WO2007114470A1 - X-ray ct scan simulator device, x-ray ct device and x-ray ct scan simulator program - Google Patents

Abstract

A high accuracy simulation image is provided without preparing a mass of sample images or noise pattern images and whether there is a history or not in which an examinee was photographed in the past. An image in the past of an examinee or an original image of a photographed phantom of a human body is input (S201-203), the body thickness of the examinee is estimated (S204) and an approximation mode is calculated on a basis of a water equivalent thickness of the estimated body thickness (S205). A noise amount added to the original image is calculated based on a difference between an image noise amount of the original image and the target image noise amount (S208). Based on the approximation model, standard projection data, which are projection data of the approximation model without noise, and added projection data, which are the standard projection data to which the noise amount added to the original image is added, are made out (S209). Further, based on the standard projection data and the added projection data, a noise image including a noise amount added to the original image is reconstructed (S210) and the same is added to the original image to make out and display a simulation image (S211).

Description

 Specification

 X-ray CT scan simulator device, X-ray CT device, and X-ray CT scan simulator program

 Technical field

 TECHNICAL FIELD [0001] The present invention relates to an X-ray CT scan simulator apparatus, an X-ray CT apparatus, and an X-ray CT scan simulator program, and in particular, a technique useful for simulation of image noise and pre-examination of appropriate imaging conditions. It is about.

 [0002] This application is a patent application claiming priority based on Japanese Patent Application No. 2006-103547 and Japanese Patent Application No. 2007-059408 based on Japanese Patent Law. 2 This application is incorporated by reference to enjoy the benefits of 007-059408.

 Background art

 [0003] The conventional X-ray CT system uses X-ray source power to detect X-rays radiated on a fan with a single-row detector. In recent years, X-rays radiated to a cone type are detected in multiple rows. Detect multi-slice CT in practical use. Not only the number of detectors but also the thinning is remarkable.

 [0004] Technological innovations in X-ray CT systems are not limited to detectors, and the speed of gantry rotation speed is increasing, making it possible to collect a wide range of data in a short time. Since it was possible to scan a much wider range than before, the increase in exposure dose was noticeable when taking images with the same tube current as before. Even when the imaging range is relatively narrow, the imaging time is long like CT Perfusion and ECG, so the local dose is high and the number of examinations is increasing.

 [0005] For the above reasons, it is important to reduce exposure by low-dose imaging such as low tube voltage imaging and low tube current imaging, but low-dose imaging causes an increase in image noise. In addition, since image noise depends on the slice thickness, photographing with a thin slice thickness causes an increase in image noise.

[0006] In order to obtain a uniform image quality regardless of the body shape of the subject while suppressing unnecessary X-ray exposure, an automatic X-ray exposure mechanism (Auto Exposure Control: AEC) as shown in Patent Document 1 The so-called technology has been put into practical use. In AEC, the target image SD is usually specified by the operator, and the tube voltage and tube current values are automatically set so as to achieve this target SD. [0007] How many SD images can provide an image suitable for diagnosis depends on the type of disease. Even for the same disease, the required image quality differs depending on the purpose of the examination (whether it is a medical examination or a close examination). For this reason, it is not easy to set optimal imaging conditions according to the purpose of the disease and the subject while the exposure dose is suppressed. Therefore, it is clinically useful to know what kind of image can be obtained under the imaging conditions before the examination, and a simulation technique for examining the optimal imaging conditions has been proposed (Patent Document 2, Patent Document). 3).

 [0008] Patent Document 1: Japanese Patent Application Laid-Open No. 2004-073865

 Patent Document 2: JP 2004-329661 A

 Patent Document 3: Japanese Patent Application Laid-Open No. 2004-57831

 Disclosure of the invention

 Problems to be solved by the invention

[0009] With the technology disclosed in Patent Document 1, an image with a desired noise amount and SD value can be obtained. There is a problem that it is not easy to set an optimal target SD value to obtain an image suitable for the inspection purpose while suppressing unnecessary exposure, and it requires a wealth of experience and advanced knowledge.

 [0010] With the technique disclosed in Patent Document 2, it is possible to simulate what kind of image is obtained under an arbitrary shooting condition before shooting. Compared with the technique disclosed in Patent Document 1, the setting of the optimum shooting conditions is simplified because the image quality can be visually confirmed while viewing the simulation image displayed on the screen. However, since the technique disclosed in Patent Document 2 is required to prepare sample images with various SDs for each imaging region in advance, there is a huge amount of sample images to be prepared. Go up. If the SD image expected from the shooting conditions is not in the sample image, a simulation image is also created by interpolation processing for two image forces with SD. For this reason, the error may increase depending on the shooting conditions, and there is a problem that the reliability of the simulation accuracy may be lacking.

[0011] In the technique disclosed in Patent Document 3, a simulation image is created by adding quantum noise and electrical noise to the measured projection data and performing reconstruction. Therefore The interpolation processing is not included as in the technique disclosed in Patent Document 2, and it is considered that the accuracy of the simulation is improved. However, the creation of a simulation image requires actually measured projection data, which is a problem that can only be applied when there is a history of photographing the subject in the past.

 [0012] In addition, in the technique disclosed in another embodiment of Patent Document 3, a method of adding a noise pattern image that has been created in advance to a reconstructed image is shown. In this method, it is necessary to prepare various noise pattern images in advance according to the shooting conditions. Each shooting parameter such as tube voltage, tube current, and FOV has many patterns, so a huge amount of noise pattern images must be prepared to support all shooting conditions! / There are ヽ and ヽ ぅ problems.

 [0013] An object of the present invention is to prepare an enormous sample image and noise pattern image. An X-ray CT scan simulator device capable of highly accurate simulation regardless of the presence or absence of a history of imaging a subject. To provide an X-ray CT system and an X-ray CT scan simulator program. Means for solving the problem

 In order to solve the above problem, an X-ray CT scan simulator device according to the present invention includes an image storage unit that stores a reference image, a target noise value setting unit that sets a noise target value of a desired image, Noise image generation means for generating a noise image based on the set target noise value, simulation image generation means for generating a simulation image by synthesizing the generated noise image and the reference image, and the simulation And display means for displaying an image.

[0015] In addition, the X-ray CT apparatus according to the present invention includes an X-ray source that irradiates a subject with X-rays, and an X-ray detection that detects X-rays that are disposed opposite to the X-ray source and transmitted through the subject. An X-ray source, a rotating device that mounts the X-ray detector and rotates around the subject, and the subject based on transmitted X-ray doses in a plurality of directions detected by the X-ray detector An X-ray comprising: an image reconstruction device that reconstructs a tomographic image of the image; an imaging condition input device that inputs the X-ray irradiation conditions and image reconstruction conditions; and an image display device that displays the tomographic image A CT apparatus, further comprising the X-ray CT scan simulator apparatus. [0016] The X-ray CT scan simulator program according to the present invention includes a step of acquiring a reference image, a step of setting a noise target value of a desired image, and a noise image based on the set target noise value. And generating a simulation image by synthesizing the generated noise image and the reference image, and outputting the simulation image.

 The invention's effect

 [0017] According to the present invention, in the X-ray CT scan simulator, by simulating what kind of image is obtained under the condition of the target SD value regardless of the presence or absence of past imaging history, If the optimum shooting conditions can be examined before measurement, it is effective.

 [0018] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

 <First Embodiment>

 [Hardware configuration]

 FIG. 1 is a diagram showing a preferred embodiment of an X-ray CT apparatus equipped with an X-ray CT scan simulator according to the present invention. An X-ray CT apparatus 1 equipped with an X-ray CT scan simulator according to the present invention includes a gantry 2, and the gantry 2 includes an X-ray source 3, a collimator 4, and a detector array 5 located on the opposite surface of the gantry 2. Have.

 [0020] The detector array 5 is formed by a detector element 6 that detects X-rays transmitted through a subject on a bed (not shown). The detector elements 6 are arranged in rows or in a plurality of parallel rows. Each detector element 6 generates an electrical signal representing the intensity of the incident X-ray beam, in other words, attenuation when the X-ray beam passes through the subject.

 [0021] X-ray projection data is collected by rotating the gantry 2 around the rotation center 8 in a state where X-rays 7 are irradiated from the X-ray source 3. The country 2 and the X-ray source 3 are controlled by the control unit 9 of the X-ray CT apparatus 1.

 The control unit 9 includes an X-ray control unit 10, a gantry control unit 11 and a DAS (data acquisition system) 12, and an analog signal from the detector element 6 is converted into a digital signal by the DAS 12. The digitized X-ray data is reconstructed by the reconstruction means 19 in the arithmetic processing means 13 and stored in the storage means 22 in the arithmetic processing means 13.

The arithmetic processing means 13 is an arithmetic processing device such as a computer, and obtains the body thickness of the subject. Body thickness estimation means 14, approximate model calculation means 15 that obtains a water phantom that has the same amount of X-ray absorption as the subject by converting the body thickness to water equivalent thickness, and image SD that obtains the image SD in images taken in the past Calculation means 16, addition noise quantity calculation means 17 for determining the amount of noise to be added to the original image (also referred to as reference image) in order to create a desired SD image, and approximation with an X-ray absorption equivalent to the subject Water approximation model projection data creation means 18 for generating model projection data, reconstruction means 19 for image reconstruction from projection data, approximation model projection data with added noise and projection data for approximation model without noise addition Noise image creation means 20 that obtains a noise image, simulation image creation means 21 that obtains a simulation image by adding the noise image to the original image, and a hard disk Each storage means 22, a temporary storage means 23 such as a memory, and an input means 24 such as a mouse and a keyboard are configured.

 [0024] Further, at least one of a digital signal processor (DSP), a micro processor unit (MPU), and a central processing unit (CPU) is provided. The image display means 25 is a display device such as a display integrated with or independent from the arithmetic processing means 13. In FIG. 1, the control unit 9 and the arithmetic processing means 13 are separated, but both may be integrated. The reconstruction means 19 may be an arithmetic unit independent of the arithmetic processing means 13.

 [0025] [Configuration of X-ray CT scan simulator]

 FIG. 2 is a configuration diagram of the X-ray CT scan simulator 200 of the present embodiment. The X-ray CT scan simulator 200 includes a storage unit 22 that is an image storage unit, an input unit 24 that is a target noise value setting unit, a noise image generation unit 30, and a simulation image generation unit 21.

 The storage unit 22 stores a reference image that serves as a reference for the simulation image created by the X-ray CT scan simulator 200. The reference image is a past image obtained by CT imaging of a subject in the past, or a human phantom image obtained by CT imaging in advance of a human phantom that faithfully reproduces the internal tissue of the human body. Sufficient X-ray dose should be used to capture human phantom images so that clear images can be obtained.

 [0027] The input unit 24 is for inputting a target noise value, and is specifically a keyboard, a mouse, or the like.

[0028] The noise image generation means 30 performs noise based on the target noise value input by the input means 24. Generate and output the image. The noise image generating means 30 includes a body thickness estimating means 14, an approximate model calculating means 15, an approximate model projection data creating means 18, an image SD calculating means 16, an added noise amount calculating means 17, and a noise image creating means 20.

[0029] The body thickness estimation means 14 acquires the body thickness of the subject. The body thickness may be manually input by the operator, or the scanogram force may be obtained. If the reference image is a past image, it may be automatically estimated by a method described later.

[0030] The approximate model calculating means 15 calculates an approximate model based on the body thickness estimated by the body thickness estimating means 14. The approximate model is a model approximated with water so as to have the same amount of X-ray absorption as the subject (hereinafter referred to as water approximate model). X-ray absorption equivalent to the subject obtained from the average CT value of the subject Even a model with a virtual substance with a quantity (hereinafter referred to as an average CT value substance approximation model). A method for calculating the approximate model will be described later.

The approximate model projection data creating means 18 creates projection data by irradiating the approximate model calculated by the approximate model calculating means 15 in a simulated manner with X-rays. A method for creating projection data will be described later.

 [0032] The image SD calculation means 16 calculates the noise amount of the reference image. The method for calculating the noise amount of the reference image will be described later.

Based on the target noise value set by the input unit 24 and the noise amount calculated by the image SD calculation unit 16, the addition noise amount calculation unit 17 calculates a noise amount to be added to the reference image.

 [0034] The noise image creating means 20 creates a noise image by reconstructing the added projection data obtained by adding the amount of noise to be added to the approximate model projection data.

 The simulation image creating unit 21 synthesizes the noise image generated by the noise image generating unit 30 and the reference image to create a simulation image.

 [0036] [Process flow]

FIG. 3 is a process flow showing a method for creating a simulation image in the present embodiment. First, in the subject to be simulated, a search is made as to whether or not there is a history of imaging the same part in the past (step S201), and if there is an imaging history, based on the image (past image) taken in the past. Set to image (step S202). [0037] When there is no shooting history, an image obtained by shooting a phantom (human phantom) that faithfully reproduces the internal composition of the human body is set as the original image (step S203). Prepare an image of the human phantom in advance. In the publicly known example, it is necessary to prepare various SD images for human body phantoms for each imaging region, but in the present invention, images captured at a sufficient dose so that a clear image can be obtained for each region. In other words, it is enough to prepare one small SD image for each part.

 [0038] As for the FOV, it is necessary to take a picture with a representative FOV for each part and scale it appropriately to match the FOV in the simulation. Therefore, it is not necessary to prepare a huge amount of human phantom images for each SD and FOV as in the known example.

 Next, the body thickness of the subject is automatically estimated (step S204). The body thickness may be obtained from a scanogram, or a method as described later may be used. Although the operator may directly input the body thickness in step S204, it is preferable to automatically estimate the body thickness in order to reduce the burden on the operator.

 Next, a water equivalent thickness is obtained based on the body thickness obtained in step S204, and an approximate model having this water equivalent thickness is calculated (step S205). The calculation method of water equivalent thickness and approximate model will be described later. Next, the image SD in the original image is calculated (step S206). The method for calculating the image SD in the original image will be described later.

Next, the target image SD value is input (step S207). The SD value entered here is any SD value desired by the operator. In step S207, the X-ray conditions (tube voltage, tube current, slice thickness, etc.) that allow the SD value to be directly input may be input. In this case, convert it to SD from the input X-ray conditions and the size of the approximate model!

[0042] Next, the SD value in the original image obtained in step S206 is compared with the target SD value input in step S207 to calculate the amount of noise to be added to the original image (step S208).

Next, projection data of the approximate model is created (step S209). Two types of projection data are created: an ideal system that does not include noise, and a projection that adds noise by the amount of noise obtained in step S208.

Next, the noise-free projection data obtained in step S209 and the projection data force obtained by adding the noise also create a noise image (step S210). Noise images are projection data with added noise. Obtained by differentiating the reconstructed image of the image and the reconstructed image of the projection data without adding noise, or by reconstructing the difference between the projection data with added noise and the projection data without adding noise. . Then by adding the noise image obtained by the scan Tetsupu S210 based on the image set in step S202 or step S203, creating a simulation image (step S211) ₀

 [0045] [Method of estimating body thickness]

 The body thickness estimation method in S204 will be described. Figure 4 shows the body thickness estimation method. First, a mask image 31 in which the pixel value of the pixel in the subject is 1 and the pixel values of the other pixels are 0 is created from the original image 30, and the inertia main axis 32 in the mask image 31 is obtained. The mask image 31 may be created by any other known method, such as that disclosed in Japanese Patent Application Laid-Open No. 2004-097665.

 Here, the distance between the intersection points PI and P2 of the contours of the inertial principal axis 32 and the mask image 31 is the body thickness in the inertial principal axis direction. The inertial main axis 32 can be obtained according to the following formula (1), where I (x, y) is the pixel at the inertial main axis q and coordinates (x, y).

[0047] {number 1}

[0048] In Equation 1, a, b, and c are expressed by Equation 2 below.

[0049] {number 2}

c-∑∑y ² l (x, y) / ∑∑I (x, y) -Y _c ²

 x y x y

x _c ^ ∑∑xi (x, y) / ∑∑ / (,)

 x y JC y

r _c =

[0050] There is also a method using a scanogram for estimating the body thickness. Analyzing the scanogram, the body thickness in the AP direction (or LR direction) can be determined from the maximum attenuation of X-rays attenuated in the subject.

[0051] [Method of calculating water equivalent thickness and approximate model from body thickness]

 Body thickness strength of S205 A method for calculating the water equivalent thickness and the approximate model will be described. Body thickness can be obtained from the method described above with reference to FIG. Here, when the pixel value of the pixel located in the original image 31 on the inertial main axis 32 shown in FIG. 4 is scanned and the average CT value is CA, the water permeation length L1 in the inertial main axis direction is expressed by the following equation (3). Desired.

 [0052] {number 3}

1000 In Equation 3, 1 represents the distance between P1 and P2. If the subject is assumed to be water-equivalent, L1 obtained by Equation 3 is the water-equivalent thickness in the inertial main axis direction. Water in a direction perpendicular to the principal axis of inertia The value thickness may be obtained assuming that the cross section of the subject is an ellipse. If the average pixel value of all the pixels in the mask is CS, the water equivalent thickness L2 in the direction perpendicular to the principal axis of inertia can be obtained by the following equation (4).

 [0054] Fine

_L 1000+ C _{s π}

 π 1000

In Equation 4, S represents the number of pixels in the mask, that is, the area. The approximate center is the ellipse whose major axis length is L1 (or L2) and whose minor axis length is L2 (or L1).

 [0056] When the body thickness is obtained, the depth of water for an arbitrary attenuation is known, so if the subject is assumed to be water equivalent, the body thickness in the AP direction (or LR direction) described above is assumed. Therefore, the water equivalent thickness in the AP direction (or LR direction) can be calculated. The water equivalent thickness in the LR direction (or AP direction) may be obtained assuming that the cross section of the subject is an ellipse.

 [0057] The total area of the ellipse is considered to be proportional to the sum of the attenuation, and the area of the ellipse is proportional to the product of the major and minor axes of the ellipse, so the sum of the attenuation (= the area of the ellipse) and the AP direction (or It is possible to calculate the water equivalent thickness (= ellipse long axis or short willow) in the LR direction (or AP direction) from the water equivalent thickness (= ellipse short axis or long willow) in the LR direction. An ellipse is an approximate model, and the method for obtaining the scanogram force water equivalent thickness is not limited to this, and any known method may be used.

 [0058] As described above, the approximate model may be obtained by approximating the whole imaging target with a water phantom based on the water equivalent thickness, but the X-ray absorption characteristics such as bone and soft tissue are greatly different in the imaging target. It is desirable to segment the imaging target for each organ and approximate it with a different X-ray absorbing material for each segmented region. Each segmented segment may be assigned an absorption coefficient α obtained by the following equation when creating projection data described later.

[0059] {number 5} II ―

 a 10 (X)

[0060] where μ w is the X-ray absorption coefficient of water, and ACT is the difference between the CT value of each segmented part and the CT value of air. Any known method may be used for segmentation. In this segmentation, for example, in photographing the head, a calcium absorption coefficient is assigned in order to approximate the inner area of a predetermined width from the outer edge of the ellipse to the bone (skull), and the area further inside than that area is May be used to assign a water absorption coefficient to approximate soft tissue.

 [0061] [Method for calculating image SD in original image]

 A method for calculating the image SD in the original image in S206 will be described. The number of views used to reconstruct the CT image Img (z) at the slice position z is M, and the convenient view number m is m = 0 to M-l. When the number of views per rotation is N, the number of used views M is not necessarily equal to the number of views N per rotation. Here, the X-ray attenuation index T can be expressed as a function T (m) of the view number to be used. Assuming that the maximum value of the X-ray attenuation index T in view number m = 0 to M_l is Tmax (0: M-1), and the reference tube current value i_re is assumed to correspond to this, tube current value for view number m iv (m) is expressed by the following equation (6).

 [0062] {Equation 6} iv (m) = i— ref * exp (T (m)-Tmax (0: M— 1)

 On the other hand, when the time trot when the scanner makes one revolution is equal to the reference time trot_ref, the X-ray attenuation index T is a constant value, and xv is used as the tube voltage and the reference tube current value i-re is used as the tube current value i. Then, the number of views in one rotation N_ref 均等 is evenly weighted, and the image noise variance value V when the image thickness thk is reconstructed as the reference image thickness thk_ref using the reconstruction filter function g is X-ray attenuation. As a function of the exponent T, it is expressed as the following equation (7).

[0063] {number 7} V (T i _ ref trot one ref thk ref) =

 c (xv,, '' ref, trot-one ref, thk-one ref) * exp (a (xv) * T)

a (xv) is a constant at ¾H v,

b (xv, g) is a constant that depends on ^ ¾ffixv and the Pi constituent filter Yu ¾, and a (xv) ₄ b (xv, g) is obtained empirically.

[0064] The predicted image noise variance value V * when the tube current value iv (m) represented by the above equation 6 is used is represented by the following equation 8.

 [0065] 删

M-\ (-1 ヽ

V = JV * ∑ 咖) / ∑ w (m) ² * V (T \ m), i _v (m), trot, thk) m = 0 V ^{m = 0}

 Here, w (m) in Expression 8 is a view direction weight applied to each view. Since the parameters such as tube voltage, tube current, reconstruction filter function, and image thickness are already known in the original image, the image noise variance prediction value V * in the original image can be calculated according to Eq. For the square root force, the SD value in the original image is also obtained.

 [0067] [¾ Method of calculating the amount of noise to be calculated]

 A method of calculating the added noise amount in S208 will be described. Let X be the energy of X-ray particles (photons), and P be the number of X-ray particles (photons). E is the tube voltage kV, P is an amount determined depending on the tube voltage kV and tube current mA, and the variance of photon noise (photon SD) Nq is given by the following equation (9).

 [0068]

N _q ² = fi ² g ^ rjE ² PdE [0069] Here, 13 is a constant determined depending on the device, and β is obtained empirically also for the signal strength when shooting without a subject. g is the energy conversion efficiency of the detector, and η is the X-ray detection efficiency of the detector. The photon energy, photon number, photon noise, and system noise in the X-ray condition of the original image (SD is σ 0) are E0, P0, Nq0, and Ns0, respectively. If the energy, photon number, and photon noise are Et, Pt, Nqt, and Nst, respectively, the variance of the photon noise amount Nadd that should be added to the original image to obtain the simulation image is expressed by the following equation (10).

 [0070] {number 10}

N = {β ² g ² i E _t ² P _t dE N _s- ( ² g ² rji E. ² P. dE + NJ)

[0071] For simplicity of calculation, the term of system noise in Equation 10 may be ignored, but in order to perform a detailed simulation, it is necessary to consider not only photon noise but also the effect of system noise. Hope U ,. System noise under each imaging condition can be obtained by scanning the X-ray tube with a sufficiently thick lead plate that does not transmit X-rays.

 [0072] As a method of calculating the amount of added noise, the following method may be considered. SD in the original image is σ 0, and the target image SD is σ t. When a noise image is added to the original image to create a simulation image, SD σ a in the noise image can be calculated by the following equation (11).

_ " twenty two

σ hi = t ~ ^σ

FIG. 5 is an example showing the relationship between the transmission length and the SD in the water phantom. The force curve shown in Fig. 5 can be obtained by photographing water phantoms of various diameters and measuring the SD at that time. It is desirable to prepare the curve shown in Fig. 5 for every tube voltage that can be set by the CT scanner to be used. In step S205, the transmission length (transmission thickness) of the approximate model is obtained by using the method as described above. Therefore, referring to the curve shown in FIG. 5, the σ a calculated by Equation 11 can be obtained. mAs values are obtained. The amount of noise at any mAs value is Since it is obtained empirically by actually measuring the atom, this can be used as the amount of added noise.

 [0075] The curve shown in Fig. 5 is prepared by preparing only the curve at a typical mAs value, and the curves at other mAs values can be calculated using the fact that SD is proportional to the square root of the mAs value. Good. However, in this case, there may be a large error under imaging conditions where system noise is conspicuous. Therefore, it is possible to prepare curves for all mAs values that can be set in the CT device to be used. Hope.

 [0076] [Method for creating projection data of approximate model]

 The approximate model projection data creation method of S209 will be described. Figure 6 shows an illustration of how to create projection data. If the energy intensity of X-rays with energy E is I, I

 E

 Is expressed by the following equation.

 E

 [0077] {number 12}

( _e - _E l cot a _dT

^£ — A ^Je

 o

[0078] Here, N is the Avogadro number, p and A are the density and atomic weight of the target, m0 is the electron mass, c is the speed of light, TO is the energy of the incident electron, Q is also radiating one electron force X The energy intensity of the line. Q is an approximate expression that is determined by the ratio E / T of photon energy E and electron energy T. The following non-patent document 1 gives an approximate expression!

[0079] Non-Patent Document 1: R. Bitch and M. Marshall, Computation of Bremsstrahlung X-ray Spectro and Comparison with Spectra Measured with a Ge (Li) Detector, Phys. Med. B iol, Vol 24, No. 3, 505-517, 1979 dT / dl is the amount of energy loss per unit length and is called stopping power. The stopping power is described in Non-Patent Document 2 for each element.

[0080] Non-Patent Document 2: Katsuhiko Yamada, Hiroki Nohara, Radiation Metrology, Chapter 2, Japan Society for Radiological Technology, 1983. μ Ε is the X-ray absorption coefficient of the target in the X-ray tube, 1 is the electron incident distance is there. Equation 12 is the energy intensity distribution. 得 る / Ε can be calculated to obtain the photon number distribution. Equation 12 is a force representing the spectrum of X-rays by bremsstrahlung Emission from excited atoms _C is the characteristic X-ray Ich is approximated by the number 13 formula follows

 {Number 13}

[0082] TK and L are energy required to remove electrons from the K and L electron orbitals, and can be obtained by comparing the absolute intensity of Ich with the value described in Non-Patent Document 3.

 [0083] Non-Patent Document 3: HPA. Catalog of Spectctral Data for Diagnostic X-rays, SRS-30, Hospital Physicist's Association, 1979 Approximate model projection data is calculated using linear attenuation characteristics and transmission distance be able to. For each photon energy E, the X-ray absorption coefficient n of each X-ray absorbing material n is calculated for each photon energy E, and the projected value at each photon energy is calculated based on the product of the transmission path length In. Then, the projection data is created by the product sum of the contribution rate W (E) of each energy that can obtain the effective spectral distribution force and the projection value.

 [0084] {number 14}

Here, Nadd is the above-described addition noise. Figure 7 outlines the calculation of transmission nose length. Considering a three-dimensional coordinate system with the origin as an arbitrary point (for example, the IISO center), the geometric coordinates of the X-ray source, detector, and approximate model can be obtained. In the equation, the X-ray path incident on an arbitrary detector can be expressed by a linear equation.

[0086] Since the method for obtaining the intersection of the ellipse and the straight line is known, the coordinates of the two intersections can be easily obtained, and the distance between the intersections, that is, the transmission path length (L1 and L2) can be obtained. Such an operation can be performed for all X-ray paths. In the example shown in Fig. 7, for the sake of simplicity, an ellipsoidal simulated organ with an X-ray absorption coefficient of 2 is placed in an ellipsoidal simulated human body with an X-ray absorption coefficient of IX 1, but a larger number is shown. Organs with different shapes or organs Those skilled in the art will readily understand that projection data can be obtained in the same way.

 [0087] In order to perform a more accurate simulation, it is desirable to consider the attenuation of X-rays in the compensation filter and scintillator for the creation of projection data. In this embodiment, it is possible to obtain projection data by creating pseudo-projection data of an approximate model. However, if there is an imaging history in the past, the projection data can be obtained by reprojecting the CT image. Good.

 [0088] [Screen Display]

 For the simulation image display, only the simulation image of the target image SD value may be displayed on the screen, but the display as shown in FIG. 8 may be performed. KVpt and mAst in Fig. 8 are the tube voltage and mAs value for obtaining the simulation image of the target image SD value. In the example of Fig. 8, the tube image and mAs value are centered on the simulation image 80 of the target image SD value. A simulation image 81 is displayed side by side in the case where is appropriately changed.

 The target image SD value is a parameter arbitrarily designated by the operator, but the set target image SD value is not necessarily optimal for reaching the inspection purpose. Therefore, in a user interface that displays only the target image SD value simulation image (hereinafter referred to as [UI] and!, U), the target image SD value is repeatedly calculated in the process of studying the optimal shooting conditions. A process is required to recreate the simulation image while changing.

 [0090] As shown in Fig. 8, not only the simulation image of the target image SD value but also the simulation image when the X-ray conditions are appropriately changed are displayed side by side, so that the process of recreating the simulation image can be greatly reduced. The SD images can be easily compared and the optimal shooting conditions can be easily set.

 [0091] In the example of Fig. 8, the force shown for changing the mAs value and tube voltage value is not limited to these two parameters, but the imaging slice thickness, reconstruction slice thickness, reconstruction function, helicity force Arbitrary parameters such as Rubych may be used. In the example shown in Fig. 8, there are three images in the vertical and horizontal directions, and a total of nine images are displayed side by side. The number and layout of images are not limited to this, and are arbitrary.

[0092] If an arbitrary image is selected on the screen, the X-ray condition at that time is the imaging protocol. If the system is such that the imaging protocol is automatically set to the imaging conditions when imaging a patient that is registered and simulated, the clinical utility will increase.

[0093] <Second embodiment>

 Although Fig. 8 shows an example of displaying simulation images with several SDs side by side, selecting one of the simulation images arranged in Fig. 8 fixes the parameters of the two axes displayed in parallel, and others Let's try displaying multiple simulation images side by side with different parameters.

 FIG. 9 is a screen display example showing this embodiment. In Fig. 9 (a), the vertical axis is the tube voltage kVp, the horizontal axis is the tube voltage mAs, the simulation image 80 generated in step S211 is centered, and the simulation image 81 when the tube voltage and mAs value are appropriately changed is surrounded. Are displayed side by side. Here, when the user clicks and selects the simulation image 80 with the mouse, the tube voltage and tube current kVpt, mAst of the simulation image 80 are fixed, and other parameters such as the helical pitch (HP) and the reconstruction function (F1, F2 , F3) is generated and a simulation image 82 is generated.

 [0095] Then, the simulation image 80 selected in FIG. 9 (a) is displayed in the center, and the simulation image 82 having the same tube current and tube voltage and different HP and reconstruction function is displayed side by side. (Figure 9 (b).

[0096] With this, it is possible to examine optimal X-ray imaging conditions while first setting two parameters and then viewing a simulation image when further parameters are changed.

In the above description, the combination of the tube current and the tube voltage is first determined, and then the helical pitch and the reconstruction function are determined. However, the combination of parameters and the order of determination are not limited to this.

[0098] <Third embodiment>

 The third embodiment is an embodiment in which a simulation image is confirmed, and the X-ray imaging conditions at that time are used as scanning imaging conditions.

For example, a “shooting condition determination” icon 90 is provided in FIGS. 8 and 9B. Figure 8 and figure

In 9 (b), select one simulation image by clicking with the mouse, and then click the shooting condition determination icon 90 with the mouse to select the shooting condition for the selected simulation image. Information indicating the conditions (FOV, imaging slice thickness, reconstruction function, HP, image slice thickness, tube voltage, tube current) is transmitted to the control unit 9 of the X-ray CT apparatus 1. The X-ray control means 10 of the control unit 9 performs scanning imaging according to the received imaging conditions.

[0100] As shown in Fig. 8, the tube voltage and tube current are determined, and all other imaging conditions such as FOV, imaging slice thickness, etc. necessary for scanning are transmitted from the simulator camera. If not, the control unit 9 of the X-ray CT apparatus 1 automatically inputs the received imaging conditions and causes the user to input the insufficient imaging conditions.

[0101] According to the present embodiment, the imaging conditions determined while viewing the simulation image can be transmitted to the X-ray CT apparatus, and the imaging conditions can be automatically input to perform scanning imaging.

 [0102] <Fourth embodiment>

 SD may be displayed side by side with the same simulation images with the same noise pattern. Due to the randomness of noise, the appearance of noise, that is, the noise pattern, is different even when the same subject is imaged under exactly the same X-ray conditions. Therefore, because of the combination of the size and position of the disease and the noise pattern, it may be difficult to see the disease even if the images are taken under the same X-ray conditions. Therefore, especially in close examinations, it is necessary to set imaging conditions that can reliably detect diseases regardless of the noise pattern.

 [0103] In such a case, a UI that displays simulation images with the same SD and different noise patterns in parallel would be clinically useful. FIG. 10 shows a screen display example in which nine simulation images 85 with the same SD value and different noise patterns are displayed in parallel. The number of dots indicating noise (one large dot and eight small dots) is the same, but the positions where dots are scattered are different in each simulation image. By displaying such a simulation image, it is possible to determine shooting conditions in consideration of noise patterns.

 [0104] Further, in recent years, a technique for reducing the exposure dose by improving the SN of an image by using an image filter capable of removing noise while suppressing the reduction in resolution as shown in Non-Patent Document 4. Law has been introduced.

[0105] Non-patent document 4: Video information Medical separate volume multi-slice CT Book2005 vol37 (7) 145-149 Therefore, when considering an exposure reduction imaging protocol using image filters, noise removal processing is performed on simulation images using any image filter such as the image filter shown in Non-Patent Document 4. A UI that can do this would be clinically useful.

 [0106] For example, in the same way as in the case of Fig. 8 described above, simulation images after filtering processing are displayed side by side when arbitrary parameters are selected on the vertical axis and horizontal axis and the X-ray conditions are changed as appropriate. When the processing parameters (smoothing level, sharpness level, etc.) of the image filter are changed, it is desirable to switch the display of the simulation image after the filtering process accordingly.

 In addition, as shown in FIG. 11, a UI that displays the simulation image 111 after filtering processing when the smoothing level and the sharpening level are changed with respect to the same simulation 110 image is also clinically useful. I will.

 <Fifth embodiment>

 [Configuration of X-ray CT scan simulator]

 FIG. 12 is a configuration diagram of the X-ray CT scan simulator 1200 of the present embodiment. The X-ray CT scan simulator 1200 includes image storage means 1210, target noise value setting means 1230, noise image generation means 1240, simulation image creation means 1244, and sample noise image editing means 1250.

 The image storage means 1210 stores a reference image serving as a reference for the simulation image created by the X-ray CT scan simulator 1200 and a plurality of sample noise images. The reference image is a past image obtained by CT imaging of a subject in the past, or a human phantom image obtained by CT imaging in advance of a human phantom that faithfully reproduces the internal tissue of the human body. Sufficient X-ray dose should be used to capture human phantom images so that clear images can be obtained. For human phantom images, images taken with typical FOVs should be prepared for each part. The sample noise image is an image including only noise components. It is desirable to prepare the sample noise image according to the part, the FOV, the ratio of the FOV to the subject size, and the reconstruction function used during image reconstruction. The method for creating the sample noise image has already been described.

[0110] The target noise value setting means 1230 is a simulation created by the X-ray CT scan simulator 1200. -Set the noise target value of the image. The target noise value setting means 1230 includes body thickness acquisition means 1231, approximate model generation means 1232, and target noise value calculation means 1233. The target noise value setting unit 1230 may be an image noise amount input unit that inputs an image noise amount. Note that the image noise amount is usually defined as the standard deviation of the CT value variation of a homogeneous phantom image, and is sometimes abbreviated as image SD (Standard Deviation).

 [0111] The body thickness acquisition means 1231 acquires the body thickness of the subject. The body thickness may be manually input by the operator, or the scanogram force may be obtained. If the reference image is a past image, it may be automatically estimated by the method described above.

 The approximate model generation unit 1232 generates an approximate model based on the body thickness acquired by the body thickness acquisition unit 1231. The approximate model may be a model that is similar to water so that it has the same amount of X-ray absorption as the subject (hereinafter referred to as the water approximate model). A model using a virtual substance having a quantity (hereinafter referred to as an average CT value substance approximation model) may be used.

 The target noise value calculation unit 1233 calculates the image noise amount based on the input shooting conditions and the approximate model generated by the approximate model generation unit 1232.

 The noise image generation means 1240 generates and outputs a noise image based on the target noise value set by the target noise value setting means 1230. The noise image generation means 1240 includes sample noise image selection means 1220, reference image noise amount calculation means 1241, added noise amount calculation means 1242, and noise amplitude change means 1243.

 [0115] The sample noise image selection means 1220 selects one sample noise image according to the photographing condition of the reference image, among the plurality of sample noise images. To select a sample noise image, refer to the FOV, FOV and subject size ratio, reconstruction function, etc. from the shooting conditions.

 [0116] The reference image noise amount calculation means 1241 calculates the noise amount of the reference image. The method for calculating the noise amount of the reference image has already been described.

[0117] The addition noise amount calculation means 1242 should add to the reference image based on the target noise value set by the target noise value setting means 1230 and the noise amount calculated by the reference image noise amount calculation means 1241. Calculate the amount of noise. The noise amplitude changing unit 1243 changes the noise amplitude of the sample noise image selected by the sample noise image selecting unit 1220 based on the added noise amount calculated by the added noise amount calculating unit 1242.

 The simulation image creating means 1244 creates a simulation image by synthesizing the noise image generated by the noise image generating means 1240 and the reference image.

 The sample noise image editing unit 1250 is a unit for performing editing such as addition and deletion of the sample noise image stored in the image storage unit 1210. Using the sample noise image editing means 1250, the operator designates at least one of the shape of the virtual phantom, the CT value, the barycentric coordinates, and the field of view for imaging, and adds the sample noise image.

 [0121] [Process flow]

 FIG. 13 is a diagram showing a processing flow until a simulation image is generated according to the present embodiment. The general flow is setting the reference image in steps S1301 to S1303, setting the target noise value in steps S1304 to S1306, generating a noise image in steps S1307 to S1311, and synthesizing the simulation image in step S1312. . Each step is described below.

 [0122] (Step S 1301)

 The X-ray CT scan simulator 1200 searches the image storage means 1210 for past images of the subject to be simulated, and determines whether there is a history of imaging the same part in the past. If it is determined that there is a past image, the process proceeds to step S1302, and if not, the process proceeds to step S1303.

 [0123] (Step S 1302)

 X-ray CT scan simulator 1200 sets a past image as a reference image.

 (Step S 1303)

 The X-ray CT scan simulator 1200 sets a human phantom image as a reference image.

[0124] (Step S 1304)

The body thickness acquisition means 1231 automatically estimates the body thickness of the subject from the scanogram and past images. The estimation method has already been described. The operator may input the body thickness directly, but it is better to estimate the body thickness automatically in order to reduce the burden on the operator. [0125] (Step SI 305)

 The approximate model generation means 1232 generates an approximate model based on the body thickness obtained in S 1306. The approximate model may be a water approximate model or an average CT value substance approximate model. The method for calculating the approximate model has already been described.

[0126] (Step S 1306)

 Target noise value setting means 1230 sets the target noise value. The target noise value can be set manually by the operator, or the target noise value calculation means 1233 can set the approximate model generated in S1307 and the shooting conditions. good.

[0127] (Step S1307)

 The X-ray CT scan simulator 1200 acquires FOV, FOV and the size ratio of the subject, and the reconstruction function from the imaging conditions of the reference image set in S1302 or S1303.

[0128] (Step S 1308)

 The sample noise image selection means 1220 selects one sample noise image based on the photographing conditions acquired in S1305, among the plurality of sample noise images in the image storage means 1210.

[0129] (Step S 1309)

 The reference image noise amount calculation unit 1241 calculates the image noise amount of the reference image. The method for calculating the amount of image noise has already been described.

[0130] (Step S1310)

 Based on the target noise value set in S1308 and the image noise amount of the reference image calculated in S1309, the added noise amount calculation unit 1242 calculates the noise amount to be added to the reference image. The method for calculating the amount of added noise has already been described.

[0131] (Step S1311)

 The noise amplitude changing means 1243 changes the noise amplitude of the sample noise image selected in S1305 according to the added noise amount calculated in S1310.

[0132] (Step S1312)

The simulation image creating means 1244 combines the reference image set in S1302 or S1303 with the sample noise image whose noise amplitude has been changed in S1311, thereby simulating. Create a layout image.

 [0133] It is desirable to prepare a sample noise image according to the part, the FOV, the ratio of the FOV to the subject size, and the reconstruction function. The human body has a vertically long organ such as the head and a horizontally long organ such as the abdomen. Here, the X-axis diameter of the subject is Rx, and the Y-axis diameter is Ry. Sample noise images are created for each part. Rx / Ry is about 0.787 for a longitudinal organ such as the head, and Ry / Rx is 0.787 for a lateral organ such as the abdomen. It is desirable to create a sample noise image with such a virtual phantom where it is desirable that a simulated organ is placed in the above-mentioned virtual phantom so as to have a value of about.

[0134] Regarding FOV, it is desirable to create sample noise images for all possible FOVs in all imaging protocols. Fig. 14 is an explanatory diagram of the ratio between FOV and subject size. For example, assume that a subject 902 is included in an image 901 as shown in FIG. Here, if the X-axis diameter of the object is Rx and the Y-axis diameter is Ry, the ratio of FOV to subject size described in the present invention is the ratio of Rx / FOV or Ry / FOV. Real number of ~ 1. Depending on the part to be imaged, the subject size may be almost the same as the FOV, or it may be only about 30% of the FOV. Therefore, it is desirable to create sample noise images in steps of about 0.05 when the ratio of FOV to subject size is in the range of 0.3 to 1.00. Even for data taken under the same _χ- ray conditions, the noise pattern varies depending on the reconstruction function. Therefore, it is desirable to create sample noise images for all reconstruction functions used in clinical practice.

[0135] It is clinically useful to have a function that allows the operator to create and add the sample noise image described above by simply preparing it in advance. In order for the operator to add a sample noise image, the operator can arbitrarily specify the virtual phantom shape, CT value, barycentric coordinates, noise amount (SD), and FOV as shown in Fig. 15. It is desirable to have a simple GUI. It is also desirable to have a GUI that displays a list of stored sample noise images on the screen and allows the operator to delete any noise images that the operator determines unnecessary! /, .

[0136] When the created simulation image is displayed by the above processing, the reference image set in S1302 or S1303, the sample noise image selected in S1305, and the amplitude change obtained in S1311 are displayed simultaneously with the simulation image. All sample noise images It is desirable for the operator to display side by side for any combination desired. Also

The display described in the first embodiment to the fourth embodiment may be performed.

 FIG. 16 shows an application example of the present invention. Figure 16 (a) is an SD force head CT image 120 taken at 100kV, 200mAs. FIG. 16 (b) is a noise image 121 to be added to create a simulation image with Sd force .6 from the original image 120 in FIG. 16 (a). FIG. 16 (c) is a simulation image 122 obtained by adding the noise image 121 of FIG. 16 (b) to the original image 120 of FIG. 16 (a), and SD is 5.6. Therefore, this corresponds to a case where the mAs value is reduced by about 1/2 compared to the shooting conditions when the original image was obtained.

 [0138] Those skilled in the art will readily understand that simulation images can be created in the same way when the SD in a simulation image is changed or in other parts.

 [0139] In the above embodiment, an X-ray CT apparatus equipped with an X-ray CT scan simulator has been described. However, it is configured as an X-ray CT scan simulator apparatus equipped with only a simulator function without an X-ray imaging function. Anyway.

[0140] Further, the function described in the above embodiment may be configured as a scan simulator program that causes a computer to execute the function, and the above function may be realized by installing this program in a personal computer or a workstation. In that case, the simulator image does not necessarily have to be displayed on the monitor of the personal computer installed with the scan simulator program. The simulator image is transmitted to a terminal device connected via a network such as a LAN. The simulator image may be displayed on the terminal device.

 Brief Description of Drawings

[0141] [FIG. 1] A configuration diagram of an X-ray CT apparatus equipped with the X-ray CT scan simulator of the present invention.

 FIG. 2 is a configuration diagram of the first embodiment.

 FIG. 3 is a processing flow of the first embodiment.

 FIG. 4 is an explanatory diagram of a body thickness estimation method.

 FIG. 5 is a diagram showing the relationship between transmission length and SD in a water phantom.

 FIG. 6 is an explanatory diagram of a method for creating projection data.

FIG. 7 is an explanatory diagram of a method for calculating a transmission length. FIG. 8 is a screen display example of the first embodiment.

FIG. 9 shows a screen display example of the second embodiment.

FIG. 10 shows a screen display example of the fourth embodiment.

FIG. 11 shows a screen display example of the fourth embodiment.

FIG. 12 is a configuration diagram of the fifth embodiment.

FIG. 13 is a processing flow of the fifth embodiment.

FIG. 14 is an explanatory diagram of the ratio between FOV and subject size.

 [Figure 15] Example GUI for operator to create and add sample noise images.

FIG. 16 shows an example of clinical application of the present invention.

Explanation of symbols

 1 X-ray CT system, 2 Gantry, 3 X-ray source, 4 Collimator, 5 Detector array, 6 Detector element, 7 X-ray, 8 Center of rotation, 9 Control unit, 10 X-ray control means, 11 Gantry control means , 12 DAS, 13 Arithmetic processing means, 14 Body thickness estimation means, 15 Approximation model calculation means, 16 Image SD calculation means, 17 Addition noise amount calculation means, 18 Approximation model projection data creation means, 19 Reconstruction means, 20 Noise image Creation means, 21 simulation image creation means, 22 storage means, 23 — hour storage means, 24 input means, 25 image display means

Claims

The scope of the claims

 Image storage means for storing a reference image;

 Target noise value setting means for setting a noise target value of a desired image;

 Noise image generation means for generating a noise image based on the set target noise value; simulation image generation means for generating a simulation image by combining the generated noise image and the reference image;

 Display means for displaying the simulation image;

An X-ray CT scan simulator device comprising:

 The X-ray CT scan simulator apparatus according to claim 1,

 The noise image generation means includes

 Body thickness obtaining means for obtaining the body thickness of the subject;

 An approximate model generating unit that generates an approximate model of the subject based on the body thickness; a reference image noise amount calculating unit that calculates a noise amount of the reference image;

 Added noise amount calculating means for calculating a noise amount to be added to the reference image based on the target noise value and the noise amount of the reference image;

 Approximate model projection data creating means for creating reference projection data that is projection data of the approximate model, and addition projection data obtained by adding the amount of addition noise to the reference projection data;

 An X-ray CT scan simulator apparatus comprising: noise image reconstruction means for reconstructing a noise image using the addition projection data.

 The X-ray CT scan simulator device according to claim 2,

 The noise image creation means creates a noise image by subtracting the reconstructed image based on the addition projection data and the reconstructed image based on the reference projection data, or creates a difference between the addition projection data and the reference projection data An X-ray CT scan simulator device that generates differential projection data by processing and reconstructs the differential projection data to create a noise image.

The X-ray CT scan simulator device according to claim 2, The approximate model calculating means calculates an approximate model such as a virtual water phantom camera having a water equivalent thickness estimated from the body thickness of the subject, or a part obtained by dividing the imaging part of the subject X-ray CT, which is characterized by calculating an approximate model to which the X-ray absorption coefficient calculated from the difference between the CT value of the part and the CT value of air and the X-ray absorption coefficient of water is calculated. Scan simulator device.

[5] In the X-ray CT scan simulator apparatus according to claim 2,

 The approximate model projection data creation means virtually generates an X-ray energy spectrum, and for each photon energy, each photon is based on the product of the X-ray absorption coefficient and the transmission path length of each X-ray absorbing material. The projection value in energy is calculated, and the reference projection data and the addition projection data are generated by the product sum of the contribution rate of each energy and the projection value, or the past image of the subject is reprojected and the reference An X-ray CT scan simulator device that creates projection data and the addition projection data.

[6] In the X-ray CT scan simulator apparatus of claim 2,!

 The X-ray CT scan simulator device, wherein the reference image noise calculation means calculates an image noise amount included in the reference image based on an imaging condition when the reference image is captured.

[7] The X-ray CT scan simulator device according to claim 1,

 The simulation image creating means further updates a simulation image group having a plurality of simulation image forces that differ in at least one of the imaging conditions of the simulation image, an image filter, and a scattered pattern of the image noise. The X-ray CT scan simulator device is characterized in that the display means displays the simulation image and the simulation image group side by side.

[8] In the X-ray CT scan simulator device of claim 7,

The image processing apparatus further includes selection means for selecting one of the simulation images displayed side by side on the display means, and the display means displays the imaging conditions and the plurality of simulation images in association with each other, and the selection means When one of the simulation images is selected, the simulation image creating means has the same shooting conditions displayed on the display means among the shooting conditions of the selected simulation image, and different shooting conditions. 7. A simulation image group having a plurality of simulation image powers is created again, and the display means displays the simulation image group created again and the selected simulation image side by side. X-ray CT scan simulator device described.

 [9] In the X-ray CT scan simulator device according to claim 7,

 The apparatus further comprises a designation unit that designates one of the simulation images or the simulation image group displayed on the display unit, and the designation is performed when the simulation image displayed on the display unit is designated. An X-ray CT scan simulator device that outputs an imaging condition for obtaining a simulated image as an imaging condition at the time of scan imaging of the subject.

[10] In the X-ray CT scan simulator device of claim 1,

 The image storage means further stores a plurality of sample noise images, and the noise image generation means selects one sample noise image from the plurality of sample noise images according to the shooting conditions. When,

 Reference image noise amount calculating means for calculating the noise amount of the reference image;

 Added noise amount calculating means for calculating a noise amount to be added to the reference image based on the target noise value and the noise amount of the reference image;

 Noise amplitude changing means for changing the noise amplitude of the selected sample noise image based on the added noise amount;

 An X-ray CT scan simulator device characterized by comprising:

[11] In the X-ray CT scan simulator device of claim 10,

 The reference image stored in the image storage means is a past image obtained by imaging a subject in the past or a human phantom image obtained by imaging a human phantom. CT scan simulator device.

[12] The X-ray Ct scan simulator device according to claim 10,

The target noise value setting means includes a body thickness acquisition means for acquiring a body thickness of the subject, an approximate model generation means for generating an approximate model of the subject based on the body thickness, the imaging conditions, and the approximate model Target noise for calculating the target noise value based on A value calculating means;

 An X-ray CT scan simulator device comprising:

[13] In the X-ray CT scan simulator device of claim 12,

 The body thickness acquisition means is a means for estimating the body thickness of the subject based on a scanogram image obtained by scanning a scanogram, or based on a past image obtained by imaging the subject in the past. An X-ray CT scan simulator that is a means for estimating body thickness.

 [14] The X-ray CT scan simulator device according to claim 12,

 The X-ray CT scan simulator device, wherein the approximate model generation means is means for calculating a water equivalent thickness equivalent to the body thickness and calculating an approximate model having the water equivalent thickness.

 [15] The X-ray CT scan simulator device according to claim 10,

 The plurality of sample noise images stored in the image storage means are sample noise images having different parts, imaging field of view, ratio of imaging field of view to subject size, and reconstruction function used for image reconstruction. X-ray CT scan simulator device.

 [16] The X-ray CT scan simulator device according to claim 10,

 An X-ray CT scan simulator characterized by further comprising an editing means for specifying at least one of a virtual phantom shape, CT value, barycentric coordinates, and field of view, and adding and deleting sample noise images.

 [17] An X-ray source that irradiates the subject with X-rays, an X-ray detector that is disposed opposite to the X-ray source and detects X-rays transmitted through the subject, and the X-ray source and the X-rays A rotation device that mounts a detector and rotates around the subject; an image reconstruction device that reconstructs a tomographic image of the subject based on transmitted X-ray amounts in a plurality of directions detected by the X-ray detector; An X-ray CT apparatus comprising: an imaging condition input device that inputs the X-ray irradiation condition and image reconstruction condition; and an image display device that displays the tomographic image.

 An X-ray CT apparatus comprising the X-ray CT scan simulator apparatus according to any one of claims 1 to 16.

[18] obtaining a reference image; Setting a desired noise value for the desired image;

 Generating a noise image based on the set target noise value; creating a simulation image by combining the generated noise image and the reference image; and outputting the simulation image;

 X-ray CT scan simulator program characterized by causing a computer to execute.

[19] The X-ray CT scan simulator program according to claim 18, wherein the noise image generation step includes:

 Obtaining a body thickness of the subject;

 Generating an approximate model of the subject based on the body thickness;

 Calculating a noise amount of the reference image;

 Calculating a noise amount to be added to the reference image based on the target noise value and a noise amount of the reference image;

 Creating reference projection data that is projection data of the approximate model, and addition projection data obtained by adding the addition noise amount to the reference projection data; and

 Reconstructing a noise image using the added projection data;

 X-ray CT scan simulator program characterized by causing a computer to execute.

[20] In the X-ray CT scan simulator program of claim 18,

 The noise image generation step includes

 Selecting one sample noise image from a plurality of sample noise images according to the shooting conditions;

 Calculating a noise amount of the reference image;

 Calculating a noise amount to be added to the reference image based on the target noise value and a noise amount of the reference image;

 Changing the noise amplitude of the selected sample noise image based on the amount of added noise;

 X-ray CT scan simulator program characterized by causing a computer to execute.