WO2011105388A1 - Dispositif de diagnostic par imagerie radiographique, et programme et procédé de traitement d'image médicale - Google Patents

Dispositif de diagnostic par imagerie radiographique, et programme et procédé de traitement d'image médicale Download PDF

Info

Publication number
WO2011105388A1
WO2011105388A1 PCT/JP2011/053895 JP2011053895W WO2011105388A1 WO 2011105388 A1 WO2011105388 A1 WO 2011105388A1 JP 2011053895 W JP2011053895 W JP 2011053895W WO 2011105388 A1 WO2011105388 A1 WO 2011105388A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
grid
frequency
defective pixel
image data
Prior art date
Application number
PCT/JP2011/053895
Other languages
English (en)
Japanese (ja)
Inventor
忍 竹之内
克己 鈴木
Original Assignee
株式会社 日立メディコ
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社 日立メディコ filed Critical 株式会社 日立メディコ
Priority to JP2012501798A priority Critical patent/JP5848697B2/ja
Priority to CN201180010693.7A priority patent/CN102770075B/zh
Publication of WO2011105388A1 publication Critical patent/WO2011105388A1/fr

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/42—Arrangements for detecting radiation specially adapted for radiation diagnosis
    • A61B6/4291—Arrangements for detecting radiation specially adapted for radiation diagnosis the detector being combined with a grid or grating
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/44—Constructional features of apparatus for radiation diagnosis
    • A61B6/4429—Constructional features of apparatus for radiation diagnosis related to the mounting of source units and detector units
    • A61B6/4452—Constructional features of apparatus for radiation diagnosis related to the mounting of source units and detector units the source unit and the detector unit being able to move relative to each other
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5258—Devices using data or image processing specially adapted for radiation diagnosis involving detection or reduction of artifacts or noise
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30061—Lung

Definitions

  • the present invention relates to an X-ray diagnostic imaging apparatus, a medical image processing program, and a method, and more particularly to an improvement in image quality of an image obtained by X-ray imaging using a grid for removing scattered X-rays.
  • a grid is arranged on the X-ray flat detector to prevent the scattered X-rays generated inside the subject from being imaged.
  • the image generated by the X-ray flat panel detector samples the image signal two-dimensionally, the pixel pitch and the grid density interfere with each other, and aliasing (moire) occurs.
  • the frequency band of the moire component is calculated from the pixel size of the X-ray flat panel detector and the grid density of the grid, and a grid in which the moire appears in the high frequency band is selected.
  • an image processing method is disclosed in which filtering processing or Fourier transform is performed, frequency data obtained by Fourier transform is reduced or removed, and inverse Fourier transform is performed.
  • the present invention has been made in view of the above problems, and provides an X-ray diagnostic imaging apparatus, a medical image processing method, and a program capable of effectively removing grid stripes (moire) even on a reduced image subjected to thinning processing.
  • the purpose is to do.
  • an X-ray diagnostic imaging apparatus detects an X-ray tube and transmitted X-rays that are disposed opposite to the X-ray tube and transmitted through a subject, and outputs image data.
  • the medical image processing program includes a step of reading image data obtained by imaging a subject with an X-ray image diagnostic apparatus provided with a grid, a step of determining a thinning number of the image data, A step of calculating a frequency of grid stripes included in the image data thinned by the determined number of thinnings, and an image of the image data subjected to the thinning processing according to the calculated frequency of grid stripes A step of performing correction and a step of displaying a subject image based on the image data after the image correction are executed by a computer.
  • the medical image processing method includes a step of reading image data obtained by imaging a subject with an X-ray image diagnostic apparatus having a grid, a step of determining a thinning number of the image data, A step of calculating a frequency of grid stripes included in the image data thinned by the determined number of thinnings, and an image of the image data subjected to the thinning processing according to the calculated frequency of grid stripes A step of correcting, and a step of displaying a subject image based on the image data after the image correction.
  • X-ray image diagnosis by performing defective pixel correction and grid stripe removal correction according to the grid stripe frequency, X-ray image diagnosis that can effectively remove grid stripes (moire) even for a reduced image subjected to thinning processing.
  • An apparatus, a medical image processing method, and a program can be provided.
  • Schematic diagram showing a schematic configuration of the X-ray diagnostic imaging apparatus 10 according to the present embodiment Explanatory diagram showing the principle of grid stripe generation
  • Schematic block diagram of this embodiment A flowchart showing a schematic processing flow of the present embodiment Flow chart showing the flow of processing of this embodiment Explanatory drawing which shows the relationship between the thinning number and the image size after thinning Graph showing correspondence between shooting distance and frequency response
  • It is explanatory drawing which shows the defective pixel correction process which concerns on this embodiment (a) shows the defective pixel correction process in a high frequency band, (b) shows the defective pixel correction process in a low frequency band.
  • FIG. 1 is a schematic diagram showing a schematic configuration of an X-ray image diagnostic apparatus 10 according to the present embodiment.
  • the X-ray diagnostic imaging apparatus 10 includes an X-ray tube 11 that irradiates the subject 1 with X-rays, an X-ray diaphragm 12 that restricts irradiation of the X-rays irradiated from the X-ray tube 11 to the subject 1, and a subject.
  • Image processing device 15 that performs image processing such as defective pixel correction, grid stripe removal processing, and gradation processing on image data to be displayed, and preview (photographing confirmation) image data generated by image processing device 15 are displayed
  • a preview display device 16 a moving image during fluoroscopy generated by the image processing device 15, an image display device 17 for displaying a still image, an X-ray generation unit including the X-ray tube 11, an X-ray flat detector 14, It is electrically connected to the image processing device 15, preview display device 16, and image display device 17, and controls each operation.
  • the control device 18 includes a distance measuring unit 18a that measures a distance (SID) from the X-ray tube 11 to the X-ray plane detector 14 during X-ray imaging, an X-ray generation unit including the X-ray tube 11, and an X-ray plane. It includes a control unit 18b that controls the operation of each device such as the detector 14 and the image processing device 15 and transmits and receives necessary information.
  • the image processing device 15 is a control / arithmetic device such as a CPU or MPU, a storage device including a ROM, a RAM, and a hard disk, an interface for receiving image data from the X-ray flat detector 14, An interface for outputting display image data to the preview display device 16 and the image display device 17 includes hardware.
  • the image processing apparatus 15 stores an image processing program for performing defective pixel correction and grid stripe removal correction according to the present embodiment.
  • This image processing program mainly includes an image data acquisition unit 15a that reads image data obtained by imaging the subject 1 from the X-ray plane detector 14, and a thinning number determination unit 15b that determines a thinning number of the image data.
  • a frequency calculation unit 15c that calculates the frequency of the grid stripe
  • a defective pixel correction unit 15d that corrects the pixel value of the defective pixel according to the calculated frequency band of the grid stripe
  • a grid stripe removing unit 15e that removes the frequency components of the grid stripes calculated by the frequency calculating unit 15c from the image data corrected by the defective pixel correcting unit 15d, and a thinning processing unit 15f that performs a thinning process on the image data
  • a gradation processing unit 15g that performs gradation processing for a display image.
  • the image processing device 15 includes a defective pixel correction unit 15d and a grid stripe removal unit 15e, and the grid stripe removal unit 15e uses the frequency calculation unit 15c from the image data corrected by the defective pixel correction unit 15d.
  • the image processing device 15 may include only the defective pixel correction unit 15d and correct the pixel value of the defective pixel according to the calculated frequency band of the grid stripe.
  • the image processing device 15 includes only the grid stripe removal unit 15e, and the frequency calculation unit 15c calculates the image data acquired by the image data acquisition unit 15a and the image data subjected to the conventional defective pixel correction processing. You may remove the grid stripe component of the frequency band made.
  • FIG. 2 is an explanatory diagram showing the principle of grid stripe generation.
  • the X-ray flat detector 14 is a flat panel detector (hereinafter referred to as “FPD”) configured by arranging detection elements in a matrix on a two-dimensional plane.
  • the width of the detection element is 143 ⁇ m.
  • a grid 13 is disposed on the X-ray flat detector 14.
  • a curve 13i represents an X-ray intensity distribution curve after passing through the grid
  • a curve 14b is a luminance distribution curve after FPD sampling (in the following description, pixel values are treated as luminance).
  • the X-rays transmitted through the grid 13 are caused by the lead 13b of the grid 13 arranged at intervals of 250 ⁇ m, as shown by the X-ray intensity distribution curve 13i after passing the grid in FIG. This produces a line intensity distribution.
  • the sampling pitch of the FPD is 250 ⁇ m, which is the same as the X-ray intensity distribution, grid stripes will not be generated because the in-phase intensity distribution can always be sampled.
  • the FPD sampling pitch is 143 ⁇ m
  • the FPD sampling pitch (14b) are out of phase, and data sampling is performed at a position indicated by a circle on the X-ray intensity distribution curve 14b.
  • solid lines connecting these FPD sampling points are recognized as grid stripes (also referred to as moire stripes) in the image output from the FPD.
  • FIG. 3 is an explanatory diagram showing the principle that the grid fringe frequency varies depending on the shooting distance.
  • 3 (a) and 3 (b) show the X-ray intensity distribution 13i after passing through the grid when the grid 13 having the same structure is photographed at different photographing distances (SID), and FIG. Fig.
  • FIG. 3 (b) shows the X-ray intensity distribution 13i when shooting at the same shooting distance (SID) as the focal length of Fig. 3, and Fig. 3 (b) shows the X-ray intensity when shooting at a shooting distance (SID) shorter than Fig. 3 (a).
  • Distribution 13i is shown.
  • the focusing distance of the grid 13 means a distance when the surface of the absorbing foil in the focusing grid, that is, the extension of the surface of the lead plate 13b is concentrated on one straight line, and is an index indicating the geometric performance of the focusing grid. Become one.
  • the grid stripes become high frequency, and the shooting distance (SID) becomes shorter as shown in Fig. 3 (b).
  • the frequency becomes low.
  • the high frequency band indicates a case where the grid fringe frequency is close to the Nyquist frequency
  • the low frequency band indicates a frequency where the grid fringe frequency is separated from the Nyquist frequency.
  • the Nyquist frequency varies depending on the thinning-out number as shown in Table 1.
  • the image profile example is as shown in FIG. 9 (a) for the high frequency and FIG. 9 (b) for the low frequency, which will be described in detail later.
  • the shooting distance SID
  • FIG. 4 is a schematic block diagram of the present embodiment.
  • FIG. 5 is a flowchart showing a schematic processing flow of the present embodiment.
  • FIG. 6 is a flowchart showing the processing flow of the present embodiment.
  • a case where a preview image is displayed after X-ray imaging of a subject will be described as an example, but the present invention can also be applied to a case where a moving image during fluoroscopy is displayed on the image display device 17.
  • the present embodiment can be applied to all image display processing for performing thinning.
  • FIG. 4 a schematic processing flow of the present embodiment will be described along each step of FIG. 5, and then a detailed processing flow of the present embodiment will be described along each step of FIG. .
  • Step S1 The image data acquisition unit 15a obtains image data obtained by irradiating the subject 1 with X-rays from the X-ray flat panel detector 14, and the image data acquired by the thinning number determination unit 15b and the thinning processing unit 15f Is determined and thinning processing is performed.
  • Step S2 The frequency calculation unit 15c calculates the frequency of the grid stripe to be removed for the image data that has been subjected to the thinning process.
  • the calculation is performed according to values such as grid density, grid focusing distance, imaging distance (SID) from the X-ray tube 11 to the X-ray flat panel detector 14, and the like.
  • Step S3 The defective pixel determination unit determines whether or not the defective pixel is included in the image data subjected to the thinning process in step S2. If it is included, the process proceeds to step S4. If it is not included, the process proceeds to step S5.
  • Step S4 The defective pixel correction unit 15d performs defective pixel correction of the image data using the grid stripe frequency calculated by the frequency calculation unit 15c.
  • Step S5 The grid stripe removal unit 15e removes the grid stripes from the image data on which defective pixel correction has been performed or image data determined to have no defective pixels, using the frequency of the grid stripes calculated by the frequency calculation unit 15c.
  • Step S6 The gradation processing unit 15g performs gradation processing on the image data from which the grid stripes have been removed, and displays the image data subjected to the gradation processing on the preview image display device 16 or the image display device 17.
  • Step S1 in FIG. 5 corresponds to steps S11 to S13 in FIG. 6
  • step S2 in FIG. 5 corresponds to step S21 in FIG. 6
  • step S3 in FIG. 5 corresponds to step S31 in FIG. 6
  • step S4 in FIG. 6 corresponds to steps S41 to S45 in FIG. 6
  • step S5 in FIG. 5 corresponds to steps S51 to S55 in FIG. 6
  • step S6 in FIG. 5 corresponds to step S61 in FIG.
  • Step S11 The distance measuring unit 18a measures an imaging distance (SID) from the X-ray tube 11 to the X-ray flat detector 14, and the control unit 18b sets imaging conditions according to the imaging distance.
  • SID imaging distance
  • the control unit 18b sets imaging conditions according to the imaging distance.
  • Step S12 Image data is transferred from the X-ray flat panel detector 14 to the image processing device 15, and the image data acquisition unit 15a acquires the image data. Further, the information from the control unit 18b to the image processing device 15, the grid 13 information (grid density and grid focusing distance), the shooting distance (SID) measured by the distance measuring unit 18a, the screen size of the preview display device 16 or the preview image Shooting condition data such as the image size is transferred (S12).
  • Step S13 The thinning number determination unit 15b calculates the thinning number of the preview image acquired in S12, and the thinning processing unit 15f thins out the image data acquired by the image data acquisition unit 15a (S13).
  • the thinning-out number a table in which the size of the image data acquired from the X-ray flat panel detector 14 is associated with the image size of the screen size / preview image is prepared in advance, and the thinning-out number determination unit 15b refers to the table. And decide.
  • FIG. 7 is an explanatory diagram showing the relationship between the thinning number and the image size after thinning.
  • the size of the image data output and acquired from the X-ray plane detector 14 is 3000 ⁇ 3000 pixels at the full size
  • the image size of the preview image displayed on the preview image display device 16a Is 750 ⁇ 750 pixels
  • the thinning-out number is calculated as “4”.
  • the image size of the preview image displayed on the preview image display device 16b is 300 ⁇ 300 pixels
  • the thinning-out number is “10”.
  • the image sizes of these preview images are variable, and are changed depending on the display size of the preview image display device and the irradiation field region size excluding the X-ray aperture.
  • Step S21 The frequency calculation unit 15c calculates the frequency of the grid stripe to be removed (S21).
  • the thinning processing unit 15f performs thinning processing on the image data obtained by imaging only the grid 13 (hereinafter referred to as “grid stripe image data”) with the same number as the thinning number acquired in step S12. Subsequently, the grid stripe removal unit 15e performs a one-dimensional FFT process which is one of its functions.
  • the frequency calculation unit 15c calculates the grid fringe frequency with reference to the result of the one-dimensional FFT process.
  • Table 1 shows the image size, thinning number, Nyquist frequency, grid fringe frequency, and spatial frequency of the preview image (reduced image) (the vertical axis shows the frequency response, the horizontal axis shows the frequency component, the center of the horizontal axis is 0, and it is symmetrical It is drawn in).
  • Table 1 shows calibration data calculated using the Fourier transform processing function of the grid fringe removing unit 15e based on grid fringe image data obtained by changing the thinning number with a common shooting distance and a fixed shooting distance.
  • FIG. 8 shows the frequency when using a grid with a focusing distance of 1800 mm and changing the shooting distance.
  • FIG. 8 is a graph showing the correspondence between the shooting distance and the frequency response, in which the vertical axis shows the frequency response, the horizontal axis shows the shooting distance, the center of the horizontal axis is 0, and is symmetrically depicted. As shown in FIG. 8, the frequency of grid stripes appearing in the image changes even when the same grid is used due to different shooting distances.
  • the X-ray diagnostic imaging apparatus 10 prepares calibration data corresponding to the number of thinnings ⁇ the number of imaging distances in advance, and refers to the calibration data that matches the imaging conditions obtained by the frequency calculation unit 15c in step S12.
  • the frequency may be determined.
  • the frequency calculation unit 15c sets the thinning number as a variable and sets the shooting distance as a variable at each shooting.
  • the grid fringe frequency may be obtained according to the distance.
  • the frequency calculation unit 15c may obtain a grid stripe frequency.
  • the defective pixel correction unit 15d corrects defective pixels of the X-ray flat panel detector 14 in accordance with the frequency band obtained by the frequency calculation unit 15c.
  • Step S31 The defective pixel determination unit determines whether or not the defective pixel is included in the image data subjected to the thinning process in step S21. If it is included, the process proceeds to step S41. If it is not included, the process proceeds to step S51.
  • Step S41 First, the defective pixel correction unit 15d reads the luminance of the image data obtained by the image data acquisition unit 15a and subjected to the thinning process for each pixel column along the grid stripe orthogonal direction (see FIG. 9). Then, it is determined whether the luminance fluctuates to a predetermined value or more with the position of the defective pixel as a boundary, that is, whether the defective pixel is at the boundary of the luminance base value (S41).
  • the above-mentioned predetermined value or more is a value that exceeds the amount of change in luminance due to grid stripes.
  • the defective pixel correction unit 15d proceeds to step S42, and if negative, proceeds to step S43.
  • the position of the defective pixel is known at the time of shipment of the X-ray flat panel detector 14, and the position information is recorded in a storage device such as a ROM (not shown) of the X-ray image diagnostic apparatus 10. Therefore, the defective pixel correction unit 15d acquires the position information of the defective pixel by referring to this position information.
  • Step S42 The defective pixel correction unit 15d performs defective pixel correction when the defective pixel is at the boundary. More specifically, in the pixel row read out in step S41, on one side of the defective pixel (for example, on the right side or the left side of the defective pixel when the grid stripe orthogonal direction is defined as the left-right direction) Defective pixel correction is performed using the located pixel (S42). For example, the luminance of the pixel adjacent on the right side of the defective pixel is interpolated as the luminance of the defective pixel. As a result, blurring of the outline of the image data due to defective pixel correction can be prevented.
  • Step S43 The defective pixel correction unit 15d performs defective pixel correction when there is no defective pixel at the boundary. First, the defective pixel correction unit 15d determines whether the grid fringe frequency calculated by the frequency calculation unit 15c in step S21 is in a high frequency band or a low frequency band, and if it is a high frequency band, proceeds to step S44 in the low frequency band. If there is, the process proceeds to step S45 (S43).
  • Step S44 The defective pixel correction unit 15d performs defective pixel correction in the high frequency band.
  • FIG. 9 is an explanatory diagram showing defective pixel correction processing according to the present embodiment
  • FIG. 9 (a) shows defective pixel correction processing in the high frequency band
  • FIG. 9 (b) shows defective pixel correction processing in the low frequency band. Indicates.
  • the luminance of the pixel column read out in step S41 repeats a high peak (mountain) and a low peak (valley) at each sampling point.
  • the defective pixel correction unit 15d generates a luminance distribution pattern 74 of the pixel column read out in step S41, and estimates whether a high peak (mountain) or a low peak (valley) comes to the position of the defective pixel. . Then, when it is estimated that a high peak (crest) comes to the position of the defective pixel, the pixel value of the defective pixel is obtained using the closest high peak (crest) in both the left and right directions across the defective pixel. If it is estimated that a low peak (valley) comes to the position of the defective pixel, the pixel value of the defective pixel is obtained using the closest low peak (valley) in both the left and right directions with the defective pixel in between. For example, in the example of FIG.
  • the defective pixel 1 has a low peak (valley), so the pixel value of the defective pixel 1 is the hatched pixel in FIG.
  • the average value of the luminance of the pixel 70 with the lowest peak (valley) closest to the left side to the pixel 1 and the luminance of the pixel 71 with the lowest peak (valley) closest to the right side is interpolated.
  • the defective pixel correction unit 15d is assumed to have a high peak (mountain) for the defective pixel 2, the pixel 72 having the highest peak (mountain) closest to the defective pixel 2 on the left side and the pixel on the right side most. Interpolate the average value with the brightness of the pixel 73 of the near high peak (mountain). If there is a peak on only one of the pixels with the defective pixel in between, interpolation may be performed using the luminance of the one peak.
  • the result of the defective pixel correction according to this embodiment is compared with the conventional correction result.
  • the luminance distribution pattern 75 in FIG. 9A is a pattern obtained as a result of conventional correction
  • the luminance distribution pattern 76 is a pattern obtained as a result of correction according to the present embodiment.
  • correction is performed using the pixel value adjacent to the defective pixel, so that the defective pixel 1 is corrected using a high peak (mountain) and a high peak (mountain). Therefore, the frequency is broken at the defective pixel 1 portion.
  • a high peak (mountain) or a low peak (valley) comes to a defective pixel it is estimated whether a high peak (mountain) or a low peak (valley) comes to a defective pixel, and as a result of estimation, it is estimated that a low peak (valley) comes.
  • correction is performed using not the adjacent pixel values but the closest low peaks (valleys) on both sides, so that it is possible to prevent the frequency from being broken at the defective pixel 1 portion.
  • a high peak (mountain) it is estimated that a high peak (mountain) will come, and correction is performed using the brightness of the closest high peak (mountain) instead of the adjacent pixel, so that the grid fringe frequency is broken. prevent.
  • Step S45 The defective pixel correction unit 15d performs defective pixel correction in the low frequency band. Based on FIG. 9B, the defective pixel correction in the low frequency band will be described.
  • the luminance of the pixel column read out in step S41 indicates a high peak (mountain), a low peak (valley), and an intermediate value of the peak value depending on the sampling point. Therefore, the defective pixel correction unit 15d generates a luminance distribution pattern of the pixel column read out in step S41, and any of the high peak (mountain), low peak (valley), and intermediate value of the peak value is located at the position of the defective pixel. Estimate what will come.
  • the closest high peak (crest) or low peak (valley) in both the left and right directions across the defective pixel is used.
  • the pixel value of the defective pixel is obtained. Further, when it is estimated that an intermediate value of the peak value comes to the position of the defective pixel, the pixel value of the defective pixel is interpolated using the pixel value adjacent to the defective pixel.
  • the defective pixel correction unit 15d generates a luminance distribution pattern 83 before correction, and an intermediate value of peak values comes to the defective pixel 1 using a technique such as pattern matching. Estimated. Therefore, the defective pixel correction unit 15d calculates an average value of the luminance of the pixel 80 adjacent to both sides of the defective pixel 1 and the luminance of the pixel 81, and interpolates the defective pixel 1 with the calculated value.
  • the defective pixel correction unit 15d estimates that the defective pixel 2 has a high peak (mountain). Therefore, the average value of the luminance of the pixel 81 with the highest peak (mountain) closest to the defective pixel 2 on the left side and the luminance of the pixel 82 with the highest peak (crest) closest to the right side is interpolated.
  • the result of the defective pixel correction according to this embodiment is compared with the conventional correction result.
  • the conventional correction when the conventional correction is performed (the luminance distribution turn 84 in FIG. 9 (b)), when the defective pixel is other than the peak, the frequency is not broken even by the conventional correction, but the defective pixel is not In the case of a high peak (mountain), for example, a defective pixel 2, the frequency is broken.
  • the defective pixel correction according to the present embodiment it is possible to correct by using the luminance of the adjacent pixel in the case other than the peak, and to correct the defective pixel based on the same peak in the case of the peak value. .
  • the frequency for one period may be matched, or the offset of the base density may be corrected.
  • Step S51 The grid stripe removal unit 15e uses the thinning number obtained by the thinning number determination unit 15b for the image data that has been corrected for defective pixels in Steps S42, S44, and S45, or the image data that has been determined to have no defective pixels. Accordingly, mirroring processing is performed (S51). This mirroring process is a pre-process for the Fourier transform process after step S52.
  • FIG. 10 is an explanatory diagram showing grid stripe removal processing, where (a) shows mirroring processing, (b) shows an example of one-dimensional FFT processing results, and (c) shows processing results of the bandpass filter. An example is shown, and (d) shows an example of the inverse one-dimensional FFT processing result.
  • the left and right image areas of the image area 90 are added by inverting the edges of the image area 90 (for example, 90L) along the grid stripe orthogonal direction. It is processing.
  • a signal component (image region 91) in a predetermined number of pixels from the left end of the image region 90 (this is determined with reference to Table 2. Details will be described later) Invert 90L to the left and add.
  • the added area is a mirroring area 91 'in FIG.
  • a signal component (image region 92) in a predetermined pixel number range from the right end of the image region 90 is added by being reversed leftward with the left end 90R of the image region 90 as the center.
  • the added area is a mirroring area 92 'in FIG.
  • Table 2 is a table that defines the number of pixels to be mirrored according to the thinning number. Similarly to Table 1, this table may be generated in advance, stored in the image processing apparatus 15 when the X-ray diagnostic imaging apparatus 10 is installed, and configured to be referred to by the grid stripe removing unit 15e as needed. Table 2 shows the ⁇ decimation number '', the ⁇ image size in the grid stripe orthogonal direction '' after decimation, and the primary Fourier transform processing (hereinafter referred to as ⁇ FFT '') necessary for the decimation number.
  • ⁇ FFT primary Fourier transform processing
  • the pixel after mirroring is based on the difference between the minimum pixel of the Fourier transform and the pixel size in the orthogonal direction of the grid stripe after thinning, as a criterion for judging how many pixels exist at both end pixels. This is a Fourier transform process (step S52) to be described later, and after performing a bandpass filter process (removing a specific frequency response) (step S53), an inverse Fourier transform process (step S54), Aliasing (artifact) occurs. This is to prevent the aliasing from being displayed in the final output image by cutting out the artifact portion.
  • the image areas 91 and 92 are mirroring areas composed of areas 137 pixels inside from the left and right end portions 90L and 90R of the image area 90. As a result, the number of pixels after mirroring is 1024 pixels (750 + 137 ⁇ 2).
  • Step S52 The grid stripe removal unit 15e performs one-dimensional FFT processing on the mirrored image data (S52).
  • FIG. 10 (b) shows a graph 93 showing the one-dimensional FFT processing result.
  • the graph 93 is a graph in which the vertical axis indicates the frequency response, the horizontal axis indicates the frequency, and the center of the horizontal axis is 0 and is displayed symmetrically.
  • Step S53 The grid stripe removal unit 15e performs bandpass filter processing for removing the frequency components of the grid stripes from the frequency components of the image data after the one-dimensional FFT processing (S53).
  • FIG. 10 (c) shows the bandpass filter processing.
  • a graph 94 showing the results is shown.
  • the graph 94 is a graph in which the vertical axis indicates the frequency response, the horizontal axis indicates the frequency, and the center of the horizontal axis is 0 and is displayed symmetrically.
  • Steps S54, S55 The grid stripe removal unit 15e performs one-dimensional inverse FFT processing on the image data after the bandpass filter processing (S54).
  • FIG. 10 (d) shows an image obtained after the one-dimensional inverse FFT processing. Since aliasing has occurred at the left and right end portions of the image 95, the grid stripe removing unit 15e cuts out only the central portion of the image 95, thereby obtaining a final image free from artifacts and from which the grid stripes are removed. (S55).
  • Step S61 Thereafter, gradation processing is performed on the final image cut out in step S55 by the gradation processing unit 15g, and the image is displayed on the preview image display device 16 (S61).
  • FIG. 11 is a comparative explanatory diagram of the effect of the present embodiment and the effect of the conventional method.
  • FIG. 11 (a) When there is a defective pixel column 96 in a direction orthogonal to the grid stripes, and this defective pixel column 96 is corrected using a defective pixel correction by a conventional method, that is, using a pixel value adjacent to the defective pixel, FIG.
  • the frequency of the grid stripe changes as shown in b).
  • grid stripe removal is performed on this image, an artifact occurs at a position where the frequency of the grid stripe changes as shown in FIG.
  • defective pixel correction is performed on the image of FIG. 11A so that the grid fringe frequency is not changed as shown in FIG. 11D.
  • the grid stripe component is removed from this image, an image free from artifacts is obtained as shown in FIG. 11 (e).
  • the grid fringe frequency can be obtained according to the thinning number, and correction according to the frequency band can be performed. That is, when a defective pixel is corrected, the defective pixel can be corrected without breaking the grid stripe frequency. Then, grid stripe removal processing is performed on the image data after the defective pixel correction. At this time, even when the grid fringe frequency is in the low frequency band, the Fourier transform is performed after increasing the number of data by mirroring processing according to the thinning number, so that the frequency resolution is improved and only the grid fringe is accurately obtained. It can be removed.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Physics & Mathematics (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Optics & Photonics (AREA)
  • Pathology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Veterinary Medicine (AREA)
  • Heart & Thoracic Surgery (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Image Processing (AREA)

Abstract

Selon la présente invention, afin d'éliminer les bandes de grille de données d'image soumises à un traitement d'amincissement sans causer des artefacts, des données d'image obtenues par capture d'une image d'un sujet à l'aide d'un dispositif de diagnostic d'imagerie radiographique pourvu d'une grille sont acquises (S11), l'indice d'amincissement est déterminé (S13), la fréquence de bandes de grille incluses dans les données d'image est calculée sur la base de l'indice d'amincissement déterminé (S21), une correction de pixel défectueux correspondant à la fréquence calculée des bandes de grille est effectuée (S41-S45), et les bandes de grille sont enlevées des données d'image corrigées (S51-S55).
PCT/JP2011/053895 2010-02-24 2011-02-23 Dispositif de diagnostic par imagerie radiographique, et programme et procédé de traitement d'image médicale WO2011105388A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2012501798A JP5848697B2 (ja) 2010-02-24 2011-02-23 Ｘ線画像診断装置
CN201180010693.7A CN102770075B (zh) 2010-02-24 2011-02-23 X射线图像诊断装置和医用图像处理方法

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2010-038919 2010-02-24
JP2010038919 2010-02-24

Publications (1)

Publication Number Publication Date
WO2011105388A1 true WO2011105388A1 (fr) 2011-09-01

Family

ID=44506794

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2011/053895 WO2011105388A1 (fr) 2010-02-24 2011-02-23 Dispositif de diagnostic par imagerie radiographique, et programme et procédé de traitement d'image médicale

Country Status (3)

Country Link
JP (1) JP5848697B2 (fr)
CN (1) CN102770075B (fr)
WO (1) WO2011105388A1 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2016172098A (ja) * 2013-03-28 2016-09-29 富士フイルム株式会社 放射線画像処理装置および方法並びにプログラム
KR101751750B1 (ko) 2015-10-16 2017-06-29 주식회사 레이언스 X선 의료 영상에서의 디펙트 보정 방법
WO2017145605A1 (fr) * 2016-02-22 2017-08-31 株式会社リコー Dispositif de traitement d'image, dispositif de capture d'image, système de commande d'appareil de corps mobile, procédé de traitement d'image, et programme
CN111275639A (zh) * 2020-01-17 2020-06-12 深圳市安健科技股份有限公司 X射线图像的线像素缺陷校正方法及终端

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6362914B2 (ja) * 2014-04-30 2018-07-25 キヤノンメディカルシステムズ株式会社 Ｘ線診断装置及び画像処理装置
CN105096260A (zh) * 2014-05-12 2015-11-25 陈跃泉 一种消除数字式x光机图像栅纹的方法
JP2017142566A (ja) * 2016-02-08 2017-08-17 富士ゼロックス株式会社 端末装置、診断システムおよびプログラム
DE102016206559B3 (de) * 2016-04-19 2017-06-08 Siemens Healthcare Gmbh Verfahren zur Korrektur eines Röntgenbilds auf Effekte eines Streustrahlenrasters, Röntgeneinrichtung, Computerprogramm und elektronisch lesbarer Datenträger
CN108065944B (zh) * 2016-11-14 2021-10-22 上海西门子医疗器械有限公司 平板探测器与滤线栅的适配方法和设备及医疗成像系统
JP2019105919A (ja) * 2017-12-11 2019-06-27 シャープ株式会社 平滑画像生成装置、異常判定装置、平滑画像生成方法、およびプログラム

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003250786A (ja) * 2002-02-28 2003-09-09 Konica Corp 画像処理装置、画像処理方法、プログラムおよび記憶媒体
JP2008136520A (ja) * 2006-11-30 2008-06-19 Hitachi Medical Corp Ｘ線画像診断装置
JP2008229194A (ja) * 2007-03-23 2008-10-02 Hitachi Medical Corp Ｘ線画像診断装置
WO2009130829A1 (fr) * 2008-04-22 2009-10-29 株式会社島津製作所 Procédé pour éliminer un moiré dans des images radiographiques par rayons x et dispositif d'imagerie par rayons x l'utilisant

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7142705B2 (en) * 2001-05-01 2006-11-28 Canon Kabushiki Kaisha Radiation image processing apparatus, image processing system, radiation image processing method, storage medium, and program
JP4850730B2 (ja) * 2006-03-16 2012-01-11 キヤノン株式会社 撮像装置、その処理方法及びプログラム

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003250786A (ja) * 2002-02-28 2003-09-09 Konica Corp 画像処理装置、画像処理方法、プログラムおよび記憶媒体
JP2008136520A (ja) * 2006-11-30 2008-06-19 Hitachi Medical Corp Ｘ線画像診断装置
JP2008229194A (ja) * 2007-03-23 2008-10-02 Hitachi Medical Corp Ｘ線画像診断装置
WO2009130829A1 (fr) * 2008-04-22 2009-10-29 株式会社島津製作所 Procédé pour éliminer un moiré dans des images radiographiques par rayons x et dispositif d'imagerie par rayons x l'utilisant

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2016172098A (ja) * 2013-03-28 2016-09-29 富士フイルム株式会社 放射線画像処理装置および方法並びにプログラム
KR101751750B1 (ko) 2015-10-16 2017-06-29 주식회사 레이언스 X선 의료 영상에서의 디펙트 보정 방법
WO2017145605A1 (fr) * 2016-02-22 2017-08-31 株式会社リコー Dispositif de traitement d'image, dispositif de capture d'image, système de commande d'appareil de corps mobile, procédé de traitement d'image, et programme
JPWO2017145605A1 (ja) * 2016-02-22 2018-12-13 株式会社リコー 画像処理装置、撮像装置、移動体機器制御システム、画像処理方法、及びプログラム
US11064177B2 (en) 2016-02-22 2021-07-13 Ricoh Company, Ltd. Image processing apparatus, imaging apparatus, mobile device control system, image processing method, and recording medium
CN111275639A (zh) * 2020-01-17 2020-06-12 深圳市安健科技股份有限公司 X射线图像的线像素缺陷校正方法及终端
CN111275639B (zh) * 2020-01-17 2023-06-20 深圳市安健科技股份有限公司 X射线图像的线像素缺陷校正方法及终端

Also Published As

Publication number Publication date
CN102770075B (zh) 2015-01-28
JPWO2011105388A1 (ja) 2013-06-20
JP5848697B2 (ja) 2016-01-27
CN102770075A (zh) 2012-11-07

Similar Documents

Publication Publication Date Title
JP5848697B2 (ja) Ｘ線画像診断装置
KR101389841B1 (ko) 파노라마 영상 데이터 제공 방법 및 장치
JP5815048B2 (ja) Ｘ線ｃｔ装置
US6901132B2 (en) System and method for scanning an object in tomosynthesis applications
JP5278544B2 (ja) 同期型グリッドの箔影除去方法およびそれを用いた放射線撮影装置
JP5370362B2 (ja) 画像補正処理装置及び画像補正処理方法
WO2011036961A1 (fr) Dispositif de tomodensitométrie à rayons x
JP4368350B2 (ja) Ｘ線画像診断装置
US9655570B2 (en) Radiological image processing apparatus and radiological image processing program
US20140363071A1 (en) Image processing apparatus and method
JP2017063907A (ja) 断層画像生成装置、方法およびプログラム
JP5526775B2 (ja) 放射線撮像装置
JP2012090659A (ja) 医用画像処理装置、医用画像撮影装置、及び医用画像処理プログラム
JP2012029720A (ja) 画像処理装置及び方法、並びに放射線撮影システム
JP5527481B2 (ja) Ｘ線診断装置およびｘ線診断用プログラム
JP5239585B2 (ja) Ｘ線撮像装置
JP5753502B2 (ja) 画像処理装置および方法
JP2004073449A (ja) Ｘ線撮影装置
JP5821790B2 (ja) Ｘ線診断装置
JP5884680B2 (ja) 放射線グリッドの箔影除去方法およびそれを用いた放射線撮影装置
JP2017070590A (ja) 画像処理装置及びその制御方法、コンピュータプログラム
US8503612B2 (en) Radiographic apparatus
JP2006122084A (ja) Ｃｔ装置、画像処理装置、画像処理方法、プログラム、記録媒体。
JP2024078179A (ja) 画像処理装置およびその制御方法、プログラム
WO2010018480A1 (fr) Combinaison d'acquisitions radiographiques avec dimensions de foyer variées permettant d'améliorer la qualité de l'image

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: 201180010693.7

Country of ref document: CN

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 11747349

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2012501798

Country of ref document: JP

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 11747349

Country of ref document: EP

Kind code of ref document: A1