JP2006230484A - X-ray diagnostic apparatus, image processing method and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an X-ray diagnostic apparatus which does not generate false images at the time of performing defective pixel correction processing and resize processing, an image processing method and an image processing program. <P>SOLUTION: In the X-ray diagnostic apparatus comprising an X-ray image detector for detecting X-rays exposed from an X-ray tube to a subject and an image processing part for processing image signals from the X-ray image detector, the image processing part replaces at least one of the pixel value of a pixel after matrix transformation processing and the pixel value of a defective pixel with the pixel value of a prescribed pixel in the case of performing at least one of the matrix transformation processing of an output image from the X-ray image detector and the correction processing of the defective pixel of the X-ray image detector. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an X-ray diagnostic apparatus, an image processing method, and an image processing program.

  In the X-ray circulatory examination, an operation of advancing a guide wire or a catheter is performed while observing a fluoroscopic image. In this case, it is necessary to advance the guide wire or catheter along the blood vessel, but the blood vessel cannot be observed with an X-ray image. For this reason, a contrast agent is injected into a blood vessel, the blood vessel is contrasted, and a guide wire catheter is advanced using an image (contrast image) at this time. Here, the state of the contrast agent flowing can be observed for several seconds, for example, but a peak hold process is performed on a plurality of images obtained in the meantime to create one image.

In this “peak hold processing”, the smallest value (the pixel having the minimum value) or the largest value (the pixel having the maximum value) is selected from the pixel values of the same pixels of the plurality of images, and the image is selected. This is a process of creating one image using pixel values selected for all the pixels in the image. Here, the minimum value and the maximum value are selectively used according to the type of contrast agent (for example, positive (CO ₂ etc.), negative (iodine etc.)).

  FIG. 5 shows the flow of processing when a road map image is obtained by the peak hold processing. As shown in FIG. 5, a fluoroscopic image is acquired (S1), and resize processing and interpolation processing, which will be described in detail later, are performed on the fluoroscopic image (S2). Next, peak detection processing is performed on a plurality of images after resizing processing and interpolation processing (S3), and as a result, a road map image is obtained (S4). A road map image can be obtained by such a series of processes.

  By the way, in the X-ray detector, there are defective pixels that are normally generated in the manufacturing process. This defective pixel cannot be made zero within the practical yield range. Therefore, using pixel values of a plurality of normal pixels existing around the defective pixel. A defective pixel correction process is performed. This correction processing generally calculates a weighted average according to the distance (for example, inversely proportional to the distance) from the pixel values of a plurality of surrounding normal pixels, and this result is used as the pixel value of the defective pixel. Is done. In such a correction process, the pixel value of the normal pixel includes noise (X-ray quantum noise and circuit noise), but this is averaged to obtain the pixel value of the defective pixel. The noise of the pixel value of the pixel is smaller than that of the normal pixel. Therefore, in the case of a line defect in which defective pixels are arranged in a line, pixels with low noise are arranged in a line.

  The X-ray detector has a predetermined matrix size. When the whole or a part of the matrix is output to the image processing apparatus, the predetermined matrix size is used to simplify the processing in the image processing apparatus. It has been converted to output. This matrix conversion is called “resizing processing”. In the resizing process, in order to calculate the pixel value of the pixel in the resized image, a weighted average of a plurality of pixels of the original image located around the pixel is calculated, and this is used as the pixel value of the resized pixel. Yes. The pixel values of the plurality of pixels of the original image include noise (X-ray quantum noise and circuit noise), and this is averaged to obtain the pixel value of the resized pixel. The noise of the pixel value of the pixel after resizing may be smaller than that of a normal pixel. For example, when the resized pixel position matches the pixel position of the original image, the weight of the original image pixel corresponding to the resized pixel position is maximized, and the result of the weighted average is the result of the original image. Since it becomes the pixel value itself of the pixel, there is no change in noise. On the other hand, when the position of the resized pixel is equally spaced from the plurality of pixels of the original image, the weight of the plurality of pixels is equal, and at this time, the noise of the resized pixel is minimized. Since the magnitude of noise in each pixel after resizing is determined by the position of the pixel, it is regularly repeated on the image. For this reason, the magnitude of the noise of the resized image is arranged in a grid pattern on the image.

  As described above, when the defective pixel correction process or the resizing process is performed, the target pixel is basically smaller in noise than the normal pixel or the original pixel, and is arranged in a linear or grid pattern. When peak detection processing is performed on such an image, there is a problem in that a linear or grid pattern appears in the road map image because the magnitude of noise differs within the screen.

  It is an object of the present invention to provide an X-ray diagnostic apparatus, an image processing method, and an image processing program that do not generate a false image when performing defective pixel correction processing and resizing processing.

  The X-ray diagnostic apparatus according to one aspect of the present invention performs replacement processing instead of performing interpolation processing when performing resizing processing or defect correction. This replacement process causes a problem of missing pixels, but there are few problems in a fluoroscopic inspection using a fluoroscopic roadmap image.

  An X-ray diagnostic apparatus according to another aspect of the present invention performs peak detection processing before defect correction or resizing processing.

  The X-ray diagnostic apparatus according to still another aspect of the present invention adds a noise component calculated from the standard deviation to a weighted average value from surrounding pixels when performing resizing processing or defect correction.

  According to the present invention, it is possible to prevent generation of a false image when performing defective pixel correction processing and resizing processing.

  Embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram of an X-ray diagnostic apparatus according to an embodiment of the present invention.

  As shown in FIG. 1, the X-ray diagnostic apparatus 10 according to this embodiment includes an X-ray high voltage apparatus 11, a C arm 21, a TV camera control unit 23, a digital image processing unit 25, and a display unit 27. Have The X-ray high voltage apparatus 11 generates a high voltage for irradiating the subject P with X-rays from the X-ray tube 13. The C arm 21 includes an X-ray tube 13 at one end thereof, an image intensifier 15 for converting X-rays into an optical image at the other end, an optical system 17 for condensing the optical image, and this And a TV camera 19 composed of a CCD for converting the collected optical image into a TV video signal by changing the gain according to the brightness. The TV camera control unit 23 outputs the TV video signal in correspondence with the fluoroscopic start signal from the X-ray high voltage apparatus 11 and the rate signal of X-ray pulse generation. The digital image processing unit 25 converts the TV video signal output from the TV camera control unit 23 into a digital signal, and performs image processing such as correction processing and image resizing processing. The display unit 27 displays the signal whose outline is enhanced by the digital image processing unit 25 on the monitor.

The operation of the X-ray diagnostic apparatus according to the first embodiment of the present invention configured as described above will be described.
Conventionally, as described above, when resizing or correcting a defective pixel, the pixel value is calculated by a weighted average of a plurality of pixels around the defective pixel. In this embodiment,
FIG. 2 is a diagram showing the flow of the image processing method according to the first embodiment of the present invention. In FIG. 2, the same processes as those in FIG. In the following description, there may be a case where only correction of a defective pixel is mentioned, but this is also included in the resizing process.
As shown in FIG. 2, first, a fluoroscopic image such as a blood vessel image is acquired, and resizing processing and defect pixel correction processing are performed (S2 ′). In this case, in this embodiment, defect image correction is performed. In this case, the defective pixel is not corrected by a weighted average of normal pixels as in the prior art, but the defective pixel is corrected by a process in which one of the pixels around the defective pixel is set to the luminance of the defective pixel (replacement). Is going. Here, in the replacement process, it is preferable to replace the pixel closest to the defective pixel. The pixels closest to the defective pixel are the upper, lower, left, and right pixels adjacent to the defective pixel. However, any pixel may be used as long as these upper, lower, left, and right pixels are normal pixels. The defective pixel may be replaced with any of the four pixels on the upper, lower, left, and right sides. For example, if the defective pixel is replaced with the pixel on the right side of the defective pixel, the other defective pixel is also replaced with the normal pixel on the right side. It is preferable to make it.
If the resizing process or defective pixel replacement process is completed in S2 ', peak detection is performed for a plurality of processed images (S3), and a road map image is obtained (S4).

  By the above processing, the noise of the pixel value of the pixel to be obtained becomes the same as the noise of the neighboring pixels. For this reason, even if the peak detection process in S3 is performed, the same result as that of the neighboring pixels can be obtained, so that no false image is generated.

The second embodiment will be described with reference to FIG. In FIG. 3, the same parts as those in FIG. 5 are denoted by the same reference numerals, and detailed description thereof is omitted.
In the present embodiment, the same processing as the conventional one is performed, but the processing order is changed. Specifically, in this embodiment, after performing peak detection (S3), resizing processing and interpolation processing are performed (S2). Note that the resizing process and the interpolation process in this case are performed by calculating the pixel value by a weighted average of normal pixels as in the conventional case.

  In this way, by changing the processing order, that is, by performing the peak detection process before performing the resizing process and the defective pixel correction, the noise of each pixel is not affected by the weighted average during the peak detection process. . For this reason, even if the resizing process and the interpolating process are obtained by the weighted average as in the prior art, a problematic false image does not occur.

  A third embodiment will be described with reference to FIG. In FIG. 4, the same parts as those in FIG.

  As described above, when the pixel value of the defective pixel or the pixel value in the resizing process is obtained by simply performing the averaging using the pixel values of a plurality of pixels, the noise component becomes smaller than the noise component of one pixel. The reason for this is that the noise component is due to a statistical error. Therefore, when a plurality of pixel values are weighted and averaged, the noise component basically approaches 0 as the pixel value increases. Therefore, in this embodiment, the noise component reduced by the weighted average is added to the corrected pixel value, and this is used as the interpolation result. As a result, it is possible to correct a decrease in noise components due to pixel interpolation.

  Hereinafter, specific embodiments will be described.

The interpolation calculation method using normal pixels is as follows. When N peripheral normal pixels are used, and interpolation is performed using a weighted average, the obtained pixel value is expressed by the following equation.

Where w _ij : weighting factor
P _ij : Pixel value of surrounding pixels
When the pixel value of a defective pixel (or a pixel in resizing processing, hereinafter referred to as “defective pixel or the like”) is obtained by the expression (1), as described above, the noise component is a statistical error component. It becomes smaller than the noise component for one pixel value. Therefore, with the configuration shown in FIG. 4, the noise component calculated by the algorithm (hereinafter referred to as “pseudo noise component”) is added to the pixel value obtained by the weighted average to compensate for the noise component.

  First, referring to FIG. 4, an outline of the operation of adding pseudo noise components will be described, and then an algorithm for calculating pseudo noise components will be described.

  As shown in FIG. 4, a weighted average of peripheral pixels such as defective pixels in the obtained fluoroscopic image (S1) is calculated to obtain pixel values such as defective pixels (S5). At the same time, the square root of variance (standard deviation SD) with respect to the weighting coefficients of peripheral pixels such as defective pixels in the acquired image is obtained (S6), and the product of this result and a preset constant k is obtained (S8).

  Further, a random number generator (not shown) generates a random number R (for example, -1 <R <1) (S7), and a product is obtained by multiplying the random number and the product obtained in S8 (S9). The result is a pseudo noise component. Then, the sum of the pseudo noise component and the pixel value obtained in S5 is obtained, and this result is used as a pixel value of a defective pixel or the like. Subsequent operations are the same as those in the first embodiment, and a description thereof will be omitted.

  In the above operation, the constant k is set to a value that makes it most difficult to see the forgery on the interpolated image, but the actual value is set in the design / adjustment stage. Further, the constant k may be multiplied at any stage. For example, the constant k may be multiplied by the product of the standard deviation and the random number, or the product of the random number and the constant k is obtained, and the result and the standard deviation are obtained. And a pseudo noise component may be obtained. Furthermore, the random number R may be generated in the range of −k <R <k.

Next, a noise component calculation algorithm will be described. The noise component is
Noise component = k × SD × R (2)
Where k: constant (> 1)
SD: square root of variance
R: random number (-1 <R <1)
Is required. Here, when the variance D is specifically obtained, the variance D is

Where N: number of surrounding pixels
w _ij ′: Weighting factor used for variance calculation. However, Σw _ij '/ N = 1
P _ij : Pixel value of the peripheral pixel at the position (i, j)
P _ijav : Average pixel value of surrounding pixels
It is represented by Here, _assuming P _ijav = Pbar_w, and expanding equation (3),

D = {N / (N-1)} · {P2bar_w '− 2Pbar_w · Pbar_w' + Pbar_w ² } (5)
And when w = w '
D = {N / (N-1)} ・ {P2bar_w −Pbar_w ² } (6)
Is required. Accordingly, the variance is obtained by equation (6).

  Actually, the smaller the number N of peripheral pixels is, the easier it is to realize an arithmetic circuit. Therefore, it is preferable to reduce N. For example, the case where N = 2 and w = w ′ = 1 is shown below.

D = {(P1 + P2) ・ (P1-P2)} / 2
If N is small, accurate dispersion cannot be obtained, but useful results can be obtained for the purpose of reducing false images due to peak detection processing.

The present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the scope of the invention at the stage of implementation.
For example, the random number is not generated by an independent generator, but may be determined from surrounding pixel values. In this case, there is also a method of setting −1 or 1 depending on the value of the lower 1 bit (of the addition result) of the peripheral pixel value. Further, any one of −1, −0.5, 0.5, and 1 may be used according to the lower 2 bits of the peripheral pixel value (addition result).
The constant k is determined in consideration of image effects at the time of design as described above. However, since the noise peak-to-peak value is larger than the noise SD, it is desirable that k> 1.
In the above embodiment, an example of an image intensifier is shown as a detector. However, the present invention is not limited to this, and the same effect can be obtained even when a flat detector (FPD) is applied as a detector. As a flat detector, either an indirect conversion method or a direct conversion method can be applied in the same manner.

  Further, the above embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements.

  In addition, for example, even if some structural requirements are deleted from all the structural requirements shown in each embodiment, the problem described in the column of the problem to be solved by the invention can be solved, and the effect described in the effect of the invention Can be obtained as an invention.

1 is a block diagram of an X-ray diagnostic apparatus according to an embodiment of the present invention. The figure which shows the flow of the image processing method which concerns on the 1st Embodiment of this invention. The figure which shows the flow of the image processing method which concerns on the 2nd Embodiment of this invention. The figure which shows the flow of the image processing method which concerns on the 3rd Embodiment of this invention. The figure which shows the flow of a process in the case of obtaining a road map image by a peak hold process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... X-ray diagnostic apparatus 11 ... X-ray high voltage apparatus 13 ... X-ray tube 15 ... Image intensifier 17 ... Optical system 19 ... TV camera 21 ... C arm 23 ... TV camera control part 25 ... Digital image processing part 27 ... Display section

Claims (12)

In an X-ray diagnostic apparatus comprising: an X-ray image detector that detects X-rays emitted from an X-ray tube to a subject; and an image processing unit that processes an image signal from the X-ray image detector;
The image processing unit performs at least one of matrix conversion processing of an output image from the X-ray image detector and correction processing of defective pixels of the X-ray image detector. An X-ray diagnostic apparatus, wherein a pixel value of at least one of a pixel value and a pixel value of the defective pixel is replaced with a pixel value of a predetermined pixel. The X-ray diagnostic apparatus according to claim 1, wherein the predetermined pixel is one of a plurality of pixels located around the pixel after the matrix conversion process and the defective pixel. Diagnostic device. The X-ray diagnostic apparatus according to claim 1, wherein the image processing unit includes:
Means for obtaining a peak image by performing a peak detection process using image signals for a plurality of continuously acquired images output from the X-ray image detector;
An X-ray diagnostic apparatus further comprising means for performing at least one of the matrix conversion process and the correction process of a defective pixel of the X-ray image detector using the peak image. An X-ray diagnostic apparatus comprising: an X-ray image detector that detects X-rays emitted from an X-ray tube to a subject; and an image processing unit that processes an image signal from the X-ray image detector. The image processor
Means for obtaining a peak image by performing a peak detection process using image signals for a plurality of continuously acquired images output from the X-ray image detector;
Means for performing at least one of the matrix conversion processing and the correction processing of defective pixels of the X-ray image detector using the peak image. In an X-ray diagnostic apparatus comprising: an X-ray image detector that detects X-rays emitted from an X-ray tube to a subject; and an image processing unit that processes an image signal from the X-ray image detector;
In the case where the image processing unit performs at least one of matrix conversion processing of an output image from the X-ray image detector and correction processing of defective pixels of the X-ray image detector,
Means for obtaining a pixel value of the pixel after the matrix conversion processing and a pixel value of the defective pixel;
Means for calculating a pseudo noise component;
An X-ray diagnostic apparatus comprising: means for adding the pixel value and the pseudo noise component to obtain a new pixel value. 6. The X-ray diagnostic apparatus according to claim 1, wherein peak detection processing is performed using image signals for a plurality of continuously acquired images output from the X-ray image detector. An X-ray diagnostic apparatus characterized by switching at least one of a conversion method of matrix conversion processing and a correction method of defect correction in processing to be performed and other processing. In an image processing method for processing an image detected by an image detector,
When performing at least one of matrix conversion processing of an output image from the image detector and correction processing of a defective pixel of the image detector, a pixel value of the pixel after the matrix conversion processing and a pixel value of the defective pixel An image processing method, wherein at least one pixel value is replaced with a pixel value of a predetermined pixel. In an image processing method for processing an image detected by an image detector,
Performing a peak detection process using image signals for a plurality of continuously acquired images output from the image detector to obtain a peak image;
Performing at least one of the matrix conversion processing and the correction processing of defective pixels of the X-ray image detector using the peak image. In an image processing method for processing an image detected by an image detector, at least one of matrix conversion processing of an output image from the X-ray image detector and correction processing of defective pixels of the X-ray image detector is performed In
Obtaining a pixel value of the pixel after the matrix conversion processing and a pixel value of the defective pixel;
Calculating a pseudo noise component;
And a step of adding the pixel value and the pseudo noise component to obtain a new pixel value. In a program for processing an image detected by an image detector,
When performing at least one of matrix conversion processing of an output image from the X-ray image detector and correction processing of defective pixels of the X-ray image detector, pixel values of the pixels after the matrix conversion processing and the defective pixels A program for executing a process of replacing at least one of the pixel values with a pixel value of a predetermined pixel. In a program for processing an image detected by an image detector,
A process for obtaining a peak image by performing a peak detection process using image signals for a plurality of continuously acquired images output from the image detector;
An image processing method comprising: performing at least one of the matrix conversion process and the correction process of a defective pixel of the X-ray image detector using the peak image. In a program for processing an image detected by an image detector, when performing at least one of matrix conversion processing of an output image from the image detector and correction processing of a defective pixel of the image detector,
A process for obtaining a pixel value of the pixel after the matrix conversion process and a pixel value of the defective pixel;
A process of calculating a pseudo noise component;
And a process of adding the pixel value and the pseudo noise component to obtain a new pixel value.

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