Patent Application
20160217594
1. Field
This disclosure relates to decomposing spectral computed tomography (CT) projection data into basis-material components, and more particularly using a cost function and global optimization to solve for the basis-material components.
2. Description of the Related Art
Computed tomography (CT) systems and methods are widely used, particularly for medical imaging and diagnosis. CT systems generally create images of one or more sectional slices through a subject's body. A radiation source, such as an X-ray tube, irradiates the body from one side. A collimator, generally adjacent to the X-ray source, limits the angular extent of the X-ray beam, so that radiation impinging on the body is substantially confined to a planar region defining a cross-sectional slice of the body. At least one detector (and generally many more than one detector) on the opposite side of the body receives radiation transmitted through the body substantially in the plane of the slice. The attenuation of the radiation that has passed through the body is measured by processing electrical signals received from the detector.
Conventionally energy-integrating detectors have been used to measure CT projection data. Now, recent technology developments are making photon-counting detectors a feasible alternative to conventional energy-integrating detectors. Photon-counting detectors have many advantages including their capacity for performing spectral CT. To obtain the spectral nature of the transmitted X-ray data, the photon-counting detectors split the X-ray beam into its component energies or spectrum bins and count a number of photons in each of the bins. Since spectral CT involves the detection of transmitted X-rays at two or more energy levels, spectral CT generally includes dual-energy CT by definition.
Photon-counting detectors use semiconductors with fast response times compared to indirect detectors, such as scintillating crystals coupled to optical detectors (e.g., photo-multiplier tubes or avalanche photodiodes) to detect resultant scintillation photons. This fast response time enables photon-counting detectors to resolve in time individual X-ray detection events. However, at high X-ray flux rates indicative of clinical X-ray imaging, multiple X-ray detection events on a single detector can occur within the detector's time response—a phenomenon called pileup.
Semiconductor-based photon-counting detectors used in spectral CT can detect incident photons and measure photon energy for every event. However, due to the interaction depth and ballistic deficit, the measured photon energy cannot be related to incident photon energy uniquely. At high flux, pulse pileup may also result in lost counts.
Left uncorrected, pileup, detector nonlinearities, and other artefacts of the projective imaging process can degrade reconstructed images from photon-counting detectors. On the other hand, when these effects are corrected for or calibrated out of the data, spectral CT has many advantages over conventional CT. Many clinical applications can benefit from spectral CT technology, including improved material differentiation and beam hardening corrections. Moreover, compared with non-spectral CT, spectral CT extracts complete tissue characterization information from an imaged object.
Semiconductor-based photon counting detectors (PCDs) are promising candidates for spectral CT, capable of providing better spectral information compared with conventional spectral CT technology (e.g., dual-source, kVp-switching, etc.)
One challenge to more effectively using semiconductor-based photon counting detectors for spectral CT is performing the material decomposition from the projection data in a robust and efficient manner.
A more complete understanding of this disclosure is provided by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:
In one embodiment, there is provided an apparatus, comprising processing circuitry configured to (1) obtain projection data having a plurality of energy components, wherein the projection data represents an intensity of radiation having been transmitted through an imaged object and then detected at a plurality of detector elements; (2) calculate a cost function representing differences between the projection data and calculated data over the plurality of energy components, wherein the calculated data represents intensity of radiation transmitted through the imaged object, the calculated data being calculated using a detector model that approximates attenuation of the radiation, the detector model using a plurality of projection lengths, with each projection length corresponding to a respective material model of a plurality of material models; and (3) optimize the plurality of projection lengths until the calculated cost function converges to approximate a global minimum of the cost function.
In another embodiment, there is provided an apparatus, comprising: (1) an X-ray source radiating X-rays; (2) a plurality of detector elements each configured to detect a plurality of energy components of the X-rays that are radiated from the X-ray source and generate projection data; and (3) processing circuitry configured to (a) obtain the projection data having the plurality of energy components, wherein the projection data represents an intensity of radiation having been transmitted through an imaged object and then detected at the plurality of detector elements, (b) calculate a cost function representing differences between the projection data and calculated data over the plurality of energy components, wherein the calculated data represents intensity of radiation transmitted through the imaged object, the calculated data being calculated using a detector model that approximates attenuation of the radiation, the detector model using a plurality of projection lengths, with each projection length corresponding to a respective material model of a plurality of material models, and (c) optimize the plurality of projection lengths until the calculated cost function converges to approximate a global minimum of the cost function.
In another embodiment, there is provided a method, comprising: (1) obtaining projection data having a plurality of energy components, wherein the projection data represents an intensity of radiation having been transmitted through an imaged object and then detected at a plurality of detector elements; (2) calculating a cost function representing differences between the projection data and calculated data over the plurality of energy components, wherein the calculated data represents intensity of radiation transmitted through the imaged object, the calculated data being calculated using a detector model that approximates attenuation of the radiation, the detector model using a plurality of projection lengths, with each projection length corresponding to a respective material model of a plurality of material models; and (3) modifying the plurality of projection lengths until the calculated cost function converges to approximate a global minimum of the cost function.
In spectral CT, radiation having multiple energy components is used to make projective measurements of an object OBJ. These projective measurements are made at a series of angles enabling conventional CT image reconstruction methods similar to non-spectral CT. However, unlike non-spectral CT, spectral CT generates additional information that allows a decomposition of the projective measurements into several material components, usually two in current clinical settings. The material decomposition results in two component materials because there are two major differentiable interaction mechanisms resulting in X-ray attenuation as the X-ray beam traverses the imaged object OBJ. These interaction mechanisms are Compton scattering and photoelectric absorption. Mapping the projection data from the spectral domain to the material domain can be performed either before or after the image reconstruction process. However, performing material decomposition from the spectral domain to the material domain before the reconstruction process is preferable due to beam hardening considerations. Herein, we are concerned with performing the material decomposition before the image reconstruction process.
When most of the X-rays have energies well above the K-edge of the majority atoms of the imaged object OBJ, as is the case for conventional X-ray sources imaging biological objects, the material decomposition problem can be solved using only two energy components consistent with the existence of the two dominant interaction processes discussed above. Thus, spectral CT is sometimes referred to as dual-energy CT, and the material decomposition process can be referred to as dual-energy analysis. Herein, spectral CT will include at least dual-energy CT, but also includes projective measurements with more than two energy components, such that the two-material decomposition problem is overdetermined. As discussed in U.S. patent application Ser. No. 13/906,110, incorporated herein by reference in its entirety, the additional information provided by more energy components can be used effectively in noise balancing and related methods to improve image quality.
A dual-energy analysis method can be used because the attenuation of X-rays in biological materials is dominated by two physical processes (i.e., photoelectric absorption and Compton scattering). Thus, the attenuation coefficient as a function of energy can be approximated by the decomposition
μ(E,x,y)=μPE(E,x,y)+μC(E,x,y)
wherein μPE(E,x,y) is the photoelectric attenuation and μC(E,x,y) is the Compton attenuation. Alternatively, this attenuation coefficient can be rearranged into a decomposition of a high-Z material (i.e., material 1) and a low-Z material (i.e., material 2) to become
μ(E,x,y)≈μ1(E)c1(x,y)+μ2(E)c2(x,y),
where c1(x,y) and c2(x,y) are, respectively, the first and second basis images.
Next, a detector model of semiconductor-based photon counting detectors is discussed.
As discussed in U.S. patent application Ser. No. 13/866,965, incorporated herein by reference in its entirety, the response function of the radiation detectors can be calibrated to provide improved results. In one implementation, the detector model for the number of counts of each given radiation detector is
N
m
=Tne
−nτ
∫∫dEdE
0
R
0(E,E0)S(E0)+Tn2e−nτ∫∫∫dEdE0dE1R1(E,E0,E1)S(E0)S(E1),
wherein each of the integrating time T, linear response function R0, nonlinear response function R1, and dead time τ are known for each radiation detector and energy component as a result of calibrations performed before the projective measurements on object OBJ. In the above nonlinear detector model only the first order nonlinear term is included. Generally, higher order nonlinear terms can also be included in the detector model for the number of counts. Each integral is integrated over the spectral range for the mth energy bin. Thus, there is a unique count Nm for each energy bin/component of each detector.
The detected spectrum is given by
S(Ei)=Sair(Ei)exp[−μ1(Ei)L1−μ2(Ei)L2],
where the attenuation coefficients μ1 and μ2 are known functions of the X-ray energy, and the spectrum in the absence of an object OBJ (designated by Sair) is also known.
Similarly, the X-ray flux n for each detector is given by
n=n
air
∫dE
0
S(E0)exp[−μ1(E0)L1−μ2(E0)L2],
where nair is known. In one implementation, which is discussed more completely in U.S. patent application Ser. No. 14/103,137, incorporated herein by reference in its entirety, the value of nair is given by
n
air
=A·I
ref,
where A is a calibration term unique to each detector that is determined before the projective measurements on object OBJ, and Iref is the reference detector signal.
Referring now to the drawings, wherein like reference numerals designate identical or corresponding parts throughout the several views,
The first step S110 of method 100 is to calculate a cost function φ(L1,L2). This cost function combines the measured projection data N′m with corresponding calculated values Nm obtained from the detector model previously discussed. As shown in
Several different cost functions (L1,L2) are possible. In one implementation, the cost function is the least squares of the difference between the measured counts N′m and the calculated counts Nm, i.e.,
φ(L1,L2)=Σ(N′m−Nm)2.
In one implementation, the cost function is the weighted least squares of the difference between the measured counts N′m and calculated counts Nm, i.e.,
where σm is the standard deviation of N′m.
In one implementation, the cost function is the Poisson likelihood function, i.e.,
φ(L1,L2)=Σ[N′m log(Nm)−Nm].
After computing the cost function in step S110, the method 100 proceeds to process 120 in which an optimization method is performed to find the minimum of the cost function. When the cost function has local minima that are different from the global minimum, a robust stochastic optimization process is beneficial to find the global minimum of the cost function.
In one implementation, the method shown in
Following step S210, the process 120 proceeds to step S220, wherein a new sample point L′ is randomly selected from the sample space surrounding the current set of projection lengths L(n-1)=(L1(n-1),L2(n-1)).
Proceeding to step S230, the process 120 inquiries as to which of value of the cost function φ(L(n-1))) or φ(L′) is smaller. In steps S240 and S250 the argument corresponding to the smaller value of the cost function is assigned as the next set of projection lengths L(n)=(L1(n)),L2(n)) for the next loop iteration.
Step S260 of process 120 evaluates whether the loop stopping criteria is satisfied. Although different stopping criteria can used,
In one implementation, the method 100 will be used with coarse searching criteria. For example, in the case that a grid of cost function values are pre-computed and assembled into a lookup table, then spacing of the grid for pre-computing cost function values will have a large spacing between the adjacent projection lengths that determine the grid of pre-computed cost function values. Alternatively, if the process shown in
In one implementation, a global minimum search using method 100 with coarse search criteria is used for an initial search to find the approximate neighborhood of a global minimum. Then, following a coarse global search, a fine search using fine search criteria is used to refine the rough approximation of the global minimum obtained using the coarse global search. The fine search uses the final value of the coarse search as its starting value of the fine search.
By using a coarse global search with search criteria sufficient to find a small enough neighborhood of the global minimum that also includes local minima that are not the global minima, the fine search succeeding the coarse search does not need to be robust to the global optimization problem (i.e., a local optimization method should be adequate for the second search). Therefore, the fine search can use a local minimum optimization method and does not need to use a global optimization method, which global optimization method often converge more slowly than local optimization methods.
In one implementation, the second search can be performed using method 100. In an alternative implementation, the second search can be performed using a detector model method to find the projection lengths, such as the detector model discussed above and the detector model discussed in U.S. patent application Ser. No. 13/866,965. In another alternative implementation, iterative searches for the global minimum can be performed using different cost functions, where presumably the projection lengths corresponding to the global minimum are approximately the same for each cost function, but the projection lengths are different for purely local minima corresponding to different cost functions. Thus, finding a minimum that is simultaneously a minimum for multiple cost functions will more robustly enable the optimization to iterate to a true global minimum and avoid iterating to a purely local minimum of any one cost function. A local minimum is the smallest value of the function over a limited range, and a global minimum is the smallest value of the function over the entire range of the function.
Next, at step 414, a global optimization step updates the value of the projection lengths L(n) in such a manner that the projection lengths L(n) converge towards a global minimum of the cost function φ(L(n)). The global optimization step can be performed according to any of the global optimization methods previously discussed herein.
Next, at step 416, the convergence criteria is evaluated, and if either the cost function φ(L(n)) falls below a predefined threshold or the maximum number of iterations nmax has been reached, then the process 410 exits the loop, returning the final value of the projection lengths L(n).
The step 422 reinitializes the error limit ε and loop variable n′. The error limit is set to a lower value ε2 than for the error limit ε1 for the global minimum optimization loop. Also, in step 422 the initial values for the projection lengths are set to the final approximation found in the global minimum optimization loop, i.e., L′(0)=L(n).
Next, each iteration of the local minimum loop 430 begins by incrementing the loop variable n′ at step 432.
At step 434, the projection lengths L′(n′) are updated in a search for the local minimum of the cost function φ(L′(n′)), where in one implementation of the method 400, the cost function φ′ used in the local minimum method 430 is different than the cost function φ used in the global minimum loop 410. In an alternative implementation of the method 400, the cost function φ′ used in the local minimum method 430 is the same as the cost function φ used in the global minimum loop 410. The method of updating the projection lengths L′(n′) can correspond to any local optimization method including: a Nelder-Mead simplex method, a gradient-descent method, a Newton's method, a conjugate gradient method, a shooting method, or other known local optimization method.
At step 436, an inquiry is made as to whether the stopping criteria have been reached.
In general, the photon-counting detectors PCD1 through PCDN each output a photon count for each predetermined energy bin. In addition to the sparse photon-counting detectors PCD1 through PCDN in the fourth-generation geometry, the implementation shown in
In one implementation, the photon-counting detectors are sparsely placed around the object OBJ in a predetermined geometry such as a circle. For example, the photon-counting detectors PCD1 through PCDN are fixedly placed on a predetermined circular component 520 in the gantry 540. In one implementation, the photon-counting detectors PCD1 through PCDN are fixedly placed on the circular component 520 at predetermined equidistant positions. In an alternative implementation, the photon-counting detectors PCD1 through PCDN are fixedly placed on the circular component 510 at predetermined non-equidistant positions. The circular component 520 remains stationary with respect to the object OBJ and does not rotate during the data acquisition.
Each of the X-ray source 512, collimator 514, and the detector unit 503 rotate around the object OBJ while the photon-counting detectors PCD1 through PCDN are stationary with respect to the object OBJ. In one implementation, the X-ray source 512 and collimator 514 are mounted on a first rotating portion 510 such as the annular frame in the gantry 540 so that the X-ray source 512 projects X-ray radiation with a predetermined source fan beam angle θA towards the object OBJ while the X-ray source 512 rotates around the object OBJ inside the sparsely placed photon-counting detectors PCD1 through PCDN. Furthermore, a detector unit 503 is mounted on a second rotating portion 530. The rotating portion 530 mounts the detector unit 503 at a diametrically opposed position from the X-ray source 512 across the object OBJ and rotates outside the stationary circular component 520.
In one implementation, the X-ray source 512 optionally travels a helical path relative to the object OBJ, which is moved in a predetermined direction that is perpendicular to the rotational plane of the rotating portion 510.
As the X-ray source 512 and the detector unit 503 rotate around the object OBJ, the photon-counting detectors PCDs and the detector unit 503 respectively detect the transmitted X-ray radiation during data acquisition. The photon-counting detectors PCD1 through PCDN intermittently detect the X-ray radiation that has been transmitted through the object OBJ and individually output a count value representing a number of photons, for each of predetermined energy bins. On the other hand, the detector elements in the detector unit 503 continuously detect the X-ray radiation that has been transmitted through the object OBJ and output the detected signals as the detector unit 503 rotates. In one implementation, the detector unit 503 has densely placed energy-integrating detectors in predetermined channel and segment directions on the detector unit surface.
In one implementation, the X-ray source 512, the photon-counting detectors and the detector unit 503 collectively form three predetermined circular paths that differ in radius. The photon-counting detectors are sparsely placed along a first circular path around the object OBJ while at least one X-ray source 512 rotates along a second circular path around the object OBJ. Further, the detector unit 503 travels along a third circular path. The above exemplary embodiment illustrates that the third circular path is the largest and outside the first and second circular paths around the object OBJ. Although not illustrated, an alternative embodiment optionally changes the relative relation of the first and second circular paths so that the second circular path for the X-ray source 512 is larger and outside the first circular path of the sparsely placed photon-counting detectors PCD1 through PCDN around the object OBJ. Furthermore, in another alternative embodiment, the X-ray source 512 also optionally travels on the same third circular path as the detector unit 503.
There are other alternative embodiments for placing the photon-counting detectors in a predetermined fourth-generation geometry in combination with the detector unit in a predetermined third-generation geometry in the CT scanner. Several alternative embodiments of the X-ray CT Scanner as described in U.S. Patent Publication No. 2013/0251097 A1, herein incorporated by reference in its entirety. Additional embodiments of the X-ray CT Scanner are also described in U.S. patent application Ser. No. 14/092,998, herein incorporated by reference in its entirety.
In one alternative implementation, the detector unit 503 is not present and the only detectors are the photon counting detectors.
In one implementation, the X-ray source 512, which is configured to perform a kV-switching function for emitting X-ray radiation at a predetermined high-level energy and at a predetermined low-level energy. In still another alternative embodiment, the X-ray source 512 is a single source emitting a broad spectrum of X-ray energies. In still another embodiment, the X-ray source 512 is more than a single X-ray emitter and each emitter can emit X-rays separately and emits a different spectrum of X-ray energies.
The detector unit 503 can use energy integrating detectors such as scintillation elements with photo-multiplier tubes or avalanche photo-diodes to detect the resultant scintillation photons from scintillation events resulting from the X-ray radiation interacting with the scintillator elements. The scintillator elements can include a crystalline scintillating material (e.g., NaI(Tl), CsI(Tl), CsI(Na), CsI(pure), CsF, KI(Tl), LiI(Eu), BaF2, CaF2(Eu), ZnS(Ag), CaWO4, CdWO4, YAG(Ce), Y3Al5O12(Ce), GSO, LSO, LaCl3(Ce), LaBr3(Ce), LYSO, BGO, LaCl3(Ce), LaBr3(Ce), C14H10, C14H12, and C10H8), an organic liquid scintillating material (e.g., an organic solvent with a fluor such as p-terphenyl (C18H14), PBD (C20H14N2O), butyl PBD (C24H22N2O), or PPO (C15H11NO)), a plastic scintillating material (e.g., a flour suspended in a solid polymer matrix), or other know scintillating materials.
The photon counting detectors can use a direct X-ray radiation detectors based on semiconductors, such as cadmium telluride (CdTe), cadmium zinc telluride (CZT), silicon (Si), mercuric iodide (HgI2), and gallium arsenide (GaAs). These direct X-ray detectors have much faster time response than indirect detectors. The fast time response of direct detectors enables them to resolve individual X-ray detection events with only limited pile-up even at the high X-ray fluxes typical of clinical X-ray imaging applications. The amount of energy of the X-ray detected is proportional to the signal generated at the direct detector, and the energies of detection events can be binned into a discrete number of corresponding energy bins yielding spectrally resolved X-ray projection measurements.
The CT scanner also includes a data channel that routes projection measurement results from the photon counting detectors and the detector unit 503 to a data acquisition system 576, a processor 570, memory 578, network controller 580. The data acquisition system 576 controls the acquisition, digitization, and routing of projection data from the detectors. The data acquisition system 576 also includes radiography control circuitry to control the rotation of the annular rotating frames 510 and 530. In one implementation data acquisition system 576 will also control the movement of the bed 516, the operation of the X-ray source 512 (e.g., the high voltage supplied to the X-ray source), and the operation of the X-ray detectors (e.g., gating of the X-ray detectors and their read out). The data acquisition system 576 can be a centralized system or alternatively it can be a distributed system. In an implementation, the data acquisition system 576 is integrated with the processor 570. The processor 570 performs functions including reconstructing images from the projection data, pre-reconstruction processing of the projection data, and post-reconstruction processing of the image data. The pre-reconstruction processing of the projection data can include correcting for detector calibrations, detector nonlinearities, polar effects, noise balancing, and material decomposition. Post-reconstruction processing can include filtering and smoothing the image, volume rendering processing, and image difference processing as needed. The image reconstruction process can be performed using filtered back projection, iterative image reconstruction methods, or stochastic image reconstruction methods. Both the processor 570 and the data acquisition system 576 can make use of the memory 578 to store, e.g., projection data, reconstructed images, calibration data and parameters, and computer programs.
The processor 570 can include a CPU that can be implemented as discrete logic gates, as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Complex Programmable Logic Device (CPLD). An FPGA or CPLD implementation may be coded in VHDL, Verilog, or any other hardware description language and the code may be stored in an electronic memory directly within the FPGA or CPLD, or as a separate electronic memory. Further, the memory may be non-volatile, such as ROM, EPROM, EEPROM or FLASH memory. The memory can also be volatile, such as static or dynamic RAM, and a processor, such as a microcontroller or microprocessor, may be provided to manage the electronic memory as well as the interaction between the FPGA or CPLD and the memory.
Alternatively, the CPU in the reconstruction processor may execute a computer program including a set of computer-readable instructions that perform the functions described herein, the program being stored in any of the above-described non-transitory electronic memories and/or a hard disk drive, CD, DVD, FLASH drive or any other known storage media. Further, the computer-readable instructions may be provided as a utility application, background daemon, or component of an operating system, or combination thereof, executing in conjunction with a processor, such as a Xenon processor from Intel of America or an Opteron processor from AMD of America and an operating system, such as Microsoft VISTA, UNIX, Solaris, LINUX, Apple, MAC-OS and other operating systems known to those skilled in the art. Further, CPU can be implemented as multiple processors cooperatively working in parallel to perform the instructions.
In one implementation, the reconstructed images can be displayed on a display. The display can be an LCD display, CRT display, plasma display, OLED, LED or any other display known in the art.
The memory 578 can be a hard disk drive, CD-ROM drive, DVD drive, FLASH drive, RAM, ROM or any other electronic storage known in the art.
The network controller 580, such as an Intel Ethernet PRO network interface card from Intel Corporation of America, can interface between the various parts of the CT scanner. Additionally, the network controller 580 can also interface with an external network. As can be appreciated, the external network can be a public network, such as the Internet, or a private network such as an LAN or WAN network, or any combination thereof and can also include PSTN or ISDN sub-networks. The external network can also be wired, such as an Ethernet network, or can be wireless such as a cellular network including EDGE, 3G and 4G wireless cellular systems. The wireless network can also be WiFi, Bluetooth, or any other wireless form of communication that is known.
As will be further illustrated the above described implementations are examples and additional implementation can vary from the above examples in many aspects. For example, although certain spatial relationships of the trajectories or paths are disclosed among the source 512, the PCDs and the energy integrating detector 503, the spatial relationship is relative and not limited to a particular relation as illustrated in
Now referring to
Still referring to
In certain implementations, the energy differentiating detectors PCD1 through PCDN are initially housed in the module housing of a modular retrofitting unit before the retrofitting device is placed in an existing CT scanner system. The above described modular retrofitting device is optionally used with other implementations. That is, the modular device 620 with the energy differentiating detectors is retrofitted in an existing image scanner for reconstructing an image. The image scanner rotates a radiation emitting source along a first path around a predetermined center while continuously emits energy towards an object. The image scanner optionally rotates an energy integrating detector for detecting intensity data along a second path around the predetermined center. The modular device further includes a predetermined number of energy differentiating detectors for detecting spectral data and a module housing for housing a predetermined number of the energy differentiating detectors that are fixedly placed along a third path, third path being inside the first path as the module housing is retrofitted into the existing image scanner, whereas the scanner reconstructs an image based upon the intensity data and the spectral data. The above described paths include certain predetermined trajectories such as a circumference, a helix and a polygon, but are not limited to a particular set of predetermined paths in a predetermined combination. Furthermore, the size of the modular retrofitting unit or device 620 is not necessarily limited to a gantry or a housing of the existing CT scanner system. The modular retrofitting unit or device 620 is also optionally attached to a gantry or a housing of the existing CT scanner system in a detachable or fixed manner.
In the above implementation, the PCDs are sparsely and fixedly placed along a first circular path around the object OBJ while at least one X-ray source 512 rotates along a second circular path around the object OBJ. Furthermore, the above implementation illustrates that the first circular path is smaller and inside the second circular path around the object OBJ. There are other alternative implementations for placing the PCDs in a predetermined fourth-generation geometry in the CT scanner system according to the current invention. Although it is not illustrated in a drawing, an alternative implementation optionally includes a first path that is substantially circular and also a non-circular first path such as a predetermined polygon along which the photon counting detectors PCD1 through PCDN are sparsely placed.
Again, although it is not illustrated in a drawing, an alternative implementation optionally includes more than one X-ray source 512, and a plurality of the X-ray sources 512 is mounted on the rotating portion 630 such as the annular frame at a predetermined angle with each other. At least one of the X-ray sources 512 is optionally a single energy source in certain implementations. By the same token, a second alternative implementation optionally includes the X-ray source 512, which is configured to perform a kV-switching function for emitting X-ray at a predetermined high-level energy and a predetermined low-level energy. Furthermore, the radiation emitting source or the X-ray source 512 optionally modulates a combination of a radiation energy level and an intensity level over time.
The above implementation according to the current invention also provides a protective rear cover for each of the photon counting detectors PCD1 through PCDN that are irradiated from behind in a short distance. As the X-ray source 512 travels outside the first circular path of the sparsely placed photon counting detectors PCD1 through PCDN, the photon counting detectors PCD1 through PCDN′ are protected by the protective layer from the X-ray irradiation on the rear surface in order to substantially reduce undesirable effects.
Now referring to
The implementation utilizes a combination of the two types of detectors. In general, the photon counting detectors PCD1 through PCDN are made from a device and output a photon count for each of predetermined energy components. Although approximately one hundred to three hundred photon counting detectors are utilized in certain implementations, the above numerical range of the photon counting detectors is merely exemplary, and the claimed invention is not necessarily limited to any particular number of the photon counting detectors. In addition to the sparsely placed photon counting detectors PCD1 through PCDN in the fourth-generation geometry, the implementation of
Still referring to
Both the X-ray source 512 and the detector unit 503 rotate around the object OBJ while the photon counting detectors PCD1 through PCDN remain stationary with respect to the object OBJ. In one exemplary implementation, the X-ray source 512 is mounted on a first rotating portion 730 such as the annular frame in the gantry 700 so that the X-ray source 512 projects X-ray with a predetermined source fan beam angle θA towards the object OBJ while the X-ray source 512 rotates around the object OBJ outside the sparsely placed photon counting detectors PCD1 through PCDN. Furthermore, an additional detector unit 503 is mounted on a second rotating portion 740 in the third-generation geometry in the above exemplary implementation of the CT scanner system according to the current invention. The rotating portion 740 mounts the detector unit 503 at a diametrically opposed position from the X-ray source 512 across the object OBJ and rotates outside the stationary circular component 720, on which the photon counting detectors PCD1 through PCDN are fixedly placed in a predetermined sparse manner.
In one implementation, the rotating portions 730 and 740 are integrally constructed as a single component such as the annular frame 102 to maintain the 180-degree angle between the X-ray source 512 and the detector unit 503 as they rotate about the object OBJ with a different radius. In an optional implementation, the rotating portions 730 and 740 are separate components but synchronously rotate to maintain the X-ray source 512 and the detector unit 503 in the fixedly opposed positions at 180 degrees across the object OBJ. Furthermore, the X-ray source 512 optionally travels a helical path as the object is moved in a predetermined direction that is perpendicular to the rotational plane of the rotating portion 730. Although it is not illustrated in the diagram, the rotating portions 730 and 740 are reversed in their diameters in another alternative implementation. That is, although the source 512 and the detector unit 503 travel outside the sparsely placed photon counting detectors PCD1 through PCDN, the source 512 has a trajectory that is inside that of the detector unit 503 in the alternative implementation while they travel at a diametrically fixed position with each other.
In the above exemplary implementation, the X-ray source 512, the photon counting detectors (PCD) and the detector unit 503 collectively form three predetermined circular paths that differ in radius. The PCDs are sparsely placed along a first circular path around the object OBJ while at least one X-ray source 512 rotates along a second circular path around the object OBJ. Further, the detector unit 503 travels along a third circular path. The above exemplary implementation illustrates that the second circular path is the largest and outside the first and third circular paths around the object OBJ. Although it is not illustrated in, yet another alternative implementation optionally changes the X-ray source 512 to travel on the same third circular path as the detector unit 503. There are other alternative implementations for placing the PCDs in a predetermined fourth-generation geometry in combination with the detector unit in a predetermined third-generation geometry in the CT scanner system according to the current invention. The X-ray source 512 is optionally a single energy source in certain implementations. By the same token, an additional alternative implementation optionally includes the X-ray source 512, which is configured to perform a kV-switching function for emitting X-ray at a predetermined high-level energy and a predetermined low-level energy. Furthermore, the radiation emitting source or the X-ray source 512 optionally modulates a combination of a radiation energy level and an intensity level over time.
As the X-ray source 512 and the detector unit 503 rotate around the object OBJ, the photon counting detectors PCDs and the detector unit 503 respectively detect the transmitted X-ray during the data acquisition. The photon counting detectors PCD1 through PCDN intermittently detect with a predetermined detector fan beam angle θB the X-ray that has been transmitted through the object OBJ and individually output a number of photons for each of predetermined energy components. On the other hand, the detector elements in the detector unit 503 continuously detect the X-ray that has been transmitted through the object OBJ and output the detected energy integration signals as the detector unit 503 rotates. Although the additional characteristics of the detector elements in the detector unit 503 will be later described in details, one implementation of the detector unit 503 has densely placed energy integrating detectors in a predetermined channel and segment directions on the detector unit surface.
The above implementations according to the current invention also provide a protective rear cover for each of the photon counting detectors PCD1 through PCDN that are irradiated from behind in a short distance. As the X-ray source 512 travels outside the first circular path of the sparsely placed photon counting detectors PCD1 through PCDN, the photon counting detectors PCD1 through PCDN are protected by the protective layer from the X-ray irradiation on the rear surface in order to substantially reduce undesirable effects.
In general, the photon counting detectors PCD1 through PCDN are sparsely positioned along the circular component 720. Although the photon counting detectors PCD1 through PCDN acquire sparse view projection data, the acquired projection data is sufficient for at least dual energy reconstruction with a certain sparse view reconstruction technique. In addition, the detector unit 503 also acquires another set of projection data, and the projection data from the detector unit 503 is used to generally improve image quality. In case that the detector unit 503 consists of energy integrating detectors with anti-scatter grids, the projection data from the detector unit 503 is used to correct scatter on the projection data from the PCDs. In the above alternative implementations, the integrating detectors optionally need to be calibrated in view of X-ray transmission through the predetermined circular component 720 and some of the PCDs. In acquiring the projection data, a sampling on the source trajectory is optionally made dense in order to enhance spatial resolution.
Now referring to
As already described, approximately one hundred to three hundred photon counting detectors PCD1 through PCDN are generally utilized in certain implementations. However, the above numerical range of the photon counting detectors is merely exemplary, and the claimed invention is not necessarily limited to any particular number of the photon counting detectors. In addition to the sparse photon counting detectors PCD1 through PCDN in the fourth-generation geometry, the exemplary implementation of
Still referring to
The two pairs of the X-ray sources 512-1, 101-2 and the detector units 503-1, 503-2 rotate around the object OBJ while the photon counting detectors PCD1 through PCDN remain stationary with respect to the object OBJ. For each pair, a rotating portion 840 respectively mounts the detector units 503-1 and 503-2 at a diametrically opposed position from the X-ray sources 512-1 and 512-2 across the object OBJ and rotates outside the stationary circular component 820, on which the photon counting detectors PCD1 through PCDN are fixedly placed in a predetermined sparse manner. Furthermore, a first pair of the X-ray source 512-1 and the detector unit 503-1 is mounted in a substantially perpendicular manner with respect to a second pair of the X-ray source 512-2 and the detector unit 503-2 in the gantry 800 in the above exemplary implementation. Each of the X-ray sources 512-1 and 512-2 projects X-ray with a predetermined source fan beam angle θA towards the object OBJ while the X-ray sources 512-1 and 512-2 rotate around the object OBJ outside the sparsely placed photon counting detectors PCD1 through PCDN.
In one implementation, the rotating portions 830 and 840 are integrally constructed as a single component such as the annular frame 102 to maintain the 180-degree angle between the X-ray sources 512-1, 101-2 and the detector units 503-1, 103-2 as they rotate about the object OBJ with a different radius. In an optional implementation, the rotating portions 830 and 840 are separate components but synchronously rotate to maintain the X-ray sources 512-1, 512-2 and the detector units 503-1, 503-2 in the fixedly opposed positions at 180 degrees across the object OBJ. Furthermore, the X-ray sources 512-1 and 512-2 optionally travel a helical path as the object is moved in a predetermined direction that is perpendicular to the rotational plane of the rotating portion 830. Although it is not illustrated in the diagram, the rotating portions 830 and 840 are reversed in their diameter in another alternative embodiment. That is, although the sources 512-1, 512-2 and the detector units 503-1 and 503-2 travel outside the sparsely placed photon counting detectors PCD1 through PCDN, the sources 512-1, 101-2 have a trajectory that is outside that of the detector units 503-1 and 503-2 while they travel at a diametrically fixed position with each other.
In the above exemplary implementation, the X-ray sources 512-1, 101-2, the photon counting detectors (PCD) and the detector units 503-1, 503-2 collectively form three predetermined circular paths that differ in radius. The PCDs are sparsely placed along a first circular path around the object OBJ while the X-ray sources 512-1 and 512-2 rotate along a second circular path around the object OBJ. Further, the detector units 503-1 and 503-2 both travel along a third circular path. The above exemplary implementation illustrates that the third circular path is the largest and outside the first and second circular paths around the object OBJ. Although it is not illustrated in a drawing, yet another alternative implementation optionally changes the X-ray sources 512-1 and 512-2 to travel on the same third circular path as the detector units 503-1 and 503-2.
There are other alternative implementations for placing the PCDs in a predetermined fourth-generation geometry in combination with two sources and two detector units in a predetermined third-generation geometry in the CT scanner system according to the current invention. At least one of the X-ray sources 512-1 and 512-2 is optionally a single energy source in certain implementations. By the same token, an additional alternative implementation optionally includes the X-ray sources 512-1 and or 512-2, which are configured to perform a kV-switching function for emitting X-ray at a predetermined high-level energy and a predetermined low-level energy. Furthermore, at least one of the radiation emitting sources or the X-ray sources 512-1 and 512-2 optionally modulates a combination of a radiation energy level and an intensity level over time.
As the X-ray sources 512-1, 512-2 and the detector units 503-1, 503-2 rotate around the object OBJ, the PCDs and the detector units 503-1, 503-2 respectively detect the transmitted X-ray during the data acquisition. The photon counting detectors PCD1 through PCDN intermittently detect with a predetermined detector fan beam angle θB the X-ray that has been transmitted through the object OBJ and individually output a number of photons for each of predetermined energy components. On the other hand, the detector elements in the detector units 503-1 and 503-2 continuously detect the X-ray that has been transmitted through the object OBJ and output the detected energy integration signals as the detector units 503-1 and 503-2 rotate. Although the additional characteristics of the detector elements in the detector units 503-1 and 503-2 will be later described in details, one implementation of the detector units 503-1 and 503-2 has densely placed energy integrating detectors in a predetermined channel and segment directions on the detector unit surface.
The above implementations according to the current invention also provide a protective rear cover for each of the PCDs that are irradiated from behind in a short distance. As the X-ray sources 512-1 and 512-2 travel outside the first circular path of the sparsely placed photon counting detectors PCD1 through PCDN, the photon counting detectors PCD1 through PCDN are protected by the protective layer from the X-ray irradiation on the resurface in order to substantially reduce undesirable effects.
In general, the photon counting detectors PCD1 through PCDN are sparsely positioned along the circular component 820. Although the photon counting detectors PCD1 through PCDN acquire sparse view projection data, the acquired projection data is sufficient for at least dual energy reconstruction with a certain sparse view reconstruction technique. In addition, the detector units 503-1 and 503-2 respectively acquire another set of projection data, and the projection data from the detector units 503-1 and 503-2 is used to generally improve image quality. In case that the detector units 503-1 and 503-2 consist of integrating detectors with anti-scatter grids, the projection data from the detector units 503-1 and 503-2 is used to correct scatter on the projection data from the PCDs. In the above alternative implementations, the integrating detectors optionally need to be calibrated in view of X-ray transmission through the predetermined circular component 820 and some of the PCDs. In acquiring the projection data, a sampling on the source trajectory is optionally made dense in order to enhance spatial resolution.
While certain implementations have been described, these implementations have been presented by way of example only, and are not intended to limit the teachings of this disclosure. Indeed, the novel methods, apparatuses and systems described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods, apparatuses and systems described herein may be made without departing from the spirit of this disclosure.
