CN112884855A - Processing method and device for security check CT reconstructed image - Google Patents

Processing method and device for security check CT reconstructed image Download PDF

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CN112884855A
CN112884855A CN202110041358.9A CN202110041358A CN112884855A CN 112884855 A CN112884855 A CN 112884855A CN 202110041358 A CN202110041358 A CN 202110041358A CN 112884855 A CN112884855 A CN 112884855A
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row
data
interpolation
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projection data
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张韡
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Cgn Begood Technology Co ltd
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    • G06T11/003—Reconstruction from projections, e.g. tomography
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Abstract

The invention discloses a method and a device for processing a security check CT reconstructed image; the method comprises the steps that projection data collected by a security check CT wide row detector are subjected to row-to-row expansion, the pixel height after the expansion is half of the pixel height before the expansion, and the expansion row data are obtained by correlation calculation according to the two rows of projection data which are closest to the expansion row data; and performing iterative inter-row data expansion on the projection data according to the row spacing and the actual pixel width until the pixel height of the expanded projection data is less than or equal to the width of the actual pixel. The CT image processing device comprises a data acquisition module, a wide-row CT projection data expansion module and a reconstruction module. The invention has the advantages that: the expanded projection data is used for reconstruction while the existing scanning conditions are not changed, the axial data sampling rate is increased, windmill artifacts are greatly reduced, and the quality of reconstructed images is obviously improved.

Description

Processing method and device for security check CT reconstructed image
Technical Field
The present invention relates to the field of security CT imaging technologies, and in particular, to a method and an apparatus for processing a CT (Computed Tomography) reconstructed image.
Background
At present, a detector with a multi-row structure is generally adopted for carrying out spiral track scanning in security inspection CT, an acquisition system of the CT mainly comprises an X-ray light source, the detector (comprising a plane and an arc surface), a conveyor belt, a sliding ring and the like, the light source and the detector synchronously rotate around an object to be detected on the sliding ring, meanwhile, the light source emits X-rays, the X-rays are constrained by a collimator, and only the rays in a required range pass through the collimator to scan the object to be detected and reach a receiving area of the detector. After the data acquisition system acquires the data of the detector, the fault section of the detected object is reconstructed through a reconstruction algorithm.
The use of multirow detector can gather multirow data simultaneously at every turn, has increased CT device's scanning speed, but because the detector cost is higher, it is not practical to increase row number by a wide margin, and it is a solution to increase the row interval of detector.
The detection units on the detector are arranged in two dimensions along the row direction and the column direction of the detector. If the distance between detector rows is larger than the length or width of a row of detector units, the row spacing is considered too wide and the wide row detector schematic is shown in FIG. 1. When the data acquired by the detector is used for reconstruction, the axial sampling rate is reduced, artifacts can appear on a reconstruction slice, the artifacts are more obvious when the detail change is obvious like windmill artifacts, which are also called windmill artifacts, and in addition, the more rapid the moving speed of the conveyor belt is, the more serious the artifacts are. The quality of CT reconstructed images can be reduced due to the occurrence of windmill artifacts, so that the accuracy of judging whether the detected object is dangerous or not by a security inspector according to the images is influenced.
In the prior art, the windmill artifact is usually removed by adopting a method for improving the axial sampling rate, but the method needs equipment with hardware supporting high axial sampling rate, and has high equipment price and high cost; the other method is to start from software, remove the windmill artifact through an algorithm, the current main algorithm is to perform post-processing on an image to remove the windmill artifact, and the post-processing algorithm of the image has high complexity and low operation efficiency.
Disclosure of Invention
Aiming at the problem of windmill artifacts caused by wide row spacing, the invention provides a processing method of a security check CT reconstructed image, which can remove the windmill artifacts, improve the image quality and reduce the use cost. It is a further object of the invention to provide an apparatus for carrying out the method.
The technical scheme of the invention is as follows: a processing method for a security check CT reconstructed image comprises the following steps: s11, inter-row expansion is carried out on the projection data acquired by the wide-row detector in the multi-row detector, the height size of the pixel after the expansion is half of the height size of the pixel before the expansion, and the expanded row data is obtained by carrying out correlation calculation according to the two rows of data of the original projection data which are closest to the expanded row data; and S12, performing iterative inter-row data expansion on the projection data according to the row spacing and the actual pixel width until the pixel height of the expanded projection data is less than or equal to the actual pixel width.
The method for obtaining the expanded row data by performing the correlation calculation according to the row data of the original projection data comprises the following steps: s21, obtaining edge pixel point values of the extended row data according to linear interpolation of corresponding edge pixel points of the two rows of projection data which are closest to each other; s22, calculating the expansion row data non-edge pixel point according to six pixel points of original projection data in the eight neighborhoods of the expansion row data non-edge pixel point; the calculation method adopts an interpolation method based on the edge direction, the gradient of six pixel points passing through the direction of the pixel point to be interpolated is calculated, linear interpolation is carried out by using the pixel values of two pixel points with the minimum gradient to obtain the pixel of the point to be interpolated, and the edge information is kept while interpolation is carried out.
The method for processing the reconstructed image of the security check CT comprises the steps of interpolating projection data, increasing the line number of the image along with the interpolation, keeping the column number unchanged, setting the size of the image as M lines xN columns, and adopting an iterative formula that the line direction of the image changes every time of iterative interpolation as follows
Mm+1＝Mm×2-1
The superscript m is before interpolation, m +1 is after interpolation, m is 0,1,2, 0 is an original image, the number of lines after interpolation is 2 times the number of lines before interpolation minus 1, and the last line of pixels is directly assigned before interpolation;
pixel size, ymX is the size of the detector unit plus the spacing between the detector units, the pixel size after interpolation is half of the pixel size before interpolation, and the iterative formula is as follows
Figure BDA0002895977240000021
Wherein, the superscript m is before interpolation, m +1 is after interpolation, m is 0,1,2.. said, m is 0, original image,
each iterative interpolation is carried out, firstly, the ith data before interpolation is assigned to the 2i data after interpolation
Figure BDA0002895977240000022
Wherein, i is 0,1,2m1, j is 0,1,2,.. No. N-1, and then the 2i +1 th line of pixels to be interpolated is interpolated, which is divided into two cases:
1. when the column index value is j-0 and j-N-1, the corresponding pixel at the jth column of the 2 i-th row and the jth column of the 2(i +1) th row are added, and then divided by 2, and the result is assigned to the jth column of the 2i + 1-th row, the formula is as follows
Figure BDA0002895977240000023
2. When the column index value j is between 1 and N-2, the absolute value of the gradient centered at the jth column in the 2i +1 th row is calculated, as shown in FIG. 5, and the formula is as follows
Figure BDA0002895977240000024
When k is 0,1,2, the following table
Figure BDA0002895977240000025
Figure BDA0002895977240000031
According to the corresponding k value of the minimum gradient, kminCalculating the value of the jth pixel of the 2i +1 th row,
Figure BDA0002895977240000032
to this end MmInterpolation of projection data of size x N to Mm+1The projection data of x N size is completed and the above interpolation process is repeated until the pixel size in the row direction of the projection data, ym+1And is smaller than the length or width of the detection unit.
A processing device for a security check CT reconstructed image comprises a CT data acquisition module, a wide-row CT projection data expansion module and a reconstruction module, wherein the CT data acquisition module is sequentially connected with the wide-row CT projection data expansion module and the reconstruction module; the CT data acquisition module is used for acquiring original sampling data obtained by scanning a scanned object by a plurality of rows of wide-row detectors; the wide-row CT projection data expansion module is used for performing row-to-row expansion on the original axial wide-row projection data to obtain target axial projection data; and the reconstruction module is used for reconstructing an image according to the target axial projection data to obtain a target reconstruction image.
The invention has the advantages that: the expanded projection data is used for reconstruction while the existing scanning conditions are not changed, the axial data sampling rate is increased, windmill artifacts are greatly reduced, and the quality of reconstructed images is obviously improved.
Drawings
FIG. 1 is a schematic diagram of a wide array detector;
FIG. 2 is an unprocessed simulated projection data of a wide array detector;
FIG. 3 is a CT reconstructed image reconstructed using unprocessed simulated projection data from a wide-row detector;
FIG. 4 is an image of an interpolation process of projection data of a simulated wide-row detector;
FIG. 5 is an angular direction diagram corresponding to the absolute value of the minimum gradient;
FIG. 6 is a schematic diagram of the data of the wide-row detector after one expansion;
FIG. 7 is a plot of processed wide-swath simulated projection data for the present invention;
FIG. 8 is a CT slice view reconstructed by the processing method of the present invention;
fig. 9 is a functional block diagram of an image processing apparatus according to an embodiment of the present invention.
Detailed Description
The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of embodiments of the invention, as detailed in the following claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of embodiments of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the drawings, the same reference numerals are used to designate the same or similar components although they are designated in different drawings. For the purpose of clarity and conciseness, a detailed description of known functions and configurations incorporated herein will be omitted to avoid obscuring the subject matter in which the present invention is used.
At present, security inspection CT generally adopts a plurality of rows of detectors with wide row spacing to acquire data, and aims to increase scanning speed and reduce cost. However, when the CT axial sampling rate is reduced by the wide-row detector, and the projection data cannot completely reflect the object or tissue with fast transformation in the Z-axis direction, radial artifacts, which are referred to as windmill artifacts, are generated in the reconstructed image. The main approach to reduce windmill artifacts is to increase the CT axial sampling rate.
The invention provides a processing method of a security check CT reconstructed image, which increases the axial sampling rate of the security check CT, reduces windmill artifacts and improves the image quality by expanding projection data acquired by a wide-row detector.
The specific method comprises the following steps:
performing inter-row expansion on projection data acquired by a wide row detector in a plurality of rows of detectors, wherein the height size of pixels after the expansion is half of the height size of pixels before the expansion, and performing correlation calculation on the expanded row data according to two rows of data of original projection data which are closest to the expanded row data to obtain the expanded row data;
and performing iterative inter-row data expansion on the projection data according to the row spacing and the actual pixel width until the pixel height of the expanded projection data is less than or equal to the width of the actual pixel.
The method of expansion is described in detail below with reference to the accompanying drawings. Fig. 1 is a schematic diagram of arrangement of pixels of a wide-row detector, and the detector row spacing is wide, which affects the axial resolution of the CT apparatus.
For projection data, by interpolation expansion between lines, the number of lines of an image increases with interpolation, and the number of columns does not change, as shown in fig. 4, the size of the image is M lines xN columns, and an iterative formula for changing the number of lines of the image in each iterative interpolation is as follows:
Mm+1＝Mm×2-1
wherein m is the number of times of image expansion, and m is 1,2.. the number of lines after interpolation is 2 times the number of lines before interpolation minus 1; wide row detector pixel size, ymX, which can be considered as the size of the detector unit plus the size of the detector unit interval, and the pixel size after the inter-line interpolation expansion is half of the pixel size before the interpolation, the iterative formula is as follows
Figure BDA0002895977240000041
Wherein, m is the image expansion times, and m is 1,2.
Each iterative interpolation is carried out, firstly, the ith data before interpolation is assigned to the 2i data after interpolation
Figure BDA0002895977240000042
Wherein, i is 0,1,2m1, j is 0,1,2,.. No. N-1, and then the 2i +1 th line of pixels to be interpolated is interpolated, which is divided into two cases:
1. when the column index value is j-0 and j-N-1 (edge pixel), the corresponding jth pixel in the jth row 2i and jth pixel in the jth row 2(i +1) are added and then divided by 2, and the result is assigned to the jth column in the 2i +1 row, as follows
Figure BDA0002895977240000051
2. When the column index value j is between 1 and N-2, the absolute value of the gradient centered at the jth column in the 2i +1 th row is calculated, as shown in FIG. 5, and the formula is as follows
Figure BDA0002895977240000052
When k is 0,1,2, the following table
Figure BDA0002895977240000053
Calculating the value of the jth pixel of the 2i +1 th row according to the k value kmin corresponding to the minimum gradient
Figure BDA0002895977240000054
To this end MmInterpolation of projection data of size x N to Mm+1The projection data of x N size is completed and the above interpolation process is repeated until the pixel size in the row direction of the projection data, ym+1And is smaller than the length or width of the detection unit. FIG. 6 is a schematic diagram of detector arrangement after once expansion of the wide-row detector, with reduced row spacing, increased rows of projection data, and improved axial resolution. Fig. 7 shows the projection data of fig. 1 expanded by the above method. The CT slice effect of the image reconstruction of the figure 8 is obtained through the processing of the CT reconstruction module, and compared with the figure 3, the windmill projection is obviously reduced.
Referring to fig. 9, a functional block diagram of an image processing apparatus according to an embodiment of the present invention:
fig. 9 includes a CT data acquisition module, a data expansion module, and a CT reconstruction module. The CT data acquisition module acquires wide-row projection data acquired by a wide-row detector; the data expansion module expands the projection data of the wide-row detector and increases the axial resolution; and finally, obtaining a target CT slice image without windmill projection through reconstruction by a reconstruction module.
The above description is only for implementing the embodiments of the present invention, and those skilled in the art will understand that any modification or partial replacement without departing from the scope of the present invention shall fall within the scope defined by the claims of the present invention, and therefore, the scope of the present invention shall be subject to the protection scope of the claims.
The present invention has not been described in detail, partly as is known to the person skilled in the art.

Claims (4)

1. A processing method of a security check CT reconstruction image is characterized by comprising the following steps: the method comprises the following steps:
s11, inter-row expansion is carried out on the projection data acquired by the wide-row detector in the multi-row detector, the height size of the pixel after the expansion is half of the height size of the pixel before the expansion, and the expanded row data is obtained by carrying out correlation calculation according to the two rows of data of the original projection data which are closest to the expanded row data;
and S12, performing iterative inter-row data expansion on the projection data according to the row spacing and the actual pixel width until the pixel height of the expanded projection data is less than or equal to the actual pixel width.
2. The method for processing the security CT reconstructed image according to claim 1, wherein: the method for obtaining the expanded row data by performing the correlation calculation according to the row data of the original projection data comprises the following steps:
s21, obtaining edge pixel point values of the extended row data according to linear interpolation of corresponding edge pixel points of the two rows of projection data which are closest to each other;
s22, calculating the expansion row data non-edge pixel point according to six pixel points of original projection data in the eight neighborhoods of the expansion row data non-edge pixel point; the calculation method adopts an interpolation method based on the edge direction, the gradient of six pixel points passing through the direction of the pixel point to be interpolated is calculated, linear interpolation is carried out by using the pixel values of two pixel points with the minimum gradient to obtain the pixel of the point to be interpolated, and the edge information is kept while interpolation is carried out.
3. The method for processing the security CT reconstructed image according to claim 1 or 2, wherein: the method interpolates projection data, the number of lines of an image is increased along with the interpolation, the number of columns is unchanged, the size of the image is M lines xN columns, and an iterative formula for changing the direction of the image line in each iterative interpolation is as follows
Mm+1＝Mm×2-1
The superscript m is before interpolation, m +1 is after interpolation, m is 0,1,2, 0 is an original image, the number of lines after interpolation is 2 times the number of lines before interpolation minus 1, and the last line of pixels is directly assigned before interpolation;
pixel size, ymX is the size of the detector unit plus the spacing between the detector units, the pixel size after interpolation is half of the pixel size before interpolation, and the iterative formula is as follows
Figure FDA0002895977230000011
Wherein, the superscript m is before interpolation, m +1 is after interpolation, m is 0,1,2.. said, m is 0, original image,
each iterative interpolation is carried out, firstly, the ith data before interpolation is assigned to the 2i data after interpolation
Figure FDA0002895977230000012
Wherein, i is 0,1,2m1, j is 0,1,2,.. No. N-1, and then the 2i +1 th line of pixels to be interpolated is interpolated, which is divided into two cases:
1. when the column index value is j-0 and j-N-1, the corresponding pixel at the jth column of the 2 i-th row and the jth column of the 2(i +1) th row are added, and then divided by 2, and the result is assigned to the jth column of the 2i + 1-th row, the formula is as follows
Figure FDA0002895977230000021
2. When the column index value j is between 1 and N-2, the absolute value of the gradient centered at the jth column in the 2i +1 th row is calculated, as shown in FIG. 5, and the formula is as follows
Figure FDA0002895977230000022
When k is 0,1,2, the following table
Figure FDA0002895977230000023
According to the corresponding k value of the minimum gradient, kminCalculating the value of the jth pixel of the 2i +1 th row,
Figure FDA0002895977230000024
to this end MmInterpolation of projection data of size x N to Mm+1The projection data of x N size is completed and the above interpolation process is repeated until the pixel size in the row direction of the projection data, ym+1And is smaller than the length or width of the detection unit.
4. A processing device for a security check CT reconstructed image is characterized in that: the device comprises a CT data acquisition module, wherein the CT data acquisition module is sequentially connected with a wide-row CT projection data expansion module and a reconstruction module.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1669528A (en) * 2004-03-19 2005-09-21 深圳安科高技术股份有限公司 Image reconstruction method in double-line or multi-line helical CT
US20070071159A1 (en) * 2005-09-23 2007-03-29 General Electric Company Methods and apparatus for reconstructing thick image slices
CN103083031A (en) * 2011-10-31 2013-05-08 Ge医疗系统环球技术有限公司 Spiral scanning image reconstruction method and device and computer program product for computed tomography (CT) device
CN105913398A (en) * 2015-06-11 2016-08-31 沈阳东软医疗系统有限公司 Method and device for processing CT reconstructed image
CN108460740A (en) * 2018-03-06 2018-08-28 赛诺威盛科技（北京）有限公司 CT spiral reconstruction image artifacts minimizing technologies
CN110021031A (en) * 2019-03-29 2019-07-16 中广核贝谷科技有限公司 A kind of radioscopic image Enhancement Method based on image pyramid

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1669528A (en) * 2004-03-19 2005-09-21 深圳安科高技术股份有限公司 Image reconstruction method in double-line or multi-line helical CT
US20070071159A1 (en) * 2005-09-23 2007-03-29 General Electric Company Methods and apparatus for reconstructing thick image slices
CN103083031A (en) * 2011-10-31 2013-05-08 Ge医疗系统环球技术有限公司 Spiral scanning image reconstruction method and device and computer program product for computed tomography (CT) device
CN105913398A (en) * 2015-06-11 2016-08-31 沈阳东软医疗系统有限公司 Method and device for processing CT reconstructed image
CN108460740A (en) * 2018-03-06 2018-08-28 赛诺威盛科技（北京）有限公司 CT spiral reconstruction image artifacts minimizing technologies
CN110021031A (en) * 2019-03-29 2019-07-16 中广核贝谷科技有限公司 A kind of radioscopic image Enhancement Method based on image pyramid

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
ELENA FAGGIANO等: "Metal artefact reduction in computed tomography images by a fourth-order total variation flow", 《COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING: IMAGING & VISUALIZATION 》 *
关静等: "多排探测器CT的基本原理及临床应用优越性", 《西南军医》 *
吴骏峰等: "多层螺旋CT评价脊柱金属置入物产生金属伪影及其影响因素", 《中国组织工程研究与临床康复》 *
王本等: "锥束CT图像重建算法", 《CT理论与应用研究》 *

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