Patent Abstract:
A method and apparatus to correct for scatter in projection data by successive approximations of a primary-beam estimate and a scatter estimate. The scatter estimate is calculated by convolving a scattering function, which is a function of the primary-beam estimate, with a smoothing function that includes Rayleigh scattering and Compton scattering terms. The scattering function is greater than zero in the limit that the primary-beam estimate goes to zero. The projection data can be X-ray computed tomography projection data, and the choice of scattering function has the benefit of reducing dark-band artefacts in reconstructed computed tomography images.

Full Description:
BACKGROUND 
     Field 
     Embodiments described herein relate generally to a method of scatter correction of projection data, and more specifically to a method of scatter correction of X-ray projection data in a computed tomography scanner system. 
     Description of the Related Art 
     In general, an X-ray projection image contains many scattered radiation components. This scattered radiation greatly degrades the accuracy of a computed tomography (CT) value in three-dimensional imaging using a two-dimensional detector. A two-dimensional detector, like a flat-panel detector used in an X-ray diagnostic apparatus, uses a scattered-radiation-removing grid to suppress scattered radiation. The suppression of scattered radiation can be further improved by post processing the projection data using a scatter-correction algorithm. In an X-ray computed tomographic apparatus, a scatter-correction algorithm in conjunction with a scatter-suppressing grid yields superior images compared to scatter-suppressing grids alone because of residual scatter. Scattered radiation correction is indispensable for extracting low-contrast information, e.g., for imaging soft tissue, by using three-dimensional imaging using a two-dimensional detector. 
     In addition to the examples given above that discuss scatter scatter-suppressing grids and scattered radiation correction to improve the image quality of projection images and that also discuss improving the image quality of reconstructed images obtained from computed tomography on a series of projection images at different projection angles, scatter suppression can also be important for measurement geometries other than three-dimensional CT imaging using a two-dimensional detector. For example, the concepts and methods discussed herein also apply to a measurement geometry of two-dimensional CT imaging using a one-dimensional detector. The method of scatter correction can also apply when the projection data is not used for CT reconstruction. 
     An X-ray beam in the presence of a scattering object can be modeled as a primary X-ray beam P(x, y) and a scattered X-ray beam S(x, y), wherein the projection data T(x, y) is a composite of these two:
 
 T ( x,y )= P ( x,y )+ S ( x,y ).
 
Using a forward-scatter model, the scattered radiation S(x, y) is given by
 
 S ( x,y )=SF( P ( x,y ))* G   2 ( x,y ),
 
where
 
SF( X )=− X  log( X ), and
 
 G   2 ( x,y )= A   1 exp[−α 1 ( x   2   +y   2 )]+ A   2 exp[−α 2 ( x   2   +y   2 )]
 
is a smoothing function that is a double Gaussian kernel with one term representing the coherent (Rayleigh) scattering and the other term representing the incoherent (Compton) scattering. The symbol “*” represents a convolution operator. The term with the coefficient A 1  is obtained by modeling Rayleigh scattering, and the term with the coefficient A 2  is obtained by modeling Compton scattering. In addition to expressing the physics of Rayleigh and Compton scattering, the double Gaussian kernel also expresses factors such as the geometry of the imaging device and the effectiveness of the scatter-suppressing grids. For example, the values of α 1  and α 2  depend on the aspect ratio of the scatter-suppressing grids. The “aspect ratio” is the height of the grid to its opening. In one implementation, in C-arm ASGs (anti-scatter grids) the aspect ratio can be approximately 10:1; while in diagnostic CT-scanners the aspect ratio can be approximately 30:1. These illustrative aspects ratios are non-limiting examples.
 
     Given the above expressions, the total beam T(x, y) can be directly calculated from a known primary beam P(x, y), but it is impossible to analytically calculate the primary beam P(x, y) from a known total beam T(x, y). A conventional technique, therefore, calculates an estimate of the primary beam P g  (x, y) by minimizing
 
 E=|T ( x,y )− T   g ( X,y )|
 
using a successive approximation method, where T g (x, y) is a composite image calculated based on P g (x, y), and can be represented by
 
 T   g ( x,y )= P   g ( x,y )+ S   g ( x,y ),
 
where S g (x, y)=−P g (x, y) log P g (x, y)*G 2  (x, y), as discussed in U.S. Pat. No. 7,912,180, the contents of which are incorporated herein by reference.
 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       A more complete appreciation of the invention and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein: 
         FIG. 1  shows a flow diagram of an implementation of a scatter-correction method; 
         FIG. 2  shows a schematic of an implementation of a computed tomography system; 
         FIG. 3  shows an implementation of a computed tomography system; 
         FIG. 4  shows a plot of a novel scattering function; and 
         FIG. 5  shows a schematic diagram of an implementation of scattered radiation correction circuitry; and 
         FIG. 6  shows a schematic of an implementation of a computed tomography system including both energy integrating detectors and photon-counting detectors. 
     
    
    
     DETAILED DESCRIPTION 
     In one embodiment, there is provided an apparatus for scatter correction of projection data, the apparatus comprising processing circuitry configured to: (1) calculate a primary-beam estimate P n , and (2) calculate a scatter estimate S n  using a convolution between a scattering function, SF(P n ), and a smoothing function G, wherein P n  is a current primary-beam estimate, S n  is a current scatter estimate, and SF(P n ) is a predetermined scatter function that is a function of the current the primary-beam estimate and is greater than zero over the range 0≦P n &lt;1. 
     In another embodiment, the processing circuitry is further configured calculate the primary-beam estimate according to 
                 P   n     =         P     n   -   1       ⁢   T         P     n   -   1       +     S     n   -   1             ,         
wherein P n-1  is a previous value of the primary-beam estimate, S n-1  is a previous value of the scatter estimate, and T is the projection data.
 
     In another embodiment, the processing circuitry is further configured to calculate the scattered estimate using the predetermined scatter function, which is given by 
               S   ⁢           ⁢     F   ⁡     (     P   n     )         =     {                 -     (       log   ⁡     (     P   1     )       +   1     )       ⁢     P   n       +     P   1               P   n     &lt;     P   1                   -     P   n       ⁢     log   ⁡     (     P   n     )                 P   n     ≥     P   1             ,             
wherein P 1  is a predefined value between zero and one.
 
     In one embodiment, the smoothing function is given by
 
 G ( x,y )= A   1 exp[−α 1 ( x   2   +y   2 )]+ A   2 exp[−α 2 ( x   2   +y   2 )],
 
wherein A 1 , α 1 , A 2 , and α 2  are predetermined values.
 
     In another embodiment, the processing circuitry is further configured to perform an iterative loop, wherein each iteration of the iterative loop includes the calculation of the primary-beam estimate and the calculation of the scatter estimate. The processing circuitry is further configured to stop the iterative loop when a predefined convergence criterion is satisfied. 
     Referring now to the drawings, wherein like reference numerals designate identical or corresponding parts throughout the several views,  FIG. 1  shows an iterative scatter correction method  100  to extract a primary beam P(x, y, θ) from projection data T(x, y, θ) in the presence of scatter S(x, y, θ). The angle θ designates the direction in which a projection measurement is made, and x and y are the locations of the detectors detecting the projection data. Absent scatter (i.e., when the primary beam P (x, y, θ) equals the projection data T(x, y, θ)) the projection data is given by
 
 T ( x,y ,θ)=∫ dEI   0 ( E )exp[−∫ dl ( x,y ,θ)μ( l,E ) l],  
 
where E is the X-ray energy, I 0 (E) is the incident intensity as a function of energy spectrum of the X-ray beam, μ(l, E) is the X-ray absorption coefficient as a function of energy E and the position l, and l(x, y, θ) is the position along the trajectory of the ray ending at the detector element at position (x, y) when the projection angle is θ. When the X-ray beam can be approximated as mono-chromatic, then the absorption can be obtained by a log-conversion step to obtain
 
∫ dlμl =−log( T/I   0 ).
 
In the context of image reconstruction, the phrase “projection data” refers to the raw data after undergoing the log-conversion step because the absorption rather than the intensity/irradiance is used for CT image reconstruction. The phrase “projection data” can also be used to describe the intensity/irradiance measurements prior to the log-conversion step, resulting in ambiguity unless the context is clearly specified in which the phrase “projection data” is used. Here, “projection data” means the intensity/irradiance measurements prior to the log-conversion because the discussion herein focuses primarily on scatter correction and focuses less on the actual image reconstruction. Here, the discussion also assumes, without loss of generality, that the primary beam P(x, y, θ), projection data T(x, y, θ), and scatter S(x, y, θ) are each normalized by the incident intensity, such that (except for the unlikely case that the imaged object exhibits gain at X-ray frequencies or the scatter exceeds absorption over some regions) each of the primary beam P(x, y, θ), projection data T(x, y, θ), and scatter S(x, y, θ) will have values between zero and one.
 
     In  FIG. 1 , the method  100  begins with step S 102  by initializing the loop variable n and initializing the scatter estimate S n (x, y, θ) and primary beam estimate P n (x, y, θ). 
     The second step S 104  of method  100  increments the loop variable n. 
     The third step S 106  of method  100  uses the previous estimates of the scatter S n-1 (x, y, θ) and the previous primary beam P n-1 (x, y, θ) to update the primary beam estimate in order to obtain the current primary beam estimate P n (x, y, θ) using the expression 
     
       
         
           
             
               
                 P 
                 n 
               
               ⁡ 
               
                 ( 
                 
                   x 
                   , 
                   y 
                   , 
                   θ 
                 
                 ) 
               
             
             = 
             
               
                 T 
                 ⁡ 
                 
                   ( 
                   
                     x 
                     , 
                     y 
                     , 
                     θ 
                   
                   ) 
                 
               
               ⁢ 
               
                 
                   
                     
                       P 
                       
                         n 
                         - 
                         1 
                       
                     
                     ⁡ 
                     
                       ( 
                       
                         x 
                         , 
                         y 
                         , 
                         θ 
                       
                       ) 
                     
                   
                   
                     
                       
                         P 
                         
                           n 
                           - 
                           1 
                         
                       
                       ⁡ 
                       
                         ( 
                         
                           x 
                           , 
                           y 
                           , 
                           θ 
                         
                         ) 
                       
                     
                     + 
                     
                       
                         S 
                         
                           n 
                           - 
                           1 
                         
                       
                       ⁡ 
                       
                         ( 
                         
                           x 
                           , 
                           y 
                           , 
                           θ 
                         
                         ) 
                       
                     
                   
                 
                 . 
               
             
           
         
       
     
     The fourth step S 108  of method  100  uses the current primary beam estimate P n (x, y, θ) to update the estimate of the scatter S n (x, y, θ) using the expression
 
 S   n ( x,y ,θ)=SF( P   n ( x,y ,θ))* G   2 ( X,y ),
 
where SF(•) is the scatter function, the symbol “*” represents a convolution operator, and
 
 G   2 ( x,y )= A   1 exp[−α 1 ( x   2   +y   2 )]+ A   2 exp[−α 2 ( x   2   +y   2 )]
 
is smoothing function that is a double Gaussian kernel with one term representing the coherent (Rayleigh) scattering and the other term representing the incoherent (Compton) scattering. The scatter function SF(•) is discussed herein with regards to  FIG. 4 .
 
     The fifth step S 110  of method  100  inquiries whether the primary beam estimate P n (x, y, θ) has converged by inquiring whether predefined convergence criteria have been satisfied. For example, the convergence criterion can be whether a Banach space distance measure of the difference between the current and previous primary beam estimates (e.g., the root mean square of the difference) is less than a predefined value. If the convergence criteria are satisfied the method  100  proceeds to step S 112 . Otherwise, the method  100  loops back to step S 104  to update the estimates of the scatter and primary beam. 
     The final step S 112  of the method  100  reports the current value of the primary-beam estimate P n (x, y, θ) as the final value of the primary beam. The current value of the scatter S n (x, y, θ) can also be reported if it is used in the image reconstruction process or in other post-processing algorithms. 
     In one implementation, for each new projection angle θ+Δθ method  100  stores the previous scatter value S prev =S n (x, y, θ) at the conclusion of the previous scatter correction calculation. The previous scatter value is then used to initiate the current scatter correction calculation S 0 (x, y, θ+Δθ)=S prev . Because the difference between projection angles will typically be small, using previous scatter value S prev  to initiate the current scatter correction calculation will often result in quicker convergence than starting each scatter correction calculation assuming no scatter, i.e., S 0 (x, y, θ+Δθ)=0 
       FIG. 2  shows an arrangement of an X-ray diagnostic apparatus  200 . The X-ray diagnostic apparatus  200  comprises a radiography gantry  202 , radiography control circuitry  204 , memory  206 , monitor  208 , input device  210 , reconstruction processing circuitry  212 , image processing circuitry  214 , and scattered radiation correction circuitry  216  that is a subset of the data pre-processing circuitry  215 , where the term “circuitry” can be interpreted as a Central Processing Unit (CPU) executing program instructions or as special-purpose hardware circuitry, such as an FPGA, or other specialized circuitry. In one implementation, the data from the X-ray diagnostic apparatus  200  can be processed approximately in chronological order with data pre-processing circuitry  215  processing the data first to prepare the data for reconstruction using computed tomography. Next, the reconstruction processing circuitry  212  operates on the pre-processed data in the projection domain to create an image expressing the absorption in each image voxel (a volume pixel). Next, the reconstructed image can be post-processed using the image processing circuitry  214  to render the image, filter/smooth the image, add false coloring to the image, etc. In one implementation, there can be overlap among the data processing between the processing of the reconstruction processing circuitry  212 , image processing circuitry  214 , and data pre-processing circuitry  215 . For example, the image processing circuitry  214  could overlap with the reconstruction processing circuitry  212 , wherein the image processing also includes additional processing steps during the CT reconstruction algorithm. 
       FIG. 3  shows a non-limiting example of the outer appearance of the radiography gantry  202 . As shown in  FIG. 3 , the radiography gantry  202  includes an X-ray tube  302 , X-ray detector  304 , C-arm  306 , stand  308 , high voltage generator  310 , bed  312 , and X-ray stop device  314 .  FIG. 3  is one example of a CT system for which the scatter correction method can be used. The scatter correction method can also be applied to other X-ray imaging geometries used for CT imaging, including diagnostic CT systems, intervention CT systems, systems using photon-integrating detectors, systems using photon-integrating detectors, cardiac, head, and full body scanners, spinning-tube CT scanners, multi-slice CT systems, for example. Furthermore, the method of scatter suppression and correction discussed herein applies also to projective measurements, such as radiographic and fluoroscopic imaging, that are not used for CT reconstruction. That is, the method of scatter suppression and correction are applicable to any X-ray projective measurements regardless of the intended use of the projective measurements, whether the projection images are an end in themselves, or they are for CT reconstruction, or they are intended for some other purpose. 
     The high voltage generator  310  generates a high voltage to be applied between the electrodes of the X-ray tube  302 , and also generates a filament current to be supplied to the cathode filament of the X-ray tube  302 . Upon receiving the high voltage and filament current, the X-ray tube  302  generates X-rays. The X-ray stop device  314  shapes X-rays generated by the X-ray tube  302 . The X-ray detector  304  can be a two-dimensional array of a plurality of detection elements (pixels) that directly or indirectly convert incident X-rays into electric charges. The X-ray tube  302  is mounted on, for example, one end of the floor type C-arm  306 . The X-ray detector  304  is mounted on the other end of the C-arm  306 . The X-ray detector  304  faces the X-ray tube  302  through an object OBJ to be examined which is placed on the bed  312 . The C-arm  306  is rotatably supported on the stand  308 . Repeating radiography with respect to the object OBJ while rotating the C-arm  306  makes it possible to acquire X-ray images (projection data) in many directions which are required for three-dimensional image reconstruction. 
     The radiography control circuitry  204  controls the rotation of the C-arm  306 , the application of high voltages from the high voltage generator  310  to the X-ray tube  302 , and reading of signals from the X-ray detector  304  in order to execute rotational radiography and generate X-ray image data. 
     The memory  206  stores a dedicated program for executing the scattered radiation correction method  100 . 
     The monitor  208  is a display device such as a CRT, plasma display, or liquid crystal display which displays an X-ray diagnostic image or the like in a predetermined form in accordance with a signal received from the reconstruction processing circuitry  212  or the image processing circuitry  214 . 
     The input device  210  includes a keyboard, various kinds of switches, a mouse, and the like and is used to input a radiography instruction, image selection instruction, etc. The reconstruction processor  212  reconstructs volume data from projection images in a plurality of projection directions. 
     The image processing circuitry  214  executes predetermined image processing such as volume rendering processing and image difference processing as needed. 
     The scattered radiation correction circuitry  216  implements the scattered radiation correction method  100 . The scattered radiation correction circuitry  216  implements the scatter correction method  100  to extract the primary beam X-ray projection data P Final (x, y, θ) from the measured X-ray projection data T(x, y, θ) with scatter. 
       FIG. 4 , shows a conventional (L 1 ) and a novel (L 2 ) scattering function to be used in the method  100 . Using a forward scatter model that ignores multiple scattering and the polychromatic nature of the incident x-ray beam and the scattered x-ray beam, the conventional scatter function is given by
 SF( x )=− x  log  x,  
 
where log is the natural logarithm function. This conventional scatter function model is shown as line L 1  in  FIG. 4 . While this conventional scattering model works well for many CT applications, in certain CT applications (e.g., in large field-of-view scans in which there is secondary scatter from a bowtie filter and other scatter sources) dark-band artifacts can manifest in the reconstructed CT image. For example, these dark-band artifacts can be observed in the shoulder region of a head and shoulder image. These dark-band artifacts can be mitigated by using the scatter function model shown as line L 2  in  FIG. 4 .
 
       FIG. 4  shows a plot of two scatter function models, L 1  and L 2 , as a function of the primary beam transmission P, where the primary beam transmission is plotted along the horizontal axis and the scatter function is plotted along the vertical axis. In the limit of small primary beam transmission, the assumptions upon which the conventional scatter function L 1  is based (e.g., single scattering and small scattering angle) lead to the results that the scatter linearly approaches zero as the primary beam transmission goes to zero. However, as an empirical matter, there can still be residual scatter even as the primary beam becomes vanishingly small. Therefore a scatter function model such as L 2 , where the scatter function remains is greater than zero as the primary beam transmission approaches zero, more accurately models the scatter that is observed in certain implementations of CT imaging. The scatter function model L 2  can be expressed as 
               SF   ⁡     (   P   )       =     {                 -     (       log   ⁡     (     P   1     )       +   1     )       ⁢   P     +     P   1             P   &lt;     P   1                   -   P     ⁢           ⁢     log   ⁡     (   P   )               P   ≥     P   1             ,             
and P 1  is a predefined value chosen to match empirical scatter measurements and/or that minimizes dark-band artifacts. Using L 2  rather than L 1  as the scatter function in the scatter correction calculation can result in fewer dark-band artifacts. In another implementation, the scatter function can be any predetermined function that predicts observed X-ray scatter and for which the scatter is greater than zero in the limit that the primary beam transmission goes to zero.
 
       FIG. 5  shows an implementation of the scattered radiation correction circuitry  216  that performs the method  100 . Next, a hardware description of the scattered radiation correction circuitry  216  according to exemplary embodiments is described with reference to  FIG. 5 . In one implementation, the hardware, which performs the function of the scattered radiation correction circuitry  216 , can also perform additional functions, including the functions of the radiography control circuitry  204 , the reconstruction processor  212 , and the image processing circuitry  214 . These functions can be performed using a single instance of the hardware shown in  FIG. 5 , or separate functions can be performed by separate instances of the hardware shown in  FIG. 5 , which are each part of a single network. 
     In  FIG. 5 , the scattered radiation correction circuitry  216  includes, e.g., a CPU  500  which performs the processes described herein. Alternatively, the scattered radiation correction circuitry  216  is a specialized hardware circuitry other than a CPU. Process data and instructions may be stored in memory  502 . Processes and instructions may also be stored on a storage medium disk  504  such as a hard drive (HDD) or portable storage medium or may be stored remotely. Further, this disclosure is not limited by the form of the computer-readable media on which the instructions are stored. For example, the instructions may be stored on CDs, DVDs, in FLASH memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk or any other information processing device with which the scattered radiation correction circuitry  216  communicates, such as a server or computer. 
     Further, aspects of this disclosure may be provided as a utility application, background daemon, or component of an operating system, or combination thereof, executing in conjunction with CPU  500  and an operating system such as Microsoft Windows 7, UNIX, Solaris, LINUX, Apple MAC-OS and other systems known to those skilled in the art. 
     CPU  500  may be a Xenon or Core processor from Intel of America or an Opteron processor from AMD of America, or may be other processor types that would be recognized by one of ordinary skill in the art, such as an ARM-based processor. Alternatively, the CPU  500  may be implemented on an FPGA, ASIC, PLD or using discrete logic circuits, as one of ordinary skill in the art would recognize. Further, CPU  500  may be implemented as multiple processors cooperatively working in parallel to perform the instructions of the inventive processes described above. 
     The scattered radiation correction circuitry  216  in  FIG. 5  also includes a network controller  506 , such as an Intel Ethernet PRO network interface card from Intel Corporation of America, for interfacing with network  530 . As can be appreciated, the network  530  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 network  530  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 another wireless form of communication. 
     The scattered radiation correction circuitry  216  further includes a display controller  508 , such as a NVIDIA GeForce GTX or Quadro graphics adaptor from NVIDIA Corporation of America that respectively interface with a corresponding display  510 , such as a Hewlett Packard HPL2445w LCD monitor. 
     The scattered radiation correction circuitry  216  further includes a general purpose I/O interface  512  interfaces with a keyboard and/or mouse  514  as well as sensors  516 . The general purpose I/O interface  512  can also connect to a variety of actuators  518 . The general purpose I/O interface  512  can also connect to a variety of peripherals including printers and scanners, such as an OfficeJet or DeskJet from Hewlett Packard. 
     A sound controller  520  is also provided in the scattered radiation correction circuitry  216 , such as Sound Blaster X-Fi Titanium from Creative, to interface with speakers/microphone  522  thereby providing sounds and/or music. 
     The general purpose storage controller  524  connects the storage medium disk  504  with communication bus  526 , which may be an ISA, EISA, VESA, PCI, or similar, for interconnecting all of the components of the scattered radiation correction circuitry  216 . A description of the general features and functionality of the display  510 , keyboard and/or mouse  514 , as well as the display controller  508 , storage controller  524 , network controller  506 , sound controller  520 , and general purpose I/O interface  512  is omitted herein for brevity as these features are known. 
       FIG. 6  shows a schematic view of a CT scanner system having energy integrating detectors arranged in a third generation geometry and photon counting detectors (PCDs) arranged in a fourth-generation geometry.  FIG. 6  shows a coupled ring topology with the X-ray source  614  inside the ring of PCDs and the X-ray detector unit  603  is outside the ring of PCDs, as discussed in U.S. patent application Ser. No. 13/426,903, incorporated herein by reference in its entirety. 
     Illustrated in  FIG. 6  is an implementation for placing the photon-counting detectors (PCDs) in a predetermined fourth-generation geometry in combination with a detector unit  603  in a predetermined third-generation geometry in a CT scanner system. The diagram illustrates relative positions among an object OBJ to be scanned resting on a table  616 , an X-ray source  612 , a collimator/filter  614 , an X-ray detector  603 , and photon-counting detectors PCD 1  through PCDN. The PCDs have a front surface, oriented towards the object OBJ and a back surface oriented away from the object OBJ. X-rays traveling through the object OBJ are either detected by the PCDs (at the front surface) or pass through the spaces between the sparsely arranged PCDs and are detected by the tightly packed energy integrating detectors in the X-ray detector  603 . 
     Also shown in  FIG. 6  is circuitry and hardware for acquiring, storing, processing, and distributing X-ray projection data. The circuitry and hardware include: a processor  670 , a network controller  674 , a memory  678 , and a data acquisition system  676 . In one implementation, the scatter correction could be performed using a dedicated program stored in memory  678  and loaded into the processor  670 , which then performs the scatter correction on the projection data before the image reconstruction steps. In one implementation, the scatter correction is performed in circuitry associated with the data acquisition system  676  before the projection data is stored into memory  678  for later processing. 
     In one implementation, the X-ray source  612  and the collimator/filter  614  are fixedly connected to a rotational component  610  that is rotatably connected to a gantry  640 . The X-ray detector  603  is similarly fixedly connected to a rotational component  630  that is rotatably connected to the gantry  640 . The PCDs are fixedly connected to a circular component  620  that is fixedly connected to the gantry  640 . The gantry  640  houses many pieces of the CT scanner. 
     The gantry of the CT scanner also includes an open aperture  615  enabling the object OBJ that is arranged on a table  616  positioned in a projection plane of the X-rays traveling from the X-ray source to the PCDs and detector unit  603 . The “projection plane” is a volume wherein X-rays pass from the X-ray source  612  to the detectors including the PCDs and the detector unit  603 . The “object space” is the intersection of the projection plane and the open aperture  615  of the gantry. The “object space” includes the union of projection planes corresponding to all projection angles of the X-ray source  612  as the X-ray source  612  rotates around the aperture of the gantry. 
     A scan is performed when an object OBJ occupies the object space and the X-ray source is rotated through a series of projection angles with the CT scanner acquiring projection data of the X-ray transmission/attenuation through the object OBJ at each projection angle. 
     In general, the photon-counting detectors PCD 1  through PCDN each output a photon count for each of a predetermined number of energy bins. In addition to the photon-counting detectors PCD 1  through PCDN arranged in the fourth-generation geometry, the implementation shown in  FIG. 6  includes a detector unit  603  having energy-integrating detectors arranged in a conventional third-generation geometry. The detector elements in the detector unit  603  can be more densely placed along the detector unit surface than the photon-counting detectors. 
     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 PCD 1  through PCDN are fixedly placed on a predetermined second circular component  620  in a gantry. In one implementation, the photon-counting detectors PCD 1  through PCDN are fixedly placed on the circular component  620  at predetermined equidistant positions. In an alternative implementation, the photon-counting detectors PCD 1  through PCDN are fixedly placed on the circular component  620  at predetermined non-equidistant positions. The circular component  620  remains stationary with respect to the object OBJ and does not rotate during the data acquisition. 
     Both the X-ray source  612 , collimator  614  (e.g., a bow tie filter), and the detector unit  603  rotate around the object OBJ while the photon-counting detectors PCD 1  through PCDN are stationary with respect to the object OBJ. In one implementation, the X-ray source  612  projects X-ray radiation with a predetermined source fan beam angle θ A  towards the object OBJ while the X-ray source  612  rotates around the object OBJ outside the sparsely placed photon-counting detectors PCD 1  through PCDN. Furthermore, the detector unit  603  is mounted at a diametrically opposed position from the X-ray source  612  across the object OBJ and rotates outside the stationary circular component  620 , on which the photon-counting detectors PCD 1  through PCDN are fixed in a predetermined sparse arrangement. 
     In one implementation, the X-ray source  612  optionally travels a helical path relative to the object OBJ, wherein the table  616  moves the object OBJ linearly in a predetermined direction perpendicular to the rotational plane of the rotating portion  610  as the rotating portion  610  rotates the X-ray source  612  and detector unit  603  in the rotational plane. 
     The motion of the rotating portion  610  around the object OBJ is controlled by a motion control system. The motion control system can be integrated with a data acquisition system or can be separate providing one way information regarding the angular position of the rotating portion  610  and the linear position of the table  616 . The motion control system can include position encoders and feedback to control the position of the rotating portion  610  and the table  616 . The motion control system can be an open loop system, a closed loop system, or a combination of an open loop system and a closed loop system. The motion control system can use linear and rotary encoders to provide feedback related to the position of the rotating portion  610  and the position of the table  616 . The motion control system can use actuators to drive the motion of the rotating portion  610  and the motion of the table  616 . These positioners and actuators can include: stepper motors, DC motors, worm drives, belt drives, and other actuators known in the art. 
     The CT scanner also includes a data channel that routes projection measurement results from the photon counting detectors and the detector unit  603  to a data acquisition system  676 , a processor  670 , memory  678 , network controller  674 . The data acquisition system  676  controls the acquisition, digitization, and routing of projection data from the detectors. The data acquisition system  676  also includes radiography control circuitry to control the rotation of the annular rotating frames  610  and  630 . In one implementation data acquisition system  676  will also control the movement of the bed  616 , the operation of the X-ray source  612 , and the operation of the X-ray detectors  603 . The data acquisition system  676  can be a centralized system or alternatively it can be a distributed system. In an implementation, the data acquisition system  676  is integrated with the processor  670 . The processor  670  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  670  and the data acquisition system  676  can make use of the memory  676  to store, e.g., projection data, reconstructed images, calibration data and parameters, and computer programs. 
     The processor  670  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  678  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  674 , 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  674  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. 
     In one implementation, the X-ray source  612  is optionally a single energy source. In another implementation, the X-ray source  612  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  612  is a single source emitting a broad spectrum of X-ray energies. In still another embodiment, the X-ray source  612  includes multiple X-ray emitters with each emitter being spatially and spectrally distinct. 
     The detector unit  603  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 be crystalline (e.g., NaI(Tl), CsI(Tl), CsI(Na), CsI(pure), CsF, KI(Tl), LiI(Eu), BaF 2 , CaF 2 (Eu), ZnS(Ag), CaWO 4 , CdWO 4 , YAG(Ce), Y 3 Al 5 O 12 (Ce), GSO, LSO, LaCl 3 (Ce), LaBr 3 (Ce), LYSO, BGO, LaCl 3 (Ce), LaBr 3 (Ce), C 14 H 10 , C 14 H 12 , and C 10 H 8 ), an organic liquid (e.g., an organic solvent with a fluor such as p-terphenyl (C 18 H 14 ), PBD (C 20 H 14 N 2 O), butyl PBD (C 24 H 22 N 2 O), or PPO (C 15 H 11 NO)), a plastic (e.g., a flour suspended in a solid polymer matrix), or other know scintillators or phosphors. 
     The PCDs can use a direct X-ray radiation detectors based on semiconductors, such as cadmium telluride (CdTe), cadmium zinc telluride (CZT), silicon (Si), mercuric iodide (HgI 2 ), and gallium arsenide (GaAs). Semiconductor based direct X-ray detectors generally have much faster time response than indirect detectors, such as scintillator detectors. The fast time response of direct detectors enables them to resolve individual X-ray detection events. However, at the high X-ray fluxes typical in clinical X-ray applications some pile-up of detection events will occur. The energy of a detected X-ray is proportional to the signal generated by the direct detector, and the detection events can be organized into energy bins yielding spectrally resolved X-ray data for spectral CT. 
     While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. 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 the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.

Technology Classification (CPC): 6