, wherein at least two of the pixels differently affected by shading are positioned relative to the collimator structure such that at least two of the pixels experience a different shading than the collimator structure due to the geometric misalignment.
9. The method of any one of claims 1 to 8, wherein at least two of the pixels that differ by shading comprise a first subset of one or more of the pixels that have an increased number of photon counts due to shading and a second subset of one or more of the pixels that have a decreased number of photon counts due to the shading.
10. The method of any of claims 1 to 9, wherein each of the collimator units has a first side and an opposite second side, and at least one of the pixels of a given subset is located on the first side of the collimator unit and at least one of the pixels of the given subset is located on the opposite second side of the same or another collimator unit.
11. The method according to claim 10, wherein the X-ray detector (20) comprises a plurality of detector modules (24) and the pixels located on opposite sides of the collimator unit belong to different detector modules of the X-ray detector.
12. The method of any of claims 1 to 11, wherein the geometric misalignment comprises a relative geometric misalignment between the X-ray source and the X-ray detector.
13. The method of any of claims 1 to 12, wherein the direction and/or extent of pixel shadowing caused by the geometric misalignment is determined based on the monitored output signals of the pixels from the specified subset of pixels.
14. The method of any of claims 1 to 13, wherein the X-ray detector (20) is a photon counting and energy discriminating X-ray detector and the effect of the geometrical misalignment on the photon counting of at least one of the pixels is corrected based on the output signals of the pixels of the specified subset of pixels or the values of the pixels of the specified subset of pixels based on the output signals and the related photon energy information obtained from the photon counting and energy discriminating X-ray detector being monitored.
15. The method of claim 14, wherein the photon counting and energy discriminating X-ray detector is configured to: dividing the detected photons into energy bins, and correcting for the effect of the geometric misalignment on the photon count comprises: correcting photon counts in the energy bins of at least one of the pixels based on the monitored photon counts of the pixels of the specified subset of pixels and the correlated photon energy information.
16. The method of claim 15, wherein a correction factor is determined based on at least one parameter indicative of the geometric misalignment and a base material thickness.
17. The method of claim 16, wherein the correction factor is determined and applied to photon counts in lower energy bins.
18. The method of any of claims 1 to 17, wherein the geometric misalignment is distinguished from a drop in a current-peak-kilovolt ratio (mA/kVp) of the X-ray source based on the monitored output signals of the pixels of the specified subset of pixels.
19. Method according to any of claims 1-18, wherein the management of the geometric misalignment comprises monitoring and/or handling the geometric misalignment, e.g. monitoring and/or correcting/calibrating the geometric misalignment.
20. A system (25; 30; 40; 50; 200) configured for managing geometric misalignments in an X-ray imaging system (100), the X-ray imaging system (100) having an X-ray source (10), a photon counting X-ray detector (20) and an intermediate collimator structure (22) in an X-ray path between the X-ray source and the X-ray detector, wherein the X-ray detector (20) comprises a plurality of pixels (21) and the collimator structure (22) comprises a plurality of collimator units (23), wherein each of at least one subset of the collimator units corresponds to an N X M matrix of the pixels, wherein at least one of N and M is larger than 1,
wherein the system is configured to monitor output signals from a given pixel subset of at least two of the pixels for the given pixel subset, at least two of the pixels being differently affected by shadows from the collimator structure due to the geometric misalignment; and is
Wherein the system is configured to determine the occurrence of the geometric misalignment based on the monitored output signals from the pixels of the specified subset of pixels.
21. The system of claim 20, wherein at least two of the pixels have different responses to the shadow, and the system is configured to monitor the different responses by measuring the output signals.
22. The system of claim 20 or 21, wherein the system is further configured to: estimating at least one parameter indicative of the geometric misalignment and/or correcting the geometric misalignment based on the monitored output signals of the pixels from the specified subset of pixels and/or iii) performing post-processing of the output signals and/or iv) reconstructing an image based on the parameter indicative of the geometric misalignment and/or based on the monitored output signals of the pixels from the specified subset of pixels.
23. An X-ray imaging system (100) comprising the system according to any one of claims 20 to 22.
24. A computer program product comprising a computer readable medium (220; 230) having stored thereon a computer program (225; 235), for managing geometrical misalignments in an X-ray imaging system (100), when executed by a processor (210), the X-ray imaging system (100) having an X-ray source (10), a photon counting X-ray detector (20), and an intermediate collimator structure (22) in an X-ray path between the X-ray source and the X-ray detector, wherein the X-ray detector (20) comprises a plurality of pixels (21) and the collimator structure (22) comprises a plurality of collimator units (23), wherein each of at least one subset of the collimator units corresponds to an N X M matrix of the pixels, wherein at least one of N and M is larger than 1,
wherein the computer program (225; 235) comprises instructions which, when executed by the processor (210), cause the processor to:
-monitoring output signals from a given pixel subset comprising at least two of said pixels for said pixel subset, at least two of said pixels being affected differently by shadows from said collimator structure due to said geometric misalignment; and is
-determining an occurrence of the geometric misalignment based on the monitored output signals of the pixels from the specified subset of pixels.
25. An X-ray detector (20) comprising:
-a plurality of edge detector modules (24) arranged side by side and adapted to be oriented towards an edge of an X-ray source (10), each of said edge detector modules (24) having at least one detector pixel (21); and
-a collimator structure (22) arranged on an X-ray path between the X-ray source and the edge detector module, wherein the collimator structure (22) comprises at least one collimator unit (23) corresponding to an N X M matrix of the pixels, wherein at least one of N and M is larger than 1, and at least one collimator lamella in the collimator unit is arranged offset with respect to a boundary between the pixels.
26. X-ray detector according to claim 25, wherein the edge detector module (24) has a lateral extension and a longitudinal extension, and collimator lamellae of the collimator unit orthogonal to the longitudinal extension of the detector module are arranged offset with respect to pixel boundaries.
27. An X-ray detector (20) comprising:
-a plurality of edge detector modules (24) arranged side by side and adapted to be oriented towards an edge of the X-ray source (10);
-X-ray attenuating structures arranged between at least a subset of the edge detector modules (24); and
-a collimator structure (22) arranged on an X-ray path between the X-ray source and the edge detector modules, wherein the collimator structure (22) comprises at least one collimator lamella arranged as an extension of an X-ray attenuating structure and having a thickness larger than a thickness of the X-ray attenuating structure located between the edge detector modules.
28. The X-ray detector of claim 27, wherein the X-ray attenuating structure comprises at least one X-ray attenuating sheet or anti-scatter foil.
29. X-ray detector according to claim 27 or 28, wherein the edge detector modules (24) have a charge collecting front side and a charge collecting back side, and at least a subset of the edge detector modules are arranged in pairs from front side to front side, wherein the at least one collimator sheet covers a front side to front side gap between the front sides.
Technical Field
The present invention relates generally to the field of X-ray imaging technology, and more particularly to a method and system for managing geometrical misalignments in an X-ray imaging system, a corresponding X-ray imaging system and a corresponding computer program product.
Background
Radiographic imaging, such as X-ray imaging, has been used for many years in medical applications and non-destructive testing.
Typically, an X-ray imaging system includes an X-ray source and an X-ray detector system. The X-ray source emits X-rays that pass through a subject or object to be imaged and are then recorded by the X-ray detector system. Since some materials absorb a greater portion of the X-rays than others, an image of the subject or object is formed.
Referring to fig. 1, it may be desirable to begin with a brief overview of an illustrative overall X-ray imaging system. In this non-limiting example, the
As shown in FIG. 2, another example of an
The entire detector may be considered an
The digital portion including the
An example of a commonly used X-ray imaging system is a Computed Tomography (CT) system. Fig. 3 is a schematic diagram illustrating an example of a CT system. In the example of fig. 3, a CT system may include an X-ray source that produces a fan or cone beam of X-rays and an opposing X-ray detector system for recording fractions of X-rays transmitted through a patient or object. The X-ray source and detector system are typically mounted in a gantry that rotates around the imaging subject. Thus, the X-ray source and X-ray detector system shown in fig. 3 may be arranged as part of a CT system, e.g. mountable in a CT gantry. The overall CT system may also include appropriate controllers and management systems.
Fig. 4 is a schematic view of an X-ray detector according to an exemplary embodiment. In this example, a schematic view of an X-ray detector and an X-ray source emitting X-rays is shown. For example, the elements of the detector may be pointing back towards the source of radiation, and they are preferably arranged in a slightly curved overall structure. The size and segmentation of the detector array affects the imaging capabilities of the X-ray imaging system. The direction of the incident X-rays is called the y-direction. Multiple detector pixels in the direction of the axis of rotation of the gantry (referred to as the z-direction) enable multi-slice image acquisition. Multiple detector pixels along the angular direction (referred to as the X-direction) enable simultaneous measurement of multiple projections in the same plane and are applied in fan/cone beam CT. Most conventional detectors have detector pixels in both the slice (z) and angular (x) directions.
Modern X-ray detectors typically convert incident X-rays into electrons by light absorption and/or compton interaction, and the resulting electrons produce secondary visible light, which is then detected by a photosensitive material. Other detectors are based on semiconductors that convert X-rays directly into electron-hole pairs that are collected by shifting charge carriers in an applied electric field.
Most X-ray detectors currently used for medical imaging are energy integrating detectors, which means that the output signal is the sum of the energies of the photons interacting during the measurement period. Thus, the contribution of each detected photon to the signal is proportional to the energy of the photon.
Photon counting detectors are also a viable alternative in some applications; photon counting detectors are currently commercially available in mammography, for example. Many photon counting detectors are spectral (energy resolved), meaning that they can classify detected photons based on the energy deposited in the detector material when the photons interact. Energy classification is performed using energy bins defined by programmable energy thresholds. The energy information may be used to obtain additional information about the composition of the object through which the photons have passed. This additional information may in turn be used to improve image quality and/or reduce radiation dose.
Compared to energy integrating X-ray detector systems, photon counting X-ray detector systems have the following advantages: the energy threshold may be used to remove electronic noise in the measurement signal that contains the energy integrating detector; the energy information can be used to perform so-called material-based decomposition by which different materials and/or compositions in the examined body can be identified and quantified (r.e. alvarez, medical physics, 38(5) · 2324-2334, 2011); no afterglow (afterglow) of the detector increasing the angular resolution (the detector will generate a signal output in a short time after the input signal has stopped); also, higher spatial resolution can be achieved by having smaller pixel sizes. Materials for X-ray detectors for photon counting include cadmium telluride (CdTe), Cadmium Zinc Telluride (CZT), and silicon (Si).
Us patent 8,183,535 discloses an example of a photon counting edge X-ray detector. In this patent, a plurality of semiconductor detector modules are arranged together to form the entire detector area, wherein each semiconductor detector module includes an X-ray sensor oriented edge-to-edge to incident X-rays and connected to an integrated circuit for registering X-rays interacting in the X-ray sensor.
Semiconductor detector modules are typically tiled together to form complete detectors of almost any size and with near-perfect geometric efficiency.
Fig. 5 is a schematic diagram illustrating an example of a semiconductor detector module. This is an example of a semiconductor detector module with a sensor part divided into detector elements, where each detector element is typically based on a diode with a charge collection electrode as a key component. In the example of fig. 5, assuming that X-rays enter through the edge, the semiconductor sensor portion is also divided into so-called depth segments in the depth direction.
Typically, the detector elements are individual X-ray sensitive sub-elements of the detector. Typically, photon interactions occur in the detector elements, and the resulting charges are collected by respective electrodes of the detector elements.
Depending on the detector topology, the detector elements may correspond to pixels, especially when the detector is a flat panel detector. However, a depth segment detector may be viewed as having a plurality of detector bars, each detector bar having a plurality of depth segments. For such a depth segment detector, each depth segment may be considered as a separate detector element, in particular if each depth segment is associated with its own separate charge collection electrode. The detector bars of a depth segmented detector typically correspond to the pixels of a normal flat panel detector.
The data output from a photon counting spectral detector typically includes the number of photons detected within an energy bin (pulse height between two thresholds), or the number of photons detected that are greater than an energy threshold. The photon count data can be used to estimate the material composition of the imaged object, a process commonly referred to as basis material decomposition. This can be done in the projection domain: estimating the material thickness of each pixel separately and forming an image of each base material; or in the image domain: an image of each energy bin is formed and material estimation is performed using the different bin images.
Object collimators or more generally collimator structures, also called scatter grids or anti-scatter grids, are commonly used in modern CT systems. In general, as shown in fig. 6, the
As shown in fig. 7, these collimator elements typically maintain a cell-to-pixel relationship with the
Misalignment of the detector, anti-scatter grid and source results in: errors in the geometric parameters of the image acquisition (the position where each measurement is performed); and shadowing of the detector, which in turn can lead to loss of photons and changes in the spectral response of the detector.
A number of methods for geometric calibration of CT imaging systems have been developed, namely estimation of the geometric parameters of the image acquisition:
US 2014/0211925,
U.S. patent No. 6,370,218 describes an invention in which a multi-layered X-ray detector is used to measure the penumbra (partial illumination area) of an X-ray illumination field to determine the position of the X-ray tube focus.
WO 2010/093314 mentions that measurement information is obtained from an edge-to-X-ray detector with depth segments and that the ratio of the number of X-ray counts detected in different depth segments is used to measure the degree of shadowing.
Us patent No. 5,131,021 relates to an invention in which a set of X-ray attenuating masks is placed over pixels outside the imaged object. The position of the X-ray source in the axial (z) direction is then estimated based on the ratio of the measurement signals in units of pixels with different masks.
Us patent No. 8,262,28 describes a method of determining the focal spot position by pointing a set of anti-scatter foils to a point other than the source position. Intentionally misaligned anti-scatter flakes cause shadows on detector pixels located near the flakes and movement of the source causes a change in the measured X-ray intensity, which can then be used to estimate the source position.
In order to improve the detection efficiency of Single Photon Emission Computed Tomography (SPECT) systems, multi-pixel matched collimators (collimator units matched to a plurality of detector pixels) have been proposed. Reference may be made, for example, to WO 2016162962a1, WO2011093127a1 and a. suzuki et al, physics in medicine and biology, 58.7 (2013): 2199. However, multi-pixel matched collimators are not typically used for CT. Fig. 12 shows an example of a multi-pixel matched collimator.
There are three types of misalignment that can result in shadowing of the detector from the object collimator (i.e., a portion of the detector cannot be illuminated by X-rays). The first type is misalignment of the X-ray source (in the X or z direction), in which case the collimator lamellae will be in the path of the incident X-ray beam and result in different active cross-sections along the depth of the detector, as shown in fig. 8. The second type is misalignment of the detector (X-direction or z-direction), which will result in the same situation as misalignment of the X-ray source, as shown in fig. 9. A third type is misalignment of the collimator lamellae, which will always result in a fixed amount of passive detector area along the depth of the detector, as shown in fig. 10.
Misaligned shadows from the source or collimator cause a loss of counts in the shadow pixels. Shadows caused by source misalignment also cause the active cross-section of the detector material to be different at different depths in the detector. Since the detectors have different spectral responses at different depths, this means that the spectral response of each detector pixel will depend on the extent of the shadowing. This effect will be referred to herein as a nonlinear spectral effect. Different spectral responses lead to problems with difficult normalization; the relative gain of each pixel (output signal as a function of input signal) depends on the shape of the input X-ray spectrum. It is therefore difficult to remove pixel differences by normalizing the output signal, for example with a single correction factor determined from a single reference measurement, for example an air scan (so-called flat field). If pixels with different spectral responses are not corrected, there is a risk that the reconstructed image has ring artifacts (rings of brighter or darker values due to higher or lower gain of the detector pixel compared to its neighboring pixels).
Since there is no spectral information available, the energy integrating detector cannot correct for different spectral responses even if the degree of shading in the pixels can be properly known. Therefore, the pixels on the energy integrating detector must have nearly the same spectral response to cope with the non-linear spectral effects. For example, see US 2016/0025867 a1, US 2013/0121475a1, which may be obtained by blocking areas at risk of shadows (i.e. the edges of pixels) with a highly attenuating material (shown in fig. 11), or by tilting the collimator lamellae at a predetermined angle (possibly greater than 1 ℃) relative to the detector array, see US 2013/0121475a1, or by adjusting the height of the collimator lamellae to ensure that the shadow effect is less than a threshold (e.g. the detection efficiency is reduced by 5%), see CN 1596829 a.
On the other hand, for a photon counting spectral detector, it is not necessary to have the same spectral response if the image is formed using material-based decomposition in the projection domain. In-system calibrationAny spectral differences (e.g., static misalignments) during the same period as during an image acquisition scan can be detected by utilizing a forward model that accurately captures pixel-dependent detector responses[6]A material-based decomposition is performed to remove. For example, a forward model may be obtained from material calibration during system calibration (r.e. alvarez, medical physics, 38(5) · 2324-2334, 2011).
However, for example, for dynamic misalignments caused by mechanical motion during scanning, there is no a priori knowledge from the system calibration and therefore calibration data cannot be used for correction. While a source monitor may be used to monitor the position of the X-ray source for further correction, high accuracy is difficult to achieve. For energy integrating detectors the effect of dynamic misalignment is mitigated using a method such as that suggested in US 2016/0025867 a1, which requires an additional grid between the object collimator and the detector to provide more shading and thus ensure a uniform active area between different detector pixels if, for example, the source has moved during scanning.
Pixel a and pixel B in the illustration shown in fig. 11 have the same active area even if both the collimator lamellae and the source are misaligned. However, this approach implies a significant sacrifice in the geometric efficiency of the detector, which can be seen in fig. 11 (X-rays blocked by the extra grid are lost), and if this approach is used for photon counting detectors, this sacrifice will be greater due to their smaller pixel size. In general, the detector pixels are denoted by
Disclosure of Invention
It is a general object to improve the performance of X-ray imaging systems, such as CT systems.
It is a particular object to provide a method for managing geometrical misalignments in an X-ray imaging system.
It is another object of the present invention to provide a system configured for managing geometric misalignments in an X-ray imaging system.
It is a further object to provide an X-ray imaging system comprising such a system.
It is a further object to provide a corresponding computer program product.
These and other objects are met by embodiments of the present invention.
According to a first aspect, a method for managing geometrical misalignments in an X-ray imaging system is provided, wherein the X-ray imaging system has an X-ray source, a photon counting X-ray detector and an intermediate collimator structure in the X-ray path between the X-ray source and the X-ray detector. The X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. The method comprises the following steps:
-monitoring output signals of pixels from a specified subset of pixels for a specified subset of pixels comprising at least two pixels, wherein the at least two pixels are differently affected by shadows from the collimator structure due to the geometric misalignment; and
-determining an occurrence of a geometric misalignment based on the monitored output signals from the pixels of the specified subset of pixels.
In this way, geometric misalignments in the X-ray imaging system can be efficiently handled.
According to a second aspect, there is provided a system configured for managing geometric misalignments in an X-ray imaging system having an X-ray source, a photon counting X-ray detector and an intermediate collimator structure in an X-ray path between the X-ray source and the X-ray detector. The X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. The system is configured to monitor output signals from pixels of a specified subset of pixels for a specified subset of pixels comprising at least two pixels, wherein the at least two pixels are differently affected by shadows from the collimator structure due to geometric misalignment. The system is configured to determine an occurrence of a geometric misalignment based on monitored output signals from pixels of the specified subset of pixels.
According to a third aspect, an X-ray imaging system comprising such a system is provided.
According to a fourth aspect, a computer program product comprising a computer readable medium having stored thereon a computer program for managing a geometric misalignment, a photon counting X-ray detector and an intermediate collimator structure on an X-ray path between the X-ray source and the X-ray detector in an X-ray imaging system with the X-ray source when executed by a processor is provided. In this application, the X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. The computer program includes instructions that, when executed by the processor, cause the processor to:
-monitoring output signals of pixels from a specified subset of pixels for a specified subset of pixels comprising at least two pixels, wherein the at least two pixels are differently affected by shadows from the collimator structure due to the geometric misalignment; and is
-determining an occurrence of a geometric misalignment based on the monitored output signals from the pixels of the specified subset of pixels.
According to a fifth aspect, there is provided an X-ray detector comprising:
-a plurality of edge detector modules arranged side by side and adapted to be oriented towards an edge of the X-ray source, each edge detector module having at least one detector pixel; and
a collimator structure arranged in an X-ray path between the X-ray source and the edge detector module, wherein the collimator structure comprises at least one collimator unit corresponding to an N X M matrix of pixels, wherein at least one of N and M is larger than 1, and at least one collimator lamella of the collimator unit is arranged offset with respect to a boundary between pixels.
According to a sixth aspect, there is provided an X-ray detector comprising:
-a plurality of edge detector modules arranged side by side and adapted to be oriented towards an edge of the X-ray source;
-an X-ray attenuating structure arranged between at least a subset of the edge detector modules; and
a collimator structure arranged in the X-ray path between the X-ray source and the edge detector modules, wherein the collimator structure comprises at least one collimator lamella arranged as an extension of the X-ray attenuating structure and having a thickness larger than the thickness of the X-ray attenuating structure located between the edge detector modules.
Other advantages will be appreciated upon reading the detailed description.
Drawings
These embodiments, together with further objects and advantages thereof, may best be understood by reference to the following description taken in conjunction with the accompanying drawings in which:
fig. 1 is a schematic diagram showing an example of an entire X-ray imaging system.
Fig. 2 is a schematic diagram illustrating another example of an X-ray imaging system.
Fig. 3 is a schematic diagram illustrating an example of a CT system.
Fig. 4 is a schematic view of an X-ray detector according to an exemplary embodiment.
Fig. 5 is a schematic diagram illustrating an example of a semiconductor detector module.
Fig. 6 is a schematic diagram showing an example of a two-dimensional object collimator in which the collimator unit is composed of heavy element lamellae in the x and z directions.
Fig. 7 is a schematic diagram showing an example of a z-direction view of the cell-pixel relationship between the collimator cell and the detector pixel.
Fig. 8 is a schematic diagram illustrating an example of misalignment of an X-ray source.
Fig. 9 is a schematic diagram illustrating an example of misalignment of a detector.
Fig. 10 is a schematic diagram illustrating an example of misalignment of collimator lamellae.
Fig. 11 is a schematic diagram illustrating an example of a conventional solution in which an additional grid is employed between the object collimator and the detector to avoid negative effects caused by dynamic or static misalignments.
Fig. 12 is a schematic diagram showing an example of a y-direction view of the proposed geometry between an object collimator and a flat detector, where the collimator elements correspond to several detector pixels. This geometry is applied to flat panel detectors.
Fig. 13 is a schematic diagram showing an example of a y-direction view of the proposed geometry between an object collimator and a flat detector, where the collimator elements correspond to several detector pixels. This geometry is applied to the edge detector array.
Fig. 14 is a schematic diagram showing an example of a view from the z direction of the proposed geometry between an object collimator and a flat detector, where the collimator unit corresponds to two pixels in one direction.
Fig. 15 is a schematic diagram illustrating an example of an X-ray detector having a collimator structure with at least one collimator unit offset with respect to a pixel boundary.
Fig. 16 is a schematic diagram illustrating an example of the symmetry maintained by two pixels within a collimator unit in the event of misalignment of the X-ray source.
FIG. 17 is a schematic diagram illustrating an example of a periodic signal that may be obtained by a detector in the event of source misalignment at the proposed geometry.
FIG. 18 is a schematic flow chart diagram illustrating an example of a method for managing geometric misalignments in an X-ray imaging system.
FIG. 19 is an example of the sensitivity of different energy bins of a silicon detector having 8 energy bins, some of which are substantially monochromatic and others of which are polychromatic.
FIG. 20 is a schematic flow chart diagram showing an example of the steps of calibrating a substantially monochromatic energy bin.
Fig. 21 is a schematic diagram illustrating an example of computer implementation according to an embodiment.
Detailed Description
FIG. 18 is a schematic flow chart diagram illustrating an example of a method for managing geometric misalignments in an X-ray imaging system having: an X-ray source, a photon counting X-ray detector, and an intermediate collimator structure in the X-ray path between the X-ray source and the X-ray detector.
Typically, the X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1.
In a particular example, N ≧ 2 and M ≧ 2.
Basically, the method comprises:
s1: monitoring output signals of pixels from a specified subset of pixels for a specified subset of pixels comprising at least two pixels which are differently affected by shadows from the collimator structure due to the geometric misalignment; and
s2: the occurrence of the geometric misalignment is determined based on the monitored output signals from the pixels of the specified subset of pixels.
For example, at least two pixels have different responses to shading, and the different responses are monitored by measuring the output signal.
As an example, the method further comprises i) estimating at least one parameter indicative of the geometric misalignment and/or ii) correcting the geometric misalignment based on monitored output signals from pixels of the specified subset of pixels and/or iii) performing post-processing of the output signals and/or iv) reconstructing the image based on the parameter indicative of the geometric misalignment and/or based on monitored output signals from pixels of the specified subset of pixels.
In a particular example, an effect of the geometric misalignment on an output signal of at least one pixel or on a value based on the output signal is corrected based on the monitored output signals of pixels from the specified subset of pixels.
For example, during image acquisition, at least one pixel to be corrected is located behind the object/subject to be imaged.
Preferably, the output signal from the pixel represents a photon count of the pixel.
In a particular example, the output signals from the pixels of the specified subset of pixels are measured during image acquisition of the object/subject and are located outside the object/subject to be imaged during the measurement.
For example, at least two pixels differently affected by the shadow are positioned relative to the collimator structure such that they experience a different shadow than the collimator structure due to the geometric misalignment.
For example, the at least two of the pixels that are differently affected by the shadow may include a first subset of one or more pixels that has an increase in the number of photon counts due to the shadow and a second subset of one or more pixels that has a decrease in the number of photon counts due to the shadow.
In a particular example, each collimator element has a first side and an opposite second side, and at least one of the pixels of the specified subset is located on the first side of the collimator element and at least one of the pixels of the specified subset is located on the opposite second side of the same or another collimator element.
For example, the X-ray detector comprises a plurality of detector modules, and the pixels located on opposite sides of the collimator unit belong to different detector modules of the X-ray detector.
In a typical example, the geometric misalignment may comprise a relative geometric misalignment between the X-ray source and the X-ray detector.
For example, the direction and/or extent of pixel shading caused by geometric misalignment may be determined based on monitored output signals from pixels of a specified subset of pixels.
In a particular embodiment, the X-ray detector is a photon counting and energy discriminating X-ray detector, and the effect of the geometric misalignment on the photon count of at least one of said pixels is corrected based on the monitored output signals of the specified subset of pixels or based on the values of the output signals of the pixels of the specified subset of pixels and the related photon energy information obtained from the photon counting and energy discriminating X-ray detector.
For example, a photon counting and energy discriminating X-ray detector may be configured to divide detected photons into energy bins, and the step of correcting for the effect of geometric misalignment on photon counting may comprise: correcting photon counts in energy bins of at least one of the pixels based on the monitored photon counts of pixels of the designated subset of pixels and the associated photon energy information.
Optionally, the correction factor may be determined based on at least one parameter indicative of the geometric misalignment and the base material thickness.
For example, a correction factor may be determined and applied to the photon counts in the lower energy bins.
In another example, geometric misalignment can be distinguished from a drop in the current-peak-kilovoltage ratio (mA/kVp) of the X-ray source based on the monitored output signals of the pixels of the designated subset of pixels.
Typically, the management of the geometric misalignment may comprise, for example, supervision and/or handling of the geometric misalignment, e.g. monitoring and/or correction/calibration of the geometric misalignment.
For a better understanding, the technique will now be described with reference to non-limiting examples.
In some aspects, a method and corresponding embodiments are provided for geometric calibration of an energy-discriminating photon counting X-ray detector system. In a particular embodiment, the method is based on having several detector pixels within the collimator unit, monitoring the change in measurement counts in pixels outside the imaging subject, and using this information to correct measurements performed by pixels located behind the imaging subject.
In the same or other aspects, the invention relates to the management of the effects of geometric misalignments of an X-ray tube and an X-ray detector, and comprises the following methods: 1) estimate a relative geometric alignment between the X-ray tube and the detector based on measurements taken by photon counts located outside the imaging subject and pixels on the spectral detector, and 2) correct output signals from detector pixels located behind the imaging subject based on the estimate of the relative geometric alignment between the X-ray tube and the detector.
Referring to the drawings, x, y and z directions are defined as the same as a common CT system, wherein the x direction is a rotating direction of a rack; the y-direction is the X-ray beam direction; the z direction is the layer direction (system axis).
Errors in the signal output from a detector pixel, such as photon counting, may result from unattenuated X-ray beam quality or dynamic changes in the response function of the detector pixel. The response function of a detector pixel is defined herein as the output signal given an input signal, e.g., the average number of counts recorded in each energy bin when the pixel is illuminated by N photons of a particular energy.
Sources of unattenuated X-ray beam quality variation include, but are not limited to: drift in X-ray tube current (mA) and drift in X-ray tube acceleration voltage (kVp). Sources of variation in the detector response function include, but are not limited to, drift in the energy threshold and variation in the relative geometric alignment of the X-ray tube and detector. The reconstructed image may contain artifacts, such as fringes or rings, if the signals output from the pixels behind the object are not corrected for variations in the quality of the unattenuated X-ray beam and/or variations in the response function of the detector pixels.
During CT image acquisition, the measurement signals in the pixels located behind the imaging object naturally change over time due to the relative rotation of the object and the detector/source. This means that fluctuations in the measurement count due to variations in the detector response function are difficult to detect. However, many misalignments (e.g. movement of the X-ray tube focus or movement of the detector) may affect the entire detector at the same time. This means that detector pixels located outside the imaging subject can be used to monitor the movement of the source relative to the detector as long as the pixels located outside the imaging subject are sensitive to misalignment.
In the disclosed invention, sensitivity to misalignment is achieved by having multiple pixels inside each collimator unit. In other words, the collimator structure comprises a plurality of collimator units, wherein each of the at least one subset of collimator units corresponds to an N × M matrix of pixels, wherein at least one of N and M is larger than 1. This type of collimator is sometimes referred to as a multi-pixel matched collimator.
In a particularly practical example, N ≧ 2 and M ≧ 2.
Fig. 12 is a schematic diagram showing an example of the proposed geometry between an object collimator (usually called collimator structure 22) and a flat detector viewed from the y-direction, wherein the
Fig. 13 is a schematic diagram showing an example of a y-direction view of the proposed geometry between the
For an edge X-ray detector having a
In the example in question, there is an N × M matrix of pixels matching each of at least a subset of the collimator elements.
In the following, non-limiting examples of collimator geometries for edge photon counting detectors will be described for minimizing shadow effects due to misalignment.
For example, a collimator structure may be provided in which the collimator lamellae in the wafer direction are extensions of the sheet of attenuating material located between the detector wafers, wherein the portion of attenuating material located above the detector wafers has a greater thickness than the portion of attenuating material located between the wafers. The benefit of this configuration is that the thicker attenuating material above the wafer blocks radiation that might otherwise have impinged on the sides of the wafer (it is desirable that all of the radiation pass/enter the edge of the wafer in order to obtain a uniform detector response). Avoiding X-rays striking the wafer side reduces the sensitivity to misalignment. For example, if an X-ray impinges on the side of the wafer, there will be a greater number of detected X-rays since the unattenuated X-ray beam impinges directly on a large area of the wafer side; and if the alignment changes such that the side of the wafer is no longer illuminated, the number of detected photons will be greatly reduced, leading to more difficult calibration problems.
Fig. 14 is a schematic diagram showing an example of a view from the z-direction for a proposed geometry between an object collimator and a flat detector, where the collimator unit corresponds to two detector pixels in one direction (such as shown in fig. 13).
In other words, an X-ray detector is provided comprising a plurality of
For example, the collimator lamellae and the X-ray attenuating structures located between the edge detector modules may be connected to, integrated with or integrated with each other.
For example, the X-ray attenuating structure may comprise at least one X-ray attenuating plate, such as a tungsten plate or an anti-scatter foil.
In a particular example, the
Fig. 15 is a schematic diagram showing an example of an X-ray detector with a
In this example, the X-ray detector comprises a plurality of edge detector modules arranged side by side and adapted to be oriented towards an edge of the X-ray source, each edge detector having at least one detector pixel. The X-ray detector further comprises a
Typically, the edge detector module has a lateral and a longitudinal extension, and for example, collimator lamellae of collimator units orthogonal to the longitudinal extension of the detector module may be arranged offset with respect to pixel boundaries.
In other words, the proposed examples of geometries relate to collimator structures with collimator units, where collimator lamellae orthogonal to the wafer are located within the detector pixels (not on the pixel boundaries). This is beneficial for managing misalignments, since the shadow from the collimator sheet will always be located within the same pixel and will not switch from one pixel to another. Moreover, the spectral distortion due to the shadow will be minimal, since the profile of the shadow is approximately the same width at all depths in the detector material, which together with the shadow being located completely within one pixel means that a change in the shadow can only lead to a change in the photon flux, with a constant factor for all energies. If the collimator lamellae are placed on the boundaries between pixels, two pixels adjacent to the collimator lamellae will experience larger photon flux variations and spectral variations as a result of the misalignment.
More generally, pixels located on different sides of the collimator sheet will be sensitive to misalignments in different directions, i.e. if the source moves, some pixels will be reacted by fewer photons by the detector and some pixels will be reacted by more photons by the detector this is shown in fig. 16, where misalignment with respect to the X-ray direction and angle "a" results in less illumination of pixel a and more illumination in pixel B fig. 17 shows that the whole detector is affected by the geometric misalignment this effect can be seen in many pixels at the same time this effect can then be estimated by e.g. monitoring the ratio of the counts recorded on either side of the collimator sheet the position of the X-ray source is then estimated by e.g. monitoring the ratio of the counts at the alignment position two pixels are equal in number (if the gain difference has been calibrated) because they are fully illuminated and at the misalignment position the height and shadow degree of the collimator can be used to calculate the angular misalignment.
In other words, for each measurement or set of measurements, the detection signal from a specified set of reference pixels located outside the imaging subject is monitored and the obtained signal is used to determine the occurrence of geometric misalignment. The requirement for the reference pixel sets is that they contain pixels with different responses to shading, i.e. a subset of pixels measures an increase in the number of counts as a result of shading, while another subset of pixels measures a decrease in the number of counts as a result of shading. In order to distinguish shadows from, for example, drifts in the current (mA) of the X-ray tube or the acceleration voltage (kVp) of the X-ray tube, a different response is required.
The drift in the X-ray tube current (mA) results in an equal increase in the number of counts for all energy bins and pixels. If the shading changes, each pixel and energy bin may experience a different change in the number of enrollment counts. If all pixels respond to the shadow in the same way (i.e., all increases or all decreases), the shadow cannot be easily distinguished from, for example, a mA drift, because all pixels and energy bins will have components in the same direction, which may be mistaken for a mA drift.
In the disclosed invention there is no need to monitor the misaligned dedicated pixels (as is the case when using a deliberately misaligned collimator sheet or pixel mask). If all pixels on the detector are outside the imaged object at the time of estimation, they can in principle be used to estimate the alignment. It is easy to estimate from the acquired CT sinogram data whether a pixel is located outside the imaged object, since the contour of the object is easily identifiable.
Once the position of the X-ray tube relative to the detector/collimator has been estimated, the obtained estimate can be used for example:
1) correcting measured X-ray counts in pixels located behind an object
2) A set of geometric parameters that can be used as an input for image reconstruction is estimated.
Depending on the geometry of the collimator, it may be desirable to use a spectral photon counting detector. For the geometry shown in fig. 13, it is desirable that the detector is spectral (and photon counting) in order to be able to perform 1), i.e. correct the measurement signal in the pixel behind the object. This may not be necessary for the geometry shown in fig. 15. The pixel to be corrected will be referred to as a target pixel.
An example of a method of correcting the number of counts in an energy bin of a target pixel (a detector pixel located behind an imaging subject) is given herein. First, two types of energy bins are identified: monochromatic and polychromatic. The monochromatic energy bins are sensitive only over a narrow energy range. For example, only photons with energies between 50keV and 60keV can produce counts in the energy bins. Polychromatic energy bins are sensitive over a wide range of energies, e.g., photons with energies between 10keV and 120keV can produce counts in the energy bins. For example, for a silicon-based photon-counting spectral detector, the highest energy threshold is substantially monochromatic, while the lower energy bins are polychromatic due to their sensitivity to compton scattering events (higher energy photons deposit only a fraction of their energy).
Fig. 19 is a schematic diagram showing an example of the sensitivity of different energy bins (the energy distribution that produces a counted photon in each pixel) of a silicon photon counting detector. In the example of fig. 19, the energy bins 4 to 8 have very narrow sensitivity regions and therefore behave as if they are monochromatic, i.e. the response to shading is independent of the input spectrum. On the other hand, the lower energy bins have a wide energy response and must be considered polychromatic.
The correction factors for the monochromatic energy bins are independent of the input spectrum of the target pixel, making them easy to correct. The correction factor may be determined by establishing a direct relationship between the counts in a bin of the target pixel and the corresponding bin of pixels in the specified reference set. The relationship between the count in the target pixel and the specified subset of pixels can be established, for example, by performing a set of reference measurements during which a typical misalignment occurs. Typical misalignments may be obtained by natural movement of the detector/source system or by intentional movement of the focal spot and/or the detector. FIG. 20 shows a flow chart for performing calibration of a monochromatic energy bin.
The correction factors for the multi-color energy bins depend largely on the input spectrum of the target pixel and different methods must be taken to calculate the correction factors for the multi-color energy bins. The following is an example of a step-by-step method for performing first order correction on the enrollment counts in a multi-color energy bin of knowledge about the input spectrum required to perform the correction:
1) the current degree of shading is estimated from the reference pixels.
2) A material basis decomposition is used to estimate the thickness of the basis material in the path of the X-ray beam that strikes the target pixel. (this estimate will have a slight deviation, the objective being to eliminate the deviation).
3) The estimated base material thickness and the detector response model are used to estimate the input spectrum of the pixel (here also the bias).
4) The estimated degree of shading (α) is used along with the estimated input spectrum to calculate a correction factor for the registered number of counts in the lower energy bins of the target pixel using a detector forward model.
5) Re-decomposition of material basis using corrected counts
Another method of calculating the correction factor is to use a look-up table that directly relates the correction factor to the base material thickness. In this case, it is not necessary to perform an intermediate step of estimating the input spectrum each time the correction factor is to be estimated. Each entry in the lookup table will then contain the correction factors for all energy bins for a particular set of base material thicknesses.
The correction may be performed iteratively, as the estimation of the base material thickness performed using the corrected counts may be used to estimate a new set of correction factors. The new correction factor will be more accurate than the first correction factor because the estimate of the base material thickness will be more accurate. The process may be repeated until convergence.
It should be understood that the methods and apparatus described herein may be combined and rearranged in various ways.
For example, certain functions may be implemented in hardware or software executed by suitable processing circuitry, or a combination thereof.
The steps, functions, procedures, modules and/or blocks described herein may be implemented in hardware using any conventional technology, such as semiconductor technology, discrete circuit or integrated circuit technology, including both general purpose electronic circuitry and application specific circuitry.
Particular examples include one or more suitably configured digital signal processors and other known electronic circuitry, such as discrete logic gates interconnected to perform a dedicated function, or Application Specific Integrated Circuits (ASICs).
Alternatively, at least some of the steps, functions, procedures, modules and/or blocks described herein may be implemented in software, such as a computer program, for execution by suitable processing circuitry, such as one or more processors or processing units.
Examples of processing circuitry include, but are not limited to, one or more microprocessors, one or more Digital Signal Processors (DSPs), one or more Central Processing Units (CPUs), video acceleration hardware, and/or any suitable programmable logic circuitry, such as one or more Field Programmable Gate Arrays (FPGAs) or one or more Programmable Logic Controllers (PLCs).
It will also be appreciated that the general processing power of any conventional device or unit in which the proposed techniques are implemented may be reused. Existing software may also be reused, for example by reprogramming the existing software or by adding new software components.
According to one aspect, there is provided a system configured for managing geometric misalignments in an X-ray imaging system having an X-ray source, a photon counting X-ray detector, and an intermediate collimator structure on an X-ray path between the X-ray source and the X-ray detector.
The X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. For example, N.gtoreq.2 and M.gtoreq.2.
The system is configured to monitor output signals of pixels from a specified subset of pixels for the specified subset of pixels comprising at least two pixels which are differently affected by shadows from the collimator structure due to geometric misalignment. The system is further configured to determine an occurrence of geometric misalignment based on the monitored output signals from the pixels of the specified subset of pixels.
For example, the at least two pixels have different responses to the shadow, and the system is configured to monitor the different responses by measuring the output signal.
For example, the system may be configured to estimate at least one parameter indicative of the geometric misalignment and/or to correct the geometric misalignment based on monitored output signals from pixels of the specified subset of pixels and/or iii) to perform post-processing of the output signals and/or iv) to perform image reconstruction based on the parameter indicative of the geometric misalignment and/or based on monitored output signals from pixels of the specified subset of pixels.
According to another aspect, there is also provided an X-ray imaging system comprising a system for managing geometric misalignments as described herein.
Fig. 21 is a schematic diagram illustrating an example of computer implementation according to an embodiment. In this particular example, the
The term "processor" should be interpreted in a generic sense as any system or device capable of executing program code or computer program instructions to perform a particular processing, determining, or computing task.
Thus, a processing circuit comprising one or more processors is configured to perform well-defined processing tasks such as those described herein when executing a computer program.
The processing circuitry need not be dedicated to performing only the above-described steps, functions, procedures and/or blocks, but may also perform other tasks.
The proposed technology also provides a computer-
By way of example, software or
As an example, a computer program product comprising a computer readable medium having stored thereon a computer program for managing geometrical misalignments in an X-ray imaging system having an X-ray source, a photon counting X-ray detector and an intermediate collimator structure in an X-ray path between the X-ray source and the X-ray detector, when executed by a processor, is provided. The X-ray detector comprises a plurality of pixels and the collimator structure comprises a plurality of collimator units, wherein each of at least a subset of the collimator units corresponds to an N X M matrix of pixels, wherein at least one of N and M is larger than 1. For example, N.gtoreq.2 and M.gtoreq.2.
The computer program includes instructions that, when executed by the processor, cause the processor to:
-monitoring output signals of pixels from a specified subset of pixels for a specified subset of pixels comprising at least two pixels, at least two of said pixels being affected differently by shadows from the collimator structure due to geometrical misalignment; and
-determining an occurrence of a geometric misalignment based on the monitored output signals from the pixels of the specified subset of pixels.
The method flows presented herein may be considered as a computer action flow when executed by one or more processors. A respective device, system, and/or apparatus may be defined as a set of functional modules, wherein each step performed by a processor corresponds to a functional module. In this case, the functional modules are implemented as computer programs running on a processor. Thus, a device, system and/or apparatus may alternatively be defined as a set of functional modules, wherein the functional modules are implemented as computer programs running on at least one processor.
The computer program residing in the memory may thus be organized into suitable functional modules configured to perform at least a portion of the steps and/or tasks described herein when executed by the processor.
Alternatively, the modules may be implemented primarily by hardware modules or alternatively by hardware. The scope of software versus hardware is purely an implementation choice.
The above embodiments are given by way of example only and it should be understood that the proposed technology is not limited thereto. Those skilled in the art will appreciate that various modifications, combinations and changes may be made to the embodiments without departing from the scope of the invention, which is defined by the appended claims. In particular, the different partial solutions in the different embodiments can be combined in other configurations, where technically possible.
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