Abstract:
The present disclosure relates to the performing spectral calibration of a CT imaging system. In accordance with certain embodiments, spectral calibration phantoms are scanned while positioned on a table in the imaging volume of the CT imaging system. The scans of the calibration phantoms, in conjunction with air sans performed on the CT imaging system, are used to derive information about the deviation of the measured phantom scans from an ideal. The deviation information is in turn used to derive spectral calibration vectors that may be used with the CT imaging system.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is a Non-Provisional of U.S. Provisional Patent Application No. 61/289,828, entitled “CT Spectral Calibration”, filed Dec. 23, 2009, which is herein incorporated by reference in its entirety for all purposes. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    The subject matter disclosed herein relates to non-invasive imaging and, in particular, to spectral calibration of a radiographic imaging system. 
         [0003]    In the fields of medical imaging and security screening, non-invasive imaging techniques have gained importance due to benefits that include unobtrusiveness, convenience, and speed. In medical and research contexts, non-invasive imaging techniques are used to image organs or tissues beneath the surface of the skin. Similarly, in industrial or quality control (QC) contexts, non-invasive imaging techniques are used to examine parts or items for hidden defects that may not be evident from an external examination. In security screening, non-invasive imaging techniques are typically used to examine the contents of containers (e.g., packages, bags, or luggage) without opening the containers and/or to screen individuals entering or leaving a secure location. 
         [0004]    One example of a non-invasive imaging system is a computed tomography (CT) imaging system in which an X-ray source emits radiation (e.g., X-rays) towards an object or subject (e.g., a patient, a manufactured part, a package, or a piece of baggage) from a variety of different angular positions. The emitted X-rays, after being attenuated by the subject or object, typically impinge upon an array of radiation detector elements of an electronic detector, which generates signals indicate of the incident radiation at different locations on the detector. The intensity of radiation reaching the detector is typically dependent on the attenuation and absorption of X-rays through the scanned subject or object. The signals generated at the detector are processed to generate images and/or volumetric representations of the internal structures of the subject or object. 
         [0005]    Such a CT system may be subject to various artifacts, such as beam hardening artifacts, ring/band artifacts, and/or scatter-induced artifacts. To mitigate such artifacts, a spectral calibration process may be performed using a variety of calibration phantoms. However, as the scan coverage of such CT systems has increased (particularly in the dimension extending through the imaging bore, i.e., the Z-direction), the phantoms have grown correspondingly larger to accommodate the increased scan coverage. The increased size of such calibration phantoms can make performing spectral calibrations by attaching the phantom at the edge of the patient table increasingly difficult. 
       BRIEF DESCRIPTION OF THE INVENTION 
       [0006]    In one embodiment, a method for calibrating a CT system is provided. In accordance with this method, an air scan is acquired at a specified peak voltage (kVp). A phantom scan is also acquired at the kVp. The phantom scan is acquired by scanning the respective phantom on a table. Projections associated with the air scan and the phantom scan are processed with a preliminary beam hardening correction function. An image is reconstructed using the corresponding corrected projections. The image is segmented to remove non-phantom components. The segmented image is processed to generate an image pair comprising a phantom image with artifacts and a phantom image without artifacts. The image pair is projected to generate a projection pair. A respective deviation ratio is derived for the projection pair. The acquiring, processing projections, reconstructing segmenting, processing the segmented image, projecting, and deriving steps are repeated for a specified range of kVp, filters, and phantoms. A number of phantoms can be used to cover the attenuation range utilized by the CT system. Spectral calibration vectors are derived based on the respective deviation ratios. 
         [0007]    In another embodiment, a method for acquiring phantom scan data is provided. In accordance with this embodiment, a phantom is positioned on a table and within a bore of a CT imaging system. The CT imaging system is operated to acquire projection data while the phantom is on the table and within the bore. 
         [0008]    In a further embodiment, a method for calibrating a CT imaging system is provided. In accordance with this embodiment, a plurality of air scans are acquired at different kVp and with different filters. A plurality of phantom scans are acquired at the different kVp, with the different filters, and using different phantoms. The plurality of phantom scans are acquired with the respective phantoms positioned on a table within the field of view of the CT imaging system. The respective plurality of air scans and the respective plurality of phantom scans are processed to derive one or more spectral calibration vectors for the CT imaging system. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0009]    These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein: 
           [0010]      FIG. 1  is a combined pictorial view and block diagram of a CT imaging system illustrating an embodiment of the present disclosure; 
           [0011]      FIG. 2  depicts an example of a water-filled phantom for use in spectral calibration, in accordance with an embodiment of the present disclosure; and 
           [0012]      FIG. 3  depicts a flowchart of an algorithm used to derive spectral calibration vectors in accordance with the an embodiment of the present disclosure. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0013]    The present disclosure provides for using large scan phantoms for performing spectral calibration of a CT imaging system. In accordance with the present approach, a phantom may be positioned on the support table during the calibration process. Contributions from the table to the acquired calibration data are removed from the calibration measurements as part of calibration process. In this manner, the CT system may undergo spectral calibration even though the calibration scan data initially includes data corresponding to other structures in addition to the calibration phantom. 
         [0014]    With the foregoing in mind and in accordance with one embodiment, a CT imaging system is provided. The present discussion is generally provided in the context of a 3rd generation CT system, however, the present disclosure is equally applicable to other systems. For simplicity, the present discussion generally describes the use of detectors and X-ray imaging systems in a medical imaging context. However, it should be appreciated that the described radiation detectors may also be used in non-medical contexts (such as security and screening systems and non-destructive testing and/or detection systems). 
         [0015]    Referring to  FIG. 1 , a computed tomography (CT) imaging system  10  is shown as including a gantry  12  representative of a “third generation” CT scanner. Gantry  12  has an X-ray source  14  that projects a beam of X-rays  16  toward a detector assembly  15  on the opposite side of the gantry  12 . The detector assembly  15  includes a collimator assembly  18 , a plurality of detector modules  20 , and data acquisition systems (DAS)  32 . The plurality of detector modules  20  detect the projected X-rays that pass through a medical patient  22 , and DAS  32  converts the data to digital signals for subsequent processing. Each detector module  20  in a conventional system produces an analog electrical signal that represents the intensity of an impinging X-ray beam and hence the attenuated beam as it passes through a patient or, as depicted in  FIG. 1 , a spectral calibration phantom  22 . During a scan to acquire X-ray projection data, gantry  12  and the components mounted thereon rotate about a center of rotation  24 . 
         [0016]    Rotation of gantry  12  and the operation of X-ray source  14  are governed by a control mechanism  26  of CT system  10 . Control mechanism  26  includes an X-ray controller  28  that provides power and timing signals to an X-ray source  14  and a gantry motor controller  30  that controls the rotational speed and position of gantry  12 . An image reconstructor  34  receives sampled and digitized X-ray data from DAS  32  and performs high-speed reconstruction. The reconstructed image is applied as an input to a computer  36 , which stores the image in a mass storage device  38 . Computer  36  also receives commands and scanning parameters from an operator via console  40 . An associated display  42  allows the operator to observe the reconstructed image and other data from computer  36 . The operator supplied commands and parameters are used by computer  36  to provide control signals and information to DAS  32 , X-ray controller  28 , and gantry motor controller  30 . In addition, computer  36  operates a table motor controller  44 , which controls a motorized table  46  to position a patient or object undergoing imaging (e.g., the spectral calibration phantom  22 , within the gantry  12 . Particularly, table  46  moves portions of the subject or other object through a gantry opening  48 . 
         [0017]    In conventional approaches, a CT imaging system  10  may undergo a spectral calibration process to allow for the correction or removal of soft tissue beam hardening artifacts, as well as ring/band artifacts arising from detector imperfections. In addition, the spectral calibration may allow scatter induced artifacts to be suppressed or removed. During a conventional spectral calibration process, cylindrical water phantoms (such as the generalized water phantom  22  of  FIGS. 1 and 2 ) of various sizes are scanned to detect the deviation from an ideal projection. The measured calibration projection data through the phantoms  22  are compared with the known phantom&#39;s size and shape to compute calibration coefficients. That is the size and shape as determined from the scans of the phantoms  22  are compared to the known size and shape of the phantoms  22 . In a conventional calibration scanning process, the phantoms are typically attached to a holder at the end of the patient table so that the phantom is within the scanner field of view, but the table is not within the field of view. Thus, the phantom calibration scan yields projection data which corresponds to a known shape, i.e., the phantom, without little or no contamination from other structures, such as the table  46 . 
         [0018]    However, as cone-beam CT systems have developed with increased coverage in the Z-direction, i.e., along the axis running through the imaging bore, the size of the cylindrical calibration phantoms has also increased to accommodate the extent of the increased Z-coverage. For example, a CT scanner with 40 mm coverage in the Z-direction may utilize a calibration phantom that is 80 mm long and more than 40 cm in diameter. Likewise, as Z-coverage extends to 80 mm, 320 mm and so forth, the size of the respective calibration phantoms increases correspondingly. As a result, the calibration phantoms have become so heavy that it is difficult for the phantoms to be held or suspended from the edge of the table. 
         [0019]    As discussed herein, approaches are disclosed for scanning the calibration phantom  22  while positioned on the table  46  (as depicted in  FIG. 1 ), without hanging or suspending the phantom  22  from the edge of the table  46 . In accordance with the present approaches, the calibration vectors are computed based on the deviation of the measured projections to ideal projections from the expected known circular object (i.e., the phantom  22 ). In particular, ideal projections are extracted and compared with the actual or measured projections after removing the contributions from the table  46 , even though the table  46  contributes to the initial measurements. 
         [0020]    With the foregoing in mind, and turning now to  FIG. 3 , in one embodiment, respective air scans  64  and phantom scans  66  are acquired (blocks  60  and  62 , respectively) at a range of kVp&#39;s (e.g., 80 kVp, 120 kVp, and 140 kVp) and with the range of available bowtie beam filters available on the scanner. For example, at a given kVp, the projections through air are measured (block  60 ) without the patient table  46  in the beam. The phantom calibration scans (block  62 ) are typically performed using multiple cylindrical water or water-like objects of different sizes (e.g., phantoms) placed in the beam path. The phantoms  22  are placed on the table  46  and scanned at the given kVp. The respective air and phantom scans (blocks  60  and  62 ) are repeated for all the kVp&#39;s and bowtie beam filters offered by the scanner and a determined dark current value is subtracted from the generated data. The data collected by these calibration scans includes the air scans  64  acquired at different kVp&#39;s and with different bowtie filters and the phantom scans  66  acquired at different kVp&#39;s, with different bowtie filters, and using a range of differently sized phantoms  22 . In one embodiment, the phantoms  22  can be centered or off-centered with respect to the iso-center of the scanner, e.g., imaging system  10 . Thus, after data collection, the following data is available for subsequent processing: air scans (i.e., a D ), which correspond to the air profile, with dark current subtracted, at a given kVp and bowtie filtration, where D is the detector index in x-direction; and phantom scans (i.e., w D   d ), which correspond to the raw data through water attenuation of a diameter d circular phantom, with dark current subtracted, at corresponding kVp and bowtie filtration as in the respective air scan. 
         [0021]    After data collection, deviations from the expected values are determined. As will be appreciated, when the table  46  is present in the X-ray beam, the measured projections can be of un-controlled shape. It is presumed that one does not have a direct expectation of these projections that represent the ideal case and free of artifacts attributable to detector imperfections and beam hardening. However, in a successfully calibrated system, the phantom should be uniform at the targeted Hounsfield units (HU) value. 
         [0022]    In the measurement, the table  46  should contribute little to the attenuation compared to the phantom  22 . Therefore, it would be a reasonable approximation that the deviations from the ideal condition in the image reconstructed with preliminary beam hardening correction vectors, which can be computed theoretically, would be contributed mostly by the phantom  22 . With this assumption, a new pair of physical and ideal projections can be obtained by processing (block  70 ) the measured projections p D   d  in accordance with: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       p 
                       D 
                       d 
                     
                     = 
                     
                       - 
                       
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                         ( 
                         
                           
                             w 
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                             d 
                           
                           
                             a 
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                    
                   
                     
 
                   
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                         f 
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         [0000]    Where, ƒ D ( ) is the preliminary beam hardening correction functional form, mostly in the polynomial format. 
         [0023]    In one implementation, the preliminary beam hardening corrected projections  72  are reconstructed (block  74 ) to form an image  76  (i.e., Ig(x, y)). The image  76  may not be fully corrected and may include rings/bands and/or HU differences (i.e., non-uniformities) in the phantom (e.g., water) region. The phantom cylinder in image Ig(x, y) is segmented (block  78 ), eliminating the table  46  and any other non-phantom components from the image  76 . The segmented image  80  may be processed (block  82 ) to represent the ideal image by setting the phantom (e.g., water) HU value to the targeted value, e.g., 1000, yielding pairs of phantom (e.g., water cylinder) images, one image  84  (i.e., Ig(x′, y′)) with artifacts, and one image  86  (i.e., Ig ideal (x′, y′)) without artifacts. Such processing may be threshold-based, taking advantage of the relatively weak attenuation provided by the table in comparison to the water in the phantom. 
         [0024]    The paired images  84 ,  86  (i.e., Ig(x′, y′) and Ig ideal (x′, y′)) are forward projected (block  88 ) to the same ray path as the corresponding measured projections p D   d , resulting in paired projection sets  90 ,  92  (i.e., pƒ D   d , pƒ D,ideal   d ). The deviation of the projection from the ideal value for each phantom is described (block  94 ) by the deviation ratio  96 : 
         [0000]    
       
         
           
             
               
                 
                   
                     r 
                     D 
                     d 
                   
                   = 
                   
                     
                       pf 
                       
                         D 
                         , 
                         ideal 
                       
                       d 
                     
                     
                       pf 
                       D 
                       d 
                     
                   
                 
               
               
                 
                   ( 
                   2 
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         [0000]    at a total projection (uncorrected) value of p D   d . With a reasonably good preliminary calibration vector set, the computed deviation ratio  96  (i.e., r D   d ) describes the characteristic of the CT detection system, with a value typically close to 1.0. This procedure is repeated for all the phantom sizes, indexed by d. In one implementation, three to four phantoms are used to fully cover the calibration range. 
         [0025]    For a given detector index, D, the spectral calibration vectors  100  can be obtained (block  98 ) by combining the preliminary beam hardening correction functions and the deviation ratio  96  (i.e., r D   d ) from all phantoms  22 , i.e., by updating the beam hardening correction functions with the extracted deviations from the ideal. For example, in one embodiment, correction data pairs are generated using the preliminary beam hardening correction for projection values covering a range of interest, such as: 
         [0000]      ( p,ƒ   D ( p ))  (3)
 
         [0000]    where p ranges from 0 to 12.0, with a step of 0.2. In addition, data points are generated using the phantom measurements such that each phantom measurement (e.g., 3 or 4 phantom measurements) yield a set of data pairs that can be used to generate an ideal phantom image (e.g., water image) free of artifacts. For example, in one embodiment these data sets are generated as: 
         [0000]        p   D   d ,ƒ D ( p   D   d )· r   D   d   (4)
 
         [0000]    where r D   d  provided the desired correction. 
         [0026]    The data pair points generated using the preliminary beam hardening correction and those generated from the phantom measurement are combined to include both the correction provided by preliminary calibration vectors and additional correction from measurements. The data pairs from the preliminary calibration are included to confine the fitting to follow the trend of the functional curve. The new data pair sets can be expressed as: 
         [0000]      { p   D   d   ;p→ƒ   D ( p );ƒ D ( p   D   d )· r   D   d }.  (5)
 
         [0000]    In one implementation, the above data pairs are fitted with the designated functional form for the spectral calibration. In one embodiment, more weight is given to the data pairs deduced from measurements (that is the data pairs deduced in accordance with equation (4). In the polynomial format, the data sets are fitted with a polynomial form, such as a 3rd to 4th order form, resulting in typically calibration vectors  100  (e.g., a1, a2, a3, aN), satisfying: 
         [0000]      (ƒ D ( p );ƒ D ( p   D   d )· r   D   d )= a   1 ·( p;p   D   d )+ a   2 ·( p;p   D   d ) 2   +a   3 ·( p;p   D   d ) 3   (6)
 
         [0000]    The new calibration vectors are used as the preliminary beam hardening correction, as depicted at block  70 , and the process is iterated a set number of times, until a cost or other threshold function is satisfied, or until a satisfactory calibration vectors (as determined by any suitable criteria) are obtained for all the detector cells in the system. Thus, as discussed above, the algorithm discussed herein provides a way to perform spectral calibration for a CT system with phantoms placed directly on the patient table, without requiring precise phantom centering. 
         [0027]    Technical effects of the invention include spectral calibration of a CT system using a phantom that is scanned while on the patient table. Other technical effects include removing non-phantom contributions from calibration scan data to facilitate calibration of an imaging system. Additional technical effects include deriving a deviation ratio describing the deviation of a set of measured calibration projections from corresponding set of ideal calibration projections and calculating calibration vectors using the deviation ratio. 
         [0028]    This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.