JP2003190147A - X-ray ct system and image processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an X-ray CT system and an image processor for preparing a subtraction image in which the influence of an artifact caused by a tissual movement is reduced. <P>SOLUTION: The system is provided with a scanner part 1 for detecting projection data related to an examinee, a control part for controlling the scanner part to collect projection data for a mask image and projection data for an image to be subtracted, a data extracting part 8 for extracting specific projection data from the projection data for the mask image on the basis of the focus angle range and the cardiac phase range of the projection data for the image to be subtracted, a reconstruction part 9 for reconstructing image data to be subtracted from the projection data of the image to be subtracted and mask image data from the extracted projection data for the mask image, and a differential arithmetic part 10 for differentiating the mask image data from the image data to be subtracted. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of capturing a subtraction image before and after injection of a contrast agent by X-ray CT (X-ray computed tomography), and particularly to a subtraction image having high temporal resolution in a tissue moving like a heart. Method, an X-ray CT apparatus (X-ray computed tomography apparatus), and an image processing apparatus.

[0002]

2. Description of the Related Art [Brain dynamic study] A bed is fixed and one CT image of the brain of the same slice is taken for about 1 second (or 3).
Continuous shooting at a time interval of 1 per 0 seconds)
The CT image before the injection of the contrast agent is subtracted from the T image to create an image proportional to the contrast agent concentration of the taken cross section, and the image is observed or the time-concentration curve of the specific region in the image is analyzed. The low blood flow region is identified and the distribution of brain activity is imaged, and is used for diagnosis of cerebral infarction and the like.

[Problems of cardiac dynamic study] The present method is applied to the myocardium of the heart to determine the presence or absence of a low blood flow region (= ischemic region) and to identify the position of the low blood flow region. When thinking about what to do, the heart is a moving tissue, so 1
In order to capture one image per second, it is necessary to capture one image within 250 ms, for example. In order to achieve this time resolution using a CT device with one rotation of 0.5 seconds, it is necessary to use half reconstruction.

However, the half reconstruction has a problem that there is no effective means for removing the artifacts due to the pulsation of the heart. That is, in the reconstruction method using the data of one rotation, there is a method of reducing the motion artifact by correcting the problem that the consistency between the data at the beginning and the end of the rotation is deteriorated due to the movement during the rotation. This method cannot be used for reconstruction.

Therefore, there is a problem in that the concentration of the contrast medium in the myocardium cannot be imaged with high accuracy and the analysis of blood flow useful for the diagnosis of ischemic heart disease cannot be substantially performed.

[0006]

SUMMARY OF THE INVENTION It is an object of the present invention to provide an X-ray CT apparatus and an image processing apparatus for producing a subtraction image in which the influence of artifacts due to tissue movement is small.

[0007]

An X-ray CT apparatus according to the present invention controls a scanner unit for detecting projection data relating to a subject and the scanner unit to control projection data for a mask image and a subtraction image. A projection data for the subtracted image, and a specific projection data from the projection data for the mask image based on a focal angle range and a cardiac phase range of the projection data for the subtracted image. A data extracting unit, and reconstructing subtracted image data from the projection data for the subtracted image, and a reconstruction unit for reconstructing mask image data from the projection data for the extracted mask image, And a difference calculation unit that subtracts the mask image data from the subtracted image data. An X-ray CT apparatus according to the present invention includes a scanner unit that detects projection data relating to a subject, and X-rays the projection data.
Backprojection means for backprojecting while changing the line focus angle, reconstruction area moving / deforming means for moving or deforming the reconstruction area depending on the X-ray focal angle during the backprojection, and all the projection data. Projection data generation means for generating pseudo projection data from pixel value data of the backprojected reconstruction area after back projection with respect to the focal angle, and difference measurement means for calculating a difference between the projection data and the pseudo projection data. , The X to minimize the calculated difference
It comprises an optimization means for iteratively correcting the dependence of the movement / deformation of the reconstruction area on the line focal angle, and means for generating image data according to the dependence when the difference is minimized. The image processing apparatus of the present invention includes means for inputting projection data for a mask image and projection data for a subtracted image, a focal angle range and a cardiac phase range of the projection data for the subtracted image. A data extraction unit for extracting specific projection data from the projection data for the mask image, and reconstructing the subtracted image data from the projection data for the subtracted image, and the extracted mask A reconstruction unit that reconstructs mask image data from projection data for an image and a difference calculation unit that subtracts the mask image data from the subtracted image data. An image processing apparatus according to the present invention includes a backprojecting unit that backprojects projection data relating to a subject while changing an X-ray focal angle, and moves or deforms a reconstruction area depending on the X-ray focal angle during the backprojection. Reconstruction area moving / deforming means, projection data generation means for backprojecting the projection data for all focal angles, and then generating pseudo projection data from pixel value data of the backprojected reconstruction area; and the projection data. Difference measurement means for calculating the difference between the X-ray focal point angle and the pseudo projection data, and optimization for iteratively correcting the dependence of movement / deformation of the reconstruction area on the X-ray focal angle so as to minimize the calculated difference. And means for generating image data according to the dependency when the difference is minimized.

[0008]

BEST MODE FOR CARRYING OUT THE INVENTION The present embodiment is intended to create a subtraction image with high temporal resolution, which is less affected by artifacts due to tissue motion, and in turn, a dynamic CT image of moving tissue is captured with high accuracy. It is effective for blood flow analysis and enables highly accurate analysis of blood flow even in a moving tissue such as the heart.
By realizing a method for diagnosing a heart disease such as ischemic heart disease from a low blood flow region of the myocardium detected using X-ray CT,
Compared with other methods for diagnosing ischemic heart disease using other methods such as T and stress ultrasonography, it is possible to provide doctors with information for diagnosing heart disease with high accuracy, low cost, and ease. is there.

The following technique is included in this embodiment. (1) Subtraction method using a mask image in the same or closest cardiac phase range / focal angle range The mask image is a term contrasting with an image reconstructed from projection data collected by a main scan. That is, it is defined as an image reconstructed from projection data acquired by pre-scan or post-scan of the same part and the same slice as the main scan executed in the period before and after the main scan execution period. As a typical example of the mask image, in contrast examination, before or after the contrast agent flows into the imaging region, with respect to the main scan that is performed during the period from when the contrast agent flows into the imaging region until it flows out. There is an image in which the contrast effect reconstructed based on the projection data collected in the pre- or post-scan performed during the period is not reflected at all or the effect is minute. In the following, a mask image will be described as an image reconstructed from projection data collected in the pre-scan before the main scan, that is, before the contrast agent injection.

(2) Reconstruction method with misregistration correction using misregistration model (3) Reconstruction method with motion artifact correction using opposed data FIG. 1 shows an X-ray CT apparatus according to this embodiment. Shows the configuration of. In the X-ray CT apparatus, a rotation / rotation (ROTATE / ROTATE) type in which an X-ray tube and a radiation detector are rotated as one body around a subject, and a large number of detection elements are arrayed in a ring shape, There are various types such as a stationary / rotation type in which only the X-ray tube rotates around the subject, and the present invention can be applied to any type. Here, the rotation / rotation type which is currently the mainstream will be described. The mechanism of converting incident X-rays into electric charges includes an indirect conversion type in which X-rays are converted into light by a phosphor such as a scintillator, and the light is further converted into electric charges by a photoelectric conversion element such as a photodiode. The mainstream is the generation of electron-hole pairs in a semiconductor and the movement thereof to an electrode, that is, a direct conversion type utilizing a photoconductivity phenomenon. Any of these methods may be adopted as the X-ray detection element, but here, the former indirect conversion type will be described. Further, in recent years, so-called multi-tube type X-ray CT apparatus in which a plurality of pairs of an X-ray tube and an X-ray detector are mounted on a rotating ring has been commercialized, and development of peripheral technologies thereof has been advanced. In the present invention,
The present invention can be applied to both a conventional one-tube type X-ray CT apparatus and a multi-tube type X-ray CT apparatus. Here, the one-tube type will be described.

As shown in FIG. 1, the scan main body 1 has a rotating ring (not shown), and the X-ray tube 2 and the X-ray detector 3 are arranged to face the rotating ring. The X-ray tube 2 receives a high-voltage pulse that is periodically generated from a high-voltage generator (not shown) and emits X-rays toward the subject P. The X-rays that have passed through the subject P are detected by the X-ray detector 3. The output of the X-ray detector 3 is the DAS (data acquisiti
data collection system 4 called "on system",
The projection data storage device 5 is amplified, converted into a digital signal, and passed through a pre-processing unit (not shown) that performs various corrections.
Is sent together with data regarding the rotation angle (X-ray focal angle) of the X-ray tube 2 detected by an encoder (not shown).
The output of the data collection system 4 is called raw data,
The data immediately before the reconstruction processing that has been corrected by the preprocessing unit is called projection data.

An electrocardiogram electrode biological amplifier 6 is attached to the subject P, and the cardiac phase of the subject P (the cardiac phase at the time of the R peak of the electrocardiogram is 0% and the cardiac phase at the time of the next R peak is 100%).
%, During which the cardiac phase changes linearly with time). The cardiac phase signal captured by the electrocardiogram electrode biological amplifier 6 is converted into a digital signal by the AD converter 7 and sent to the projection data storage device 5.

The projection data storage device 5 stores the projection data in association with the focal angle data and the cardiac phase data when the projection data was collected.

In the actual examination, a contrast medium is injected into the subject. In the pre-injection stage, projection data for the mask image (hereinafter referred to as mask image projection data) is collected (pre-scan) over a plurality of heart beat periods, and in the post-injection stage, over a plurality of heart beat periods. The projection data for the subtracted image (hereinafter referred to as the subtracted image projection data) is collected (main scan), and two scans are performed before and after the injection of the contrast agent.

In the reconstruction of the subtracted image, the subtracted image projection data for 180 degrees + α (α is the view angle) necessary for half reconstruction are cut out one after another from a plurality of heartbeat periods, and are respectively reconstructed. For each subtracted image, the mask image that is the difference target is reconstructed individually. The mask image projection data for 180 degrees + α used for reconstructing each mask image is calculated in which range in a plurality of heartbeat periods. It is important from the viewpoint of reducing motion artifacts whether or not it is cut out from. In the present embodiment, with respect to the subtracted image projection data for a certain 180 ° + α period, the focal angle range and the cardiac phase range for a 180 ° + α period considered to be closest to each other in a specific distance function described later. Extract the mask image projection data. This extraction processing is performed by the ECG-gated projection data extraction unit 8, and details of this processing will be described later.

The reconstructing unit 9 sequentially reconstructs the subtracted image data on the basis of the 180 ° + α worth of subtracted image projection data cut out one after another from the plurality of heartbeat periods, and corresponds to each subtracted image. The mask image data is reconstructed from the mask image projection data of the period extracted by the ECG gated projection data extraction unit 8.

The subtracted image data and the mask image data thus reconstructed are subtracted by the difference calculation unit 10 between the images corresponding to each other. The series of subtraction image data generated by the difference is sent to the time density curve generation unit 11, and the time density curve data is generated for each pixel or each local.

FIG. 2 shows the relationship between CT projection data obtained by using the detector 3 and the electrocardiogram electrode biological amplifier 6 and electrocardiogram data (cardiac phase). In this example, the mask image projection data is photographed over a plurality of continuous heartbeat periods before the injection of the contrast agent, and the projection data corresponding to this period is recorded in the projection data storage device 6. This period is called a “mask image photographing period”. Further, approximately 250 ms near the R peak of the electrocardiogram during multiple heartbeat periods after the injection of the contrast medium.
The width data is photographed, and the projection data is similarly recorded in the projection data storage device 6. This period is called a "subtraction image capturing period".

Next, in the ECG gated projection data extraction unit 8,
Projection data for one heartbeat during the subtraction image capturing period (referred to as "subtraction image projection data") and projection data for the mask image reconstruction ("mask image capturing period") (Referred to as “projection data”). Here, the motion artifact is corrected by devising a method of extracting the mask image projection data.

The outline is as follows. The set of the focal angle in the imaging period of the subtracted image projection data and the phase (cardiac phase) in the cycle of the heartbeat is obtained, and the projection data closest to it is extracted from the projection data of the "mask image imaging period" to project the mask image. Output as data.

The "mask image projection data" and the "subtraction image projection data" are sent to the reconstruction unit 9 and the tomographic image data corresponding to each is reconstructed. At this time, a reconstruction method for reducing the artifact due to the pulsation of the heart is applied to either or both of the mask image and the subtracted image.

The outline of this reconstruction method is to include backprojection means for performing backprojection while changing the focal angle after subjecting projection data for a certain period used for reconstruction to known preprocessing such as filter calculation. , And in the back projection,
A reconstruction area moving / deforming means for moving or deforming the reconstruction area depending on the focal angle is provided, and after back-projecting for all focal angles, pseudo projection data is generated from the back-projected reconstruction area. Equipped with projection data generation means, provided with difference measurement means for calculating a metric value of the difference between projection data and pseudo projection data, and moving / deformed the focal angle and reconstruction area so that the difference calculated by the difference measurement means becomes small. It is equipped with an optimizing means for iteratively correcting the dependency between the two.

In the difference construction method, the cone beam projection data p (θ, φ) is multiplied by the weight w (θ, φ) to produce a value w (θ, φ) p (θ, φ) which is back projected. The back projection means is provided, and the weight w is w (θ, φ) + w (θ + 180
(° -2α, -φ) is an almost constant value k, the weights near the beginning and the end of the projection data are 0 or a value close to 0, and the center of the projection data (-φ-90 + α + β≤θ≤-
The weight around φ + 90 + α + β) is set to an almost constant value k, and the weight is prepared so as to be continuous over the entire period and the projection direction. θ is the focal angle, α is the cone angle, and φ of the projected straight line is the angle from the central direction of the cone angle.

The "mask image" and the "subtraction image" thus reconstructed are subjected to difference calculation in the difference calculation section 10 to create a subtraction image.

Now, the same (close) cardiac phase range described above
The subtraction method (1) using the mask image in the focal angle range will be described in detail. (Cardiac phase range, focal angle range) The projection data used for reconstructing the CT image is imaged while rotating the tube 2 and the detector 3 around the subject P, and therefore the focal angle at the time of imaging the view. Changes linearly with time from 0 to 360 degrees. This state is shown in FIG.

The change in the angle of the tube in the range between time ts and te is from Fs to Fe, and in the case of FIG. 3, it is 220 to 400 degrees (40 degrees in the next rotation period) (in FIG. 3). ,
(White frame). Subtraction image reconstruction is performed using the projection data in the range of 220 degrees to 400 degrees. When a CT image is reconstructed from projection data in this range, here, the focal angle range of the projection data used to reconstruct the subtracted image is 220 degrees to 4 degrees.
In the range of 00 degrees, the leading edge of the focal angle is 220 degrees and the trailing edge of the focal angle is 400 degrees.

Here, the term "cardiac phase" is used as the phase with respect to the pulsation of the heart at the time when a certain view is photographed. As described above, the cardiac phase at the time of the R peak of the electrocardiogram is 0% and the cardiac phase at the time of the next R peak is 100%, during which the cardiac phase changes linearly with time. The projection data in the time range from time ts to te used in the reconstruction of the subtracted image in FIG. 3 above corresponds to Ps to Pe when replaced with the cardiac phase (about 50% to 95% in FIG. 3). This is referred to herein as the cardiac phase range of projection data. Ps is the leading edge of the cardiac phase, and Pe is the trailing edge of the cardiac phase.

(The trailing edge of the cardiac phase of the subtracted image
Focal angle trailing edge) Let Pej be the cardiac phase trailing edge of one projection data dj among the subtraction projection data captured by using the shooting timing of FIG. 4, and let the focal angle range trailing edge be Fej. Trailing edge Fej and cardiac phase Trailing edge Pej
Are plotted at one point in the focal angle-cardiac phase plan view shown in FIG. The projection data extraction unit 8 extracts projection data in the range from the cardiac phase front edge Psj and the focal angle range rear edge Fej to (Fej, Pej) of the subtracted projection data dj.

(Focus Angle of Mask Image Projection Data-Cardiac Phase Trajectory) FIG. 6 is a plot of the trajectory seen from the tube rotation angle αc and the cardiac phase Pc during the mask image photographing period plotted on the focal angle-cardiac phase plane. is there. A locus for a period of about 6 heartbeats is plotted, during which the tube rotates 9 rotations + 50 degrees. These plotted loci are called mask image projection data loci. The trailing edge (Fej, Pej) of the subtracted projection data is also plotted at one point in the same plane.

(Extraction of Mask Image Projection Data) Here,
A point on the mask image projection data trajectory from the point (Fej, Pej)
The distance l to the point (Fc, Pc)²= K²α
(Fc-Fej)²+ K²p (Pc-Pej) ²Is defined as
One point (F on the mask image projection data locus where l is the minimum
ec, Pec) is determined.

It is possible to use a general optimization algorithm to determine one point on the mask image projection data locus for which the distance l is the minimum, but since there are many local minimums, the true minimum is always true. There is no guarantee that the value can be obtained. To always find the true minimum,
The following methods are effective.

When a mask image projection data locus is connected by a line having a focal angle of 0 ° (360 °) and a line having a cardiac phase of 0% (100%) and considered cyclically, one curve that can be expressed as a piecewise straight line Can be obtained. These straight lines are divided into 6 lines with a cardiac phase of 0% (100%). Considering this way, the range of the focal angle of the mask image projection data locus in the above figure is 45 [degree] to 995 [degree], the cardiac phase is 50% to 640%, and the focal angle is 0 ° to 360 °. Degree, the cardiac phase of 0 to 100% of the cardiac phase-focal angle can be drawn inside the plane of 60 planes. The trailing edge (Fej, Pej) of the subtracted projection data can also be plotted at 60 points, and the minimum distances for the six line segments are calculated from each of the 60 points, and the minimum value of those 360 minimum distances is obtained. By determining, it is possible to determine one point on the mask image projection data locus where l is the minimum.

In this method, it is necessary to obtain the minimum distance for all 360 combinations. However, the minimum distance for one combination can be obtained algebraically, so that the required time is very small and even if it is repeated 360 times. , It takes a short time. It is practical because there is a guarantee that the correct minimum distance can always be obtained.

The point thus determined is set as the trailing edge of the mask image projection data, and the point (Fsc, which is 180 degrees (actually 180 degrees + α)) traced back from this point is traced back from here (for example, 180 degrees (actually 180 degrees + α)). Psc) is used as the leading edge of the mask image projection data, and is extracted as projection data in the range of (Fec, Pec) and (Fsc, Psc).

(Creation of Subtraction Image) Image reconstruction is performed from the extracted mask image projection data and subtraction image projection data, and subtraction processing is performed to create a subtraction image. As another method, the difference may be subtracted from the projection data, that is, the mask image projection data may be subtracted from the subtraction projection data, and the result may be used for reconstruction. In this case, it is necessary that the mask image projection data and the subtracted projection data have the same rotation angle range. This corresponds to setting kp = 0. According to this method,
Since the reconstruction process that takes the longest processing time is reduced from twice to once, there is a feature that the time required to create a subtraction image can be saved.

(Variation) In the present embodiment, the mask image projection data in which the distance between the subtracted projection data and the trailing edges of the mask image projection data is the smallest is extracted. Alternatively, the mask image projection data having the shortest mutual distance divided at a certain ratio may be extracted. Further, the mask image projection data that minimizes the distance-square integration (using the ratio as an integration parameter) between the points divided at a certain ratio may be extracted. Also, in the present embodiment, k
Although α and kp are constants, they may be non-linear functions of the focal angle range and the cardiac phase, respectively.

Further, parfocal angle subtracted and real-time rotation speed control may be adopted. While capturing the subtracted image projection data, predict the leading edge / midpoint / trailing edge of the focal angle range at the next heartbeat from the heart rate and the rotational speed of the tube to find the minimum distance of the mask image projection data. The rotation speed is changed so that the distance becomes smaller. It is preferable to predict the focal angle up to a few heartbeats ahead and control the rotation speed so that the projection data locus is the best, that is, the minimum distance is the smallest.

As a result, the difference in the focal angle between the mask image and the subtracted image can be further reduced, and the motion artifact can be further reduced.

Furthermore, parfocal angle subtraction and registration may be adopted. The above process (1)
The mask image and the subtracted image obtained in
After performing alignment using an arbitrary registration technique, difference calculation processing is performed. Even if the cardiac phase between the mask image and the subtracted image is slightly different, there is an effect that an accurate difference calculation image can be obtained.

Further, it is effective to perform the registration of the subtracted images of the cardiac phase obtained by using the registration technique, in order to analyze the concentration of the contrast agent with high accuracy.

As a registration technique, it is preferable to apply a method called non-rigid registration for aligning while distorting an image.

In the above explanation, the focus angle range and the cardiac phase range are closest to each other between the subtracted image and the mask image, so that the artifacts due to the deviation between them are reduced. The correction method described in 1) relates to the reduction of motion artifacts in an image due to motion within the projection data acquisition period.

A method (2) of correcting the positional deviation in the image using the model in the reconstruction will be described. In this method,
In the process of reconstructing an image from the measured X-ray projection data, the motion of a subject (equivalently, the motion of the detection system) during the imaging period of the projection data for one image reconstruction is calculated using a model of the motion. A method of reconstructing an image in which motion artifacts are reduced during the period by predicting the direction and the amount and deforming / moving the reconstruction area based on the predicted motion at the same time will be described. Generally, a case of reconstructing a stereoscopic image by using a two-dimensionally arranged detector will be described, but a similar method can be applied to a case of reconstructing a single slice.

(Model of subject movement) For simplicity, the area of the volume to be reconstructed is a rectangular parallelepiped. Even if other regions such as spheres and cylinders are used, the principle of the reconstruction method described below does not basically change. Assuming two rectangular parallelepipeds that are doubly contained inside the rectangular parallelepiped, the three areas divided by the three rectangular parallelepipeds are areas A, B, and C. In FIG. 7, a rectangular parallelepiped region is shown as a rectangle for simplicity.

The area of the sum of the areas A, B and C is the reconstruction area. It is premised that the respective regions have different movements, but the illustrated regions are when the tube rotation angle is zero. The first model adopted is that the entire area A translates at a velocity va, and further the expansion velocities da1, da2, da3 in the directions of unit vectors ia, ja, ka orthogonal to each other about a reference point ca that is translated together.
It is supposed to expand with. Similarly, the area C is the velocity vc
It is assumed that expansion is performed at the expansion speeds dc1, dc2, and dc3 in the directions of the vectors ic, jc, and kc that are orthogonal to each other about the reference point cc that moves in parallel with each other. The translation speed has a unit of [mm / degree] here, and 1 mm / de
The speed of gree is 1 for every 1 [degree] rotation of the tube.
It means to move mm. The expansion rate has the unit of [% / degree], which means that the expansion rate of 1% / degree is 1
[Degree] Indicates that the area expands by 1% with each rotation. When the focal angle is θ, the point belonging to the region A located at the point r0 at the focal angle of 0 degree is at the next position x (θ).

[0046]

[Equation 1]

Here, using the operator Ta ^θ , the transformation of the above equation will be simply expressed as r = Ta ^θ r0. Such a conversion can be determined by a total of 12 parameters of va, ca, da1, da2, da3 and three angle parameters θa, φa, Ψa that determine the orthonormal bases ia, ja, ka. Similarly, the conversion of the points belonging to the region C is r
= Tc ^θ r0, which is determined by a total of 12 parameters of vc, cc, dc1, dc2, dc3, and θc, φc, Ψc.

The movement of the points belonging to the area B is close to the movement of the area A, and the movement of the points close to the area A is the movement of the points of the area C.
It is assumed that the movement is close to. This is achieved as follows using continuous weights w with values in the range 0-1.

[0049]

[Equation 2]

The weight w is defined in the area B, has a value of 0 at the boundary with the area A, has a value of 1 at the boundary with the area C, and changes continuously within the area. An example of weights indicating the parameter dependence of the region B with respect to the region C is shown in FIG.
Shown in. The change in weight in FIG. 8B represents the change on the broken line in FIG. In the rectangular parallelepiped area, the area B
The dependency rate (weight) of the parameter of the area B with respect to the parameter of the area C may be determined according to the distance from the boundary of the area A to the boundary of the area A. If the area has a spherical shape, the points having the same spherical coordinate values are associated with each other, or θ = 0.
The points closest to each other at the time of may be associated with each other.

In the above description, the rotation of the area was not taken into consideration, but it is easy to extend it to include the rotation movement.

(Separation of Known Parameter and Unknown Parameter) In the above model, the movement of a point belonging to any one of the area A, the area B, and the area C is represented by 24 parameters in total. These 24 parameters are divided into each direction component of three orthogonal axes, and the known parameter and the unknown parameter are divided into two.
Classify into one. The unknown parameter is a parameter determined based on the projection data so that the artifact due to the motion can be effectively removed. The known parameter is a value that is determined as a known value in advance, instead of being determined from the data. FIG. 9 shows a classification example.

(Setting of known parameters and initial value setting of unknown parameters, shape setting of areas A, B, C) Some of the known parameters are not values predetermined by the apparatus, but reference positions and directions of expansion, etc. There are some things that the operator should decide while checking the image. Further, the positions and sizes of the areas B and C are preferably determined while checking the image.

FIG. 10 shows an example in which some of the known parameters are set using the image reconstructed without using the motion artifact correction method according to this embodiment as a reference image. The image reconstructed without using the artifact correction method contains motion artifacts, but it can be sufficiently used as a reference image for setting and confirming the reference position of expansion and the area.

The position / shape of the boundary between the regions B and C is θ = 0.
The size and shape at the time of are displayed in the CT stereoscopic image, and the size and position can be changed on the screen. The area A is preset so as to include all structures around the subject such as a bed. It should be slightly smaller than the reconfigurable area of the device. θa,
φa and Ψa are three axes ia, ja, ka that represent the expansion direction.
Is determined by modifying θc, φc, Ψc are θ
Although it may be the same as a, φa, and Ψa, another axis may be displayed so that it can be set on the screen. Among the known parameters, the parameters other than those set in FIG. 9 are set to 0 here.

The initial values of unknown parameters can be set in the same manner. The arrow in the area C in FIG. 10 represents the parallel movement speed vc of the area C. This arrow can change its size and direction on the display,
Initial values of the first and second direction components of vc are set. The start point and the end point of the arrow correspond to the start point and the end point of the movement during the shooting period. When the set vector is V [mm], the parallel movement speed vc is set as follows.

[0057]

[Equation 3]

Fe-Fs [degree] is the focal angle range. The third direction component is a known parameter, and the value set on the screen is the set value of the known parameter. The expansion rate setting marker displayed in the figure represents the start point and the end point of the expansion during the imaging period. Using the marker length l, the expansion reference position and the marker distance L, the expansion coefficient is set as follows. Set the initial value of the rate. For reduction, multiply by -1.

[0059]

[Equation 4]

(Image Reconstruction and Determination of Unknown Parameter) Regions A, B, and C each include a large number of voxels,
The vector described for the pixel values of these voxels is x.
Let y be a vector in which the projection data p (θ, φ) is dispersed and arranged in one vertical column. The relation between x and y is y = Px using the matrix P
It can be expressed as. Note that P depends on unknown parameters. Let u be a vector in which all unknown parameters (here, three) are vertically arranged. By using a known reconstruction method such as a filtered back projection method, an estimated value xest of voxel pixel values can be obtained from the measured projection data ymes as xest = P ^T Fymes. P ^T represents a back projection calculation, and F represents a filter calculation. yest again from xest got from ymes
By performing projection like p = Pxest, it is possible to generate projection data yrep that is ideally very similar to ymes. However, if the subject is moving during the shooting period, motion artifacts occur in xest, and ymes and yrep do not match.
In particular, looking at the projection data in the portion where the opposite data exists, ymes has a difference between the opposite data, whereas yrep does not have a difference between the opposite data. Therefore, the squared error of ymes and yrep is increased by the value due to the motion artifact.

The reconstruction means according to the present embodiment uses the projection P for an arbitrary value of the parameter u representing the motion of the subject.
(U) or means for performing backprojection PT (u) is provided, and further the squared error of ymes and yrep,

[Equation 5]

Minimization means are provided to minimize As the minimization algorithm, various known methods can be applied. For example, the conjugate direction method (co
njugated irrection method) can be suitable. The u (find uest) finally obtained as a result of the minimization is
u is selected so that the squared error of ymes and yrep = Pxest is minimized. If there is a movement of the subject during the shooting period and there is a discrepancy in the opposite data of ymes,
In yrep, u can be adjusted so that the discrepancy of the opposite data occurs in the same manner, which is the uest obtained by the minimization. Therefore, the artifacts due to the motion included in the image data xcmp = P ^T (uest) Fymes reconstructed using uest are greatly reduced.

(Image Creation and Presentation of Output Image) The image data xcmp obtained by the above method is a set of pixel values of a plurality of voxels arranged at specific positions in the areas A, B and C. . However, the regions A, B and C have movements such that their position and shape are deformed during the rotation of the tube. Therefore, it cannot be presented as an image unless the rotation angle of the tube is determined. For example, if you want to create an image with a focal angle θ = 0 exactly in the middle of the shooting start angle and the end angle, θ =
Using the positions and shapes of the regions A, B, and C at 0, the image is resampled to the pixel values of voxels arranged at equal intervals in the three directions of the vertical and horizontal depths. However, if voxels are arranged in advance so that the voxels are evenly spaced at the time of θ = 0, it is not necessary to actually resample the image at θ = 0. This volume data is displayed using volume rendering or MPR. By changing the value of θ and executing the same procedure, it becomes possible to observe an image at an arbitrary focal angle or create a moving image for observation.

Although the above description relates to the correction of the motion artifact in the image, the similar method is used to correct the positional deviation due to the body movement or the tissue movement between the time-series images. You can also For example, an actually measured time-density curve is generated from a time-series image captured in time series. Then, the point after the deformation movement of the point in the time-series image is calculated based on the deformation movement parameter related to the temporal deformation / movement of the tissue or the like. An evaluation function that calculates the difference between the time-series image and the time-series image after the deformation movement using the deformation movement parameter, and that indicates the degree of agreement between the time-series image and the time-series image after the deformation movement based on the calculated difference. Is calculated.
The deformation movement parameters are optimized so as to minimize or maximize the evaluation function. By deforming and moving the image using this deformation moving parameter, it is possible to reduce the positional shift due to the body movement or the movement of the tissue between the time-series images.

As a variation of the motion compensation reconstruction, in FIG. 9, all the third direction components such as velocity, position, expansion coefficient, etc. are known. It can image a single slice or a very small number of slices. This is because it is assumed that CT is used. The first and second directional components correspond to two orthogonal directions in the plane of the slice, and the third directional component corresponds to a direction orthogonal to the slice, but the movement of the third directional component corresponds to these fractions. This is because CT cannot estimate the slice. In recent years, the development of X-ray CT apparatuses capable of simultaneously capturing many slices such as 16 rows and 256 rows has been reported. If these X-ray CT apparatuses are used, the parameters in the direction orthogonal to the slices are unknown, and these directions are also unknown. It is also possible to correct the movement with respect to. Since many of the actual motion artifacts are caused by the motion in the direction orthogonal to the slice, if motion compensation in this direction is possible, the motion artifacts can be further reduced.

In order to reduce motion artifacts due to motion in the slice plane, it is necessary to accurately estimate motion in these directions. For this purpose, it is desirable that the range of the focal angle used for the motion estimation is larger than 180 ° + fan beam angle, and ideally, it is about 270 ° as shown in FIG. 180 °
If it is a degree, the projection line of the opposite data at the first focus position of the angular range and the projection line of the opposite data at the last focus position have very close directions, and both are approximately orthogonal to the projection line. Only the movement in the direction can be corrected. However, if it is close to 270 °, both of them (projected straight lines of the opposing data at the first and last focus positions) become close to a right angle.
It is possible to correct movements in different directions between the first and last facing data at the focus position. However, in the actual reconstruction, projection data of 180 ° + fan beam angle may be present. Therefore, the following configuration can be considered.

First, using projection data close to 270 °,
The motion parameters are estimated by the method already described.
After that, projection data in an angle range narrower than that (for example, 180 ° + fan beam angle) is extracted, and reconstruction is performed while performing motion correction using the estimated motion parameter. The first reconstruction involves an iterative modification that estimates the motion parameters, whereas the final reconstruction uses the already obtained motion parameters to perform the one-time reconstruction.

By doing so, it becomes possible to effectively correct the movement in the two directions within the slice plane, and finally it is possible to reconstruct from the projection data in a narrow range, and to improve the accuracy of the movement correction. As a result, it is possible to improve the time resolution, and it is possible to more effectively remove the motion artifact.

Next, a motion artifact correction method (3) using weighting of projection data will be described. 36 tubes
When shooting with 0 degree rotation, Japanese Examined Patent Publication 04-42011
The motion artifact correction method described in Japanese Patent Publication can be applied. However, when it is desired to image a moving tissue with a high temporal resolution, such as an image of the heart, it is necessary to perform reconstruction using projection data in an angle range smaller than 360 degrees. The method of the above document can be applied to the case of an angle range smaller than 360 degrees, but is not optimized for the case of a small angle range of about 180 degrees.

In this embodiment, an artifact reducing method optimized for projection data in an angle range of 180 degrees + a little larger than the fan beam angle will be described. The method is applicable to both reconstruction of a mask image and reconstruction of a subtracted image. Further, it is also possible to apply it to simple projection data without assuming subtraction, and it is effective in providing an image in which artifacts due to motion are reduced.

The angle of the leading edge of the angle range of the projection data is F
Let s and the angle of the trailing edge be Fe. For simplicity, in the following description, the rotation angle will be considered by a measuring method in which the rotation angle is rotated by c = (Fe−Fs) / 2. In such a measuring method, as shown in FIG. 11, the focal angle range is fs = Fs-c, fe.
= Fe-c Where 180 + α + β [de
Consider reconstruction from projection data taken in the angle range of [gree]. α is the fan beam angle. In normal half reconstruction, the rotation range required for reconstruction is 180 + α
However, here, a case is considered in which generally data having a large angle β is used.

As can be seen from FIG. 12, fs = -90-α / 2-β fe = 90 + α / 2 + β fe-fs = 180 + α + β. When the rotation angle of the tube is θ and the angle clockwise from the center of the projection angle of the fan beam is φ, one projection line is represented by (θ, φ). Since the tube rotation range is from fs to fe, fs ≦ θ ≦ fe. Further, since the fan beam angle is α, −α · 2 ≦ φ ≦ α / 2. For some projection lines within this range there are practically the same opposing projection lines that are opposite in orientation only. Projected line (θ,
The opposite projection straight line of (φ) is the case where θ is a positive value (θ-2φ + 1
80, -φ), when θ is a positive value (θ-2φ-180,
-Φ). The projection values of the opposing projection lines should be the same value if there is no influence such as displacement. If the rotation angle range of the opposite projection line is between fs and fe, the projection value of the opposite projection line is obtained by photographing.

The range of (θ, φ) where the opposing projection straight lines exist in the range of fs to fe is shown by the diagonal lines in the central portion of FIG. The projected values of (θ, φ) in this range are opposite 2
This means that one value is being measured. In contrast, Figure 1
Areas surrounded by thick lines on both sides of 3 are outside the focal angle range and projection data is not measured, but the opposite projection straight line is
It exists in the focal angle range (hatched area).

Therefore, if the measured projection data is substituted, the projection data for 360 degrees will be obtained,
If the subject does not move during shooting, reconstruction can be performed from the 360-degree data thus aligned.
However, if the subject moves, the projection data adjacent to each other at the boundary between the shaded area and the white area with a thick frame is about 180 ±.
This means that the shooting time is shifted by the time corresponding to the tube rotation of α. Therefore, if there is a motion in the subject, data discontinuity occurs and streak artifacts appear in the reconstructed image.

On the other hand, in this embodiment, when reconstruction is performed using a method such as convolution back projection, the weight w (θ, φ) is given to the projection data (θ, φ) during back projection. Reconstruction is performed using the multiplied data. This weight is selected so that w (θ, φ) + w (θ + 180-2α, −φ) = k. This corresponds to weighting and replacing the opposite data with thin diagonal lines.

If the weight w is set under the following conditions, the discontinuity of the data is eliminated, and the artifact due to the movement is less likely to occur.

When the weights at the beginning and the end of the projection data are 0, w (-90-α / 2-β, φ) = 0 w (90 + α / 2 + β, φ) = 0 Oblique inside the thin shaded area When the weight of the boundary part of k is k, w (θ, −θ + 90−α−β) = k w (θ, −θ−90 + α + β) = k, and the weight of the central parallelogram region is k. Weights are continuous In the present embodiment, two weight examples are shown in FIG.
It shows using (a) and FIG.14 (b). In these figures, a region having a constant weight is represented by a white region, and a region having a gradient is represented by a diagonal line. The weight of the white thick line area is 0, k
= 2 is selected, the weight of the diagonal white area in the center is 2. In FIG. 14A, the weight of the shaded area continuously changes between 0 and 2. It is easiest to make this change a first-order number with respect to θ. Considering the entire trapezoidal region, this function is a bi-hour number. In addition to this, if the gradient at the boundary is set to 0 using a non-linear function such as a quadratic function of φ or a trigonometric function, it is more effective in reducing artifacts due to motion.

In FIG. 14B, the weight changes continuously between 0 and 1 in the dark shaded area, and the weight changes continuously between 1 and 2 in the light shaded area. As in the first explanation, the change may be a linear function or a non-linear function with respect to θ. The second weight is characterized in that the weight of the thick thick line region is constant with respect to φ.
Therefore, the same weight can be applied to the entire view in the dark shaded area, which is a feature that the configuration is easy. Further, instead of changing the weight, the X-ray output can be changed to obtain the same effect. Generally, when the movement-induced artifact correction is performed, the noise of the image increases although the exposure dose does not change. However, the movement-induced artifact correction is performed by changing the X-ray output instead of changing the weight. Therefore, the noise of the image is increased, but at the same time, the exposure amount can be reduced. In general, the weight is substantially w
In order to obtain (θ, φ), the weight actually applied is w
(Θ, φ) = w (θ, φ) / g (θ).
In the second weighting, w'is set to a constant value in the dark shaded area, and it is not necessary to actually perform weighting, so that weighting by the output of X-rays can be easily performed. However, even with the first weight, for example, g (θ) = w (θ, 0), w ′ (θ, φ) = w (θ, φ)
It is possible to use the weight by the X-ray output like / w (θ, 0).

As described above, the "subtraction image" captured by the above-described series of flows has the "cardiac phase range" and the "focal angle range (see Embodiment 1)" which are close to the "subtraction image projection data". It is created by creating "mask image projection data" having "," and performing subtraction using the tomographic image reconstructed from both projection data. "Focal angle range" in the ECG sync data extraction unit
Two projection data (“mask image projection data” and “subtraction image projection data”) having the same or close values are extracted and a subtraction image is created using these two projection data. Motion artifacts whose patterns depend on the "focal angle range" are canceled out, and "subtraction image"
Has the effect of reducing motion artifacts contained in.

Further, since the reconstructing section uses a reconstructing method for reducing motion artifacts as described in the second and third embodiments, further reduction of motion artifacts is realized.

The artifact reducing methods (1), (2), and (3) can reduce these artifacts, and
It is also applicable to half reconstruction. By applying one or more of these techniques in combination, it is possible to capture a subtraction image with high accuracy and high time resolution. Therefore, it can be applied to the imaging of the heart that requires high temporal resolution, and it is possible to greatly reduce the artifacts due to the movement of the heart that could not be avoided with conventional cardiac CT images, and to reduce the cardiac flow such as myocardial blood flow. It is characterized by being able to provide useful information for diagnosis of diseases.

(Modification) The present invention is not limited to the above-described embodiment, but can be variously modified and implemented at the stage of implementation without departing from the scope of the invention.
Further, the above embodiment includes various stages,
Various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, some constituent elements may be deleted from all the constituent elements shown in the embodiment.

For example, in the above description, an example of the X-ray CT apparatus has been described, but an image processing apparatus that processes projection data collected by the X-ray CT apparatus, that is, projection data of a mask image collected by the X-ray CT apparatus. And projection data for the subtracted image are input and stored, and the effects of tissue motion artifacts are executed by executing the above-mentioned processes (1), (2), and (3) using the projection data. It is possible to configure the image processing device that generates a subtraction image with a small size independently of the scanner unit.

[0084]

According to the present invention, it is possible to create a subtraction image in which the influence of artifacts due to tissue movement is small.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of an X-ray CT apparatus according to this embodiment.

FIG. 2 is a diagram showing a relationship between an imaging timing and a cardiac phase in the present embodiment.

FIG. 3 is a diagram showing a relationship between a focal angle and a cardiac phase in the present embodiment.

FIG. 4 is a diagram showing a cardiac phase trailing edge Pej and a focal angle range trailing edge Fej of certain projection data dj in the present embodiment.

FIG. 5 is a diagram showing positions corresponding to a focal angle range trailing edge Fej and a cardiac phase trailing edge Pej of the subtracted image projection data plotted on the focal angle-cardiac phase plan view in the present embodiment.

FIG. 6 is a view showing a focus angle of the mask image projection data closest to the focal angle range trailing edge Fej and the cardiac phase trailing edge Pej of the subtracted image projection data in the present embodiment. Range trailing edge αec and cardiac phase trailing edge P
Diagram showing ec.

FIG. 7 is a diagram schematically showing a plurality of virtual regions for correcting misregistration in an image in the present embodiment.

8 is a diagram showing a spatial change in the dependency (weight) of the movement / deformation parameter of the region B on the regions A and C of FIG. 7 in the present embodiment.

FIG. 9 is a diagram showing known / unknown classification for each orthogonal three-axis direction component of movement / deformation parameters in the present embodiment.

FIG. 10 is a diagram showing the areas A, B, and C of FIG. 7 in the present embodiment.
FIG. 6 is a diagram showing an example of shape setting of FIG.

FIG. 11 is a supplementary diagram for explaining half reconstruction in the present embodiment.

FIG. 12 is a supplementary diagram for explaining half reconstruction in the present embodiment.

FIG. 13 is a supplementary diagram for explaining half reconstruction in the present embodiment.

FIG. 14 is an explanatory supplementary diagram of motion artifact correction using weighted correction of projection data in the present embodiment.

FIG. 15 is a diagram showing a preferable range of a focal angle used for motion estimation in the present embodiment.

[Explanation of symbols]

1 ... Scanner body, 2 ... X-ray tube, 3 ... X-ray detector, 4 ... Data collection system, 5 ... Projection data storage device, 6 ... Electrocardiogram electrode biological amplifier, 7 ... AD converter, 8 ... Temple synchronized projection data extraction unit, 9 ... Reconstruction Department, 10 ... Difference calculation unit, 11 ... Time concentration curve generation unit.

Continued front page    (72) Inventor Hitoshi Yamagata             1385 Higashiyama, Shimoishi, Otawara, Tochigi Prefecture             Toshiba Nasu factory inside F-term (reference) 4C093 AA22 CA03 DA02 FD12 FD13                       FF27 FF34                 5B057 AA09 BA03 CA08 CB08 CH01                       DC22

Claims (18)

[Claims] 1. A scanner unit for detecting projection data on a subject, a control unit for controlling the scanner unit to collect projection data for a mask image and projection data for a subtracted image. A data extraction unit that extracts specific projection data from the projection data for the mask image based on the focal angle range and the cardiac phase range of the projection data for the subtraction image, and for the subtraction image A reconstruction unit that reconstructs subtracted image data from projection data and reconstructs mask image data from projection data for the extracted mask image, and subtracts the mask image data from the subtracted image data. An X-ray CT apparatus comprising a difference calculator. 2. The data extraction unit determines a linear combination of leading and trailing edges of a focal angle range of projection data for the subtracted image and a linear combination of leading and trailing edges of a cardiac phase range. Means for determining the positions of the focal angle and the cardiac phase closest to the linear combination of the determined cardiac phase range and the focal angle range on the X-ray focal locus of the projection data for the mask image. According to the determined focal angle and cardiac phase, the leading edge and the trailing edge of the focal angle range required to reconstruct the mask image data are determined, and the projection data collected in this range is used for mask image reconstruction. X-ray CT apparatus according to claim 1, further comprising means for extracting as projection data for 3. The data extraction unit determines a focal angle of a leading edge or a trailing edge of a focal angle range of projection data for the subtracted image and a cardiac phase of a leading edge or a trailing edge of the cardiac phase range. Means for performing the X-ray focus movement trajectory of the projection data for the mask image with respect to the determined focus angle and cardiac phase,
Means for determining the closest focal angle and cardiac phase on a specific distance function, and within the focal angle range required for the mask image data reconstruction with the determined focal angle and cardiac phase as the leading edge or trailing edge. 2. The X-ray CT apparatus according to claim 1, further comprising: means for extracting the projection data of 1) as projection data for reconstructing the mask image data. 4. The specific distance function is l ² = ka ² (Fc-F) ² + kp ² (Pc-P), where l is a distance and F is a focal angle of projection data for the subtracted image. Fc is a point on the focal angle locus of the projection data for the mask image, P is the leading or trailing edge of the cardiac phase range of the projection data for the subtracted image Heart phase,
Pc is a point on the cardiac phase trajectory of the projection data for the mask image, ka is a weighting factor that determines the contribution rate of the focal angle distance to l, and kp is a weighting factor that determines the contribution rate of the cardiac phase distance to l. The X-ray CT apparatus according to claim 3, wherein the X-ray CT apparatus is provided. 5. The X-ray CT apparatus according to claim 4, wherein kp = 0. 6. The X-ray CT apparatus according to claim 4, wherein ka and kp are functions that change depending on the focal angle range and the cardiac phase range, respectively. 7. A scanner unit for detecting projection data on a subject, a backprojection unit for backprojecting the projection data while changing the X-ray focal angle, and a reprojection unit for reprojecting the projection data depending on the X-ray focal angle. Reconstruction area moving / deformation means for moving or deforming the composition area, and projection data for back-projecting the projection data for all focal angles, and then generating pseudo projection data from pixel value data of the back-projected reconstruction area. Generation means, difference measurement means for calculating a difference between the projection data and the pseudo projection data, and dependence of movement / deformation of the reconstruction area on the X-ray focal angle so as to minimize the calculated difference. X is characterized by comprising: optimization means for iteratively correcting the sex; and means for generating image data according to the dependency when the difference is minimized.
X-ray CT equipment. 8. The X-ray CT apparatus according to claim 7, wherein the reconstruction area moving / deforming means divides the reconstruction area into a plurality of areas and gives a movement parameter and a deformation parameter for each area. . 9. The reconstructed area moving / deforming means depends on a moving parameter and a deforming parameter for each point in at least one area of the plurality of areas depending on a moving parameter and a deforming parameter for at least two other areas. The X-ray CT apparatus according to claim 8, wherein 10. A movement parameter and a deformation parameter for each point in the one area are set depending on a distance from a boundary of the other area.
The described X-ray CT apparatus. 11. The X-ray CT according to claim 8, wherein the outermost reconstruction area of the plurality of areas is given in a shape of a rectangular parallelepiped, a rectangle, an ellipsoid, an ellipse, a sphere, or a circle.
apparatus. 12. Each area other than the reconstruction area comprises:
The X-ray CT apparatus according to claim 11, wherein the X-ray CT apparatus has any one of a rectangular parallelepiped shape, a rectangular shape, an ellipsoidal shape, an ellipse, a sphere, and a circle. 13. The movement parameter includes a parallel movement speed parameter, and the deformation parameter includes an expansion reference point,
9. The X-ray CT apparatus according to claim 8, wherein each parameter of expansion rate and expansion direction is included. 14. The difference is a sum of a squared error between the projection data and the pseudo projection data and a penalty value calculated by referring to a voxel value used to generate the projection data. The X-ray CT apparatus according to claim 7, which is calculated. 15. The X-ray CT apparatus according to claim 7, wherein the optimizing means iteratively corrects the dependence of the movement / deformation of the reconstruction area on the X-ray focal angle by the conjugate direction method. . 16. The optimization means optimizes at least one unknown parameter of the parallel movement speed parameter, the expansion reference point parameter, the expansion speed parameter, and the expansion direction parameter as a variable, and a predetermined value. 14. The X-ray CT apparatus according to claim 13, wherein is set as an initial value of the unknown parameter, and predetermined numerical values are applied to the remaining known parameters. 17. A means for inputting projection data for a mask image and projection data for a subtracted image, based on a focal angle range and a cardiac phase range of the projection data for the subtracted image. A data extraction unit that extracts specific projection data from the projection data for the mask image, and reconstructs subtracted image data from the projection data for the subtracted image and for the extracted mask image An image processing apparatus, comprising: a reconstruction unit that reconstructs mask image data from the projection data of 1. and a difference calculation unit that subtracts the mask image data from the subtracted image data. 18. A backprojection means for backprojecting projection data on a subject while changing an X-ray focal angle, and a reconstruction area for moving or deforming the reconstruction area depending on the X-ray focal angle during the backprojection. Moving and deforming means, projection data generating means for back-projecting the projection data for all focal angles, and then generating pseudo-projection data from pixel value data of the back-projected reconstruction area, the projection data and the pseudo-data. Difference measuring means for calculating a difference from projection data, and optimizing means for iteratively correcting the dependence of movement / deformation of the reconstruction area on the X-ray focal angle so as to minimize the calculated difference, An image processing apparatus, comprising: a unit that generates image data according to the dependency when the difference is minimized.