CN108460740B - CT spiral reconstruction image artifact removing method - Google Patents
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Abstract
The invention provides a CT spiral reconstruction image artifact removing method, which comprises the following steps: projection data collected by thin detector units in the multi-row detectors are not processed; and expanding the projection data acquired by the thick detector units in the multi-row detectors. The specific method comprises the following steps: expanding the projection data collected by each row of thick detector units into N rows of data; wherein N is: dividing the thickness of the thick row of detector units by the thickness of the thin row of detector units; the projection data acquired by the thick-row detector units are expanded into N rows of data, each row of data is associated with the projection data acquired by the two closest rows of original detector units, the weight ratio of the closest data in the projection data acquired by the two rows of original detector units is large, the weight ratio of the next closest data is small, and the weight sum is 1. The invention has the advantages that: the processing speed is high, windmill artifacts in the image can be effectively removed, and meanwhile, the noise level of the image is not obviously changed.
Description
Technical Field
The invention relates to a CT spiral reconstruction image artifact removing method.
Background
In the third generation ct (computed tomography) machine, a detector with a multi-row structure is generally used to perform helical trajectory scanning, acquire projection data of a patient, and then reconstruct a tomographic image of the patient. In the data acquisition process, a light source (namely a bulb tube) and a detector of the CT machine synchronously rotate around a CT bed plate, and meanwhile, the light source emits X rays, and only the rays in a required range pass through a collimator to scan a patient through the constraint of the collimator and reach a receiving area of the detector.
In an actual clinical scan, as shown in fig. 1A, when a small opening collimator is used, only the middle rows of detector elements of the detector can receive X-ray signals. When a large-opening collimator is used, all rows of detector cells of the detector can receive the X-ray signals, as shown in fig. 1B.
Currently, the third generation CT machines generally employ multiple rows of detectors, such as 16 rows, 24 rows, 32 rows, 64 rows, 128 rows, etc. Generally, the third generation CT machines employ multiple rows of detector elements having a uniform thickness, but there are also multiple rows of detectors in the third generation CT machines with a different thickness between the middle row and the two side rows of detector elements, such as the 24 rows of detectors shown in FIG. 2. The 24 rows of detectors shown in fig. 2, each cell of which represents a physical detector unit, are arranged in sequence in the transverse direction to form different channels of the detector and in the longitudinal direction to form different rows of detectors, for a total of 24 rows. The dark grey sections (16 in the middle) and the light grey sections (4 in each of the upper and lower rows) are each the same width in the direction of the channel arrangement, but the thickness of the detector units in the longitudinal row direction is different. The unit thickness of the detector elements in the middle row (dark grey segment) is the same, and the thickness of the detector elements in the two side rows (light grey segment) is 2 times the thickness of the detector elements in the middle row (dark grey segment).
For the collimator with a small opening as shown in fig. 1A, since the X-rays emitted from the light source pass through the patient under the constraint of the collimator with a small opening, and are only received by the detector units with the same thickness in the middle of the multiple rows of detectors, the reconstructed tomographic image of the patient is relatively clear after the multiple rows of detectors acquire the projection data of the patient. However, for the large-opening collimator shown in fig. 1B, the X-rays emitted from the light source pass through the patient under the constraint of the large-opening collimator, and are received by all rows of detector units of the multi-row detector, and since the thickness of the detector units on both sides of the multi-row detector is 2 times that of the detector unit in the middle row, in the image reconstruction under the large-opening collimator shown in fig. 1B, the minimum layer thickness of the image reconstructed by the system is 2 times that of the reconstructed image layer under the small-opening collimator shown in fig. 1A according to the conventional method; meanwhile, in the data acquisition process, the data acquired by the middle thin-layer detector unit are combined, so that each two adjacent thin-layer detector units generate one layer of thick-layer data. In this case, the axial data acquisition rate of the system is reduced, resulting in severe windmill artifacts in the reconstructed image at locations of varying distances of tissue, as indicated by the white arrows in fig. 3.
Disclosure of Invention
In view of the above, the present invention provides a method for removing artifacts in CT helical reconstruction images. The method can effectively remove the artifacts generated when the middle row and the two side rows of detectors with different thicknesses are used for acquiring data and reconstructing the image.
In order to achieve the purpose, the invention adopts the following technical scheme: a CT spiral reconstruction image artifact removing method comprises the following steps: projection data collected by thin detector units in the multi-row detectors are not processed; and expanding the projection data acquired by the thick detector units in the multi-row detectors.
Preferably, the projection data collected by each row of thick detector units is expanded into N rows of data; wherein N is: dividing the thickness of the thick row of detector units by the thickness of the thin row of detector units; the projection data acquired by the thick-row detector units are expanded into N rows of data, each row of data is associated with the projection data acquired by the two closest rows of original detector units, the weight ratio of the closest data in the projection data acquired by the two rows of original detector units is large, the weight ratio of the next closest data is small, and the weight sum is 1.
Preferably, said N is 2.
Drawings
FIG. 1A is a schematic diagram of the optical path of a lower bulb detector of a small-opening collimator;
FIG. 1B is a schematic diagram of the optical path of a lower bulb detector of a large-opening collimator;
FIG. 2 is a schematic diagram of a 24 row detector configuration with different thickness in the middle row and the two side rows;
FIG. 3 is a CT tomographic image with windmill artifacts;
FIG. 4 is a schematic diagram of the present invention for removing image artifacts;
fig. 5 is an image after removing artifacts using the present invention.
Detailed Description
The structure and features of the present invention will be described in detail below with reference to the accompanying drawings and examples. It should be noted that various modifications can be made to the embodiments disclosed herein, and therefore, the embodiments disclosed in the specification should not be construed as limiting the present invention, but merely as exemplifications of embodiments thereof, which are intended to make the features of the present invention obvious.
The inventor of the invention finds out that the artifact is caused when the middle row and the two side rows of detectors with different thicknesses are used for acquiring data and reconstructing the image: when reconstructing data scan images under a large-aperture collimator, in order to ensure that the thickness of each row of the acquired projection data is consistent, it is common practice to merge intermediate thin-layer data, which may cause a decrease in the axial sampling rate, thereby generating significant windmill artifacts in the filtered back-projection reconstructed images.
In order to remove the artifacts in the image, the method for removing the artifacts provided by the invention comprises the following steps:
s1, projection data collected by thin detector units in the multi-row detectors are not processed;
s2, expanding projection data acquired by thick detector units in the multi-row detectors, wherein the expansion aims to increase the axial data sampling rate;
the specific method comprises the following steps:
s21, expanding the projection data collected by each row of thick detector units into N rows of data; wherein N is: dividing the thickness of the thick row of detector units by the thickness of the thin row of detector units;
that is, if the thickness of the thick detector unit of the multi-row detector is 2 times the thickness of the thin detector unit (i.e., N is 2), for example, the thickness of the 1 st row to 4 th row and the 21 st row to 24 th row (light gray portion) of the 24-row multi-row detector is 2 times the thickness of the 5 th row to 20 th row (dark gray portion) of the middle row; then, projection data acquired by the middle 5 th row-20 th row (16 rows in total) thin row detector units are not processed; the projection data collected by the 1 st row-4 th row and the 21 st row-24 th row thick row detector units on two sides are expanded, the projection data collected by the 1 st row-4 th row detector units are expanded into 2 times of the original projection data and 8 rows of projection data, and similarly, the projection data collected by the 21 st row-24 th row detector units are also expanded into 2 times of the original projection data and 8 rows of projection data. Thus, the original 8 rows of detector projection data are expanded into 16 rows of detector projection data which are 2 times of the original projection data, the original 24 rows of projection data are expanded into 8+16+8 which is 32 rows of projection data, and the 32 rows of projection data obtained after expansion are reconstructed into the CT tomographic image of the patient according to the conventional method.
S22, expanding the projection data acquired by the thick-row detector units into N rows (N is 2) of data, wherein each row of data is associated with the projection data acquired by the two closest rows of original detector units, the weight ratio of the closest data in the projection data acquired by the two rows of original detector units is large, the weight ratio of the next closest data in the projection data acquired by the two rows of original detector units is small, and the weight sum is 1, namely:
B4+l＝D l4＜l＜21
wherein,
w1+w 21, and w1＞w2
DlData representing the original l-th row of detector units;
B2l-1、B2land representing the data of the detector units after the expansion of the first row of detector units.
The following describes how to expand data collected by thick row detector units in a multi-row detector in detail with reference to the drawings. The first row in FIG. 4 represents the raw data acquired by the 24 detector rows, denoted D1、D2、D3、D4、D5、D6、……、D19、D20、D21、D22、D23、D24Row 1, row 2, row 3, row 4, row 5, row 6, row … …, row 19, row 20, row 21, row 22, row 23, row 24 data representing a 24 row detector acquisition.
Since the thickness of the thick detector units (1 st row-4 th row and 21 st row-24 th row) on both sides of the 24-row detector is 2 times that of the middle thin detector unit (5 th row-20 th row), as shown in the second row in FIG. 4, the data of the 5 th row-20 th row of the middle thin detector unit is not processed, and the data of the 1 st row-4 th row and 21 st row-24 th row of the thick detector units on both sides are expanded by 1 time and B is used1、B2、B3、B4、B5、B6、B7、B8、B9、B10、B11、B12、……、B21、B22、B23、B24、B25、B26、B27、B28、B29、B30、B31、B32Representing expanded lines 1-32And (6) arranging data.
Specifically, the original 1 st row data D is divided into1Extended to B1、B2(ii) a Original 2 nd row data D2Extended to B3、B4(ii) a Original 3 rd row data D3Extended to B5、B6(ii) a Original 4 th row data D4Extended to B7、B8(ii) a The original row 5-row 20 data are not processed, D5＝B9、D6＝B10、D7＝B11、……、D19＝B23、D20＝B24(ii) a Original 21 st row data D21Extended to B25、B26(ii) a Original 22 nd row data D22Extended to B27、B28(ii) a Original 23 rd row data D23Extended to B29、B30(ii) a Original 24 th row data D24Extended to B31、B32。
According to the formula:
B4+l＝D l4＜l＜21
in a specific embodiment of the invention, W1＝0.75，W20.25, although other values may be used, provided that w is equal to1+w 21, and w1＞w2And (4) finishing.
As shown in FIG. 4, the present invention provides D1Extended to B1And B2，B1＝D1，B2＝0.75D1+0.25D2(ii) a Will D2Extended to B3And B4，B3＝0.75D2+0.25D1，B4＝0.75D2+0.25D3；
Will D3Extended to B5And B6，B5＝0.75D3+0.25D2，B6＝0.75D3+0.25D4；
Will D4Extended to B7And B8，B7＝0.75D4+0.25D3，B8＝0.75D4+0.25D5；
B9＝D5；B10＝D6；B11＝D7；……；B22＝D18；B23＝D19；B24＝D20；
Will D21Extended to B25And B26，B25＝0.75D21+0.25D20，B26＝0.75D21+0.25D22；
Will D22Extended to B27And B28，B27＝0.75D22+0.25D21，B28＝0.75D22+0.25D23；
Will D23Extended to B29And B30，B29＝0.75D23+0.25D22，B30＝0.75D23+0.25D24；
Will D24Extended to B31And B32，B31＝0.75D24+0.25D23，B32＝D24。
For 16 rows, 32 rows, 64 rows and 128 rows of detectors with different thicknesses in the middle row and the two rows, artifacts in the reconstructed image can be removed according to the method provided by the invention, namely: projection data acquired by the thin detector units are not processed; and expanding the projection data acquired by the thick detector units. Because the thickness of the thick detector unit of the 16-row, 32-row, 64-row and 128-row detectors used in the market is 2 times of the thickness of the thin detector unit, the data collected by each row of thick detector units is usually expanded into 2 rows of data, and the thickness of each row of expanded data is the same as the thickness of the data collected by the thin detector units.
The invention does not need to modify the structure of the existing CT machine, does not need to change the CT reconstruction algorithm, and only needs to expand the acquired data.
The invention has the advantages that:
1. as shown in fig. 5, the windmill artifact in the image can be effectively removed, and the noise level of the image does not change significantly.
2. The method provided by the invention only processes the projection domain data and does not need to process the image domain data, so the processing speed is high, the reconstruction speed of the image is not influenced, and the method is suitable for the reconstruction of the scanning data and the image of all different parts.
3. A simple linear interpolation method is adopted in the process of expanding the projection domain data, so that the robustness of the algorithm is ensured, and the resolution ratio of the reconstructed image is basically not lost.
It should be noted that the present invention is applicable to all non-uniform thickness detector configurations, and is not limited to 24 rows (16 middle thin layers and 4 thick layers on either side) of detectors.
Finally, it should be noted that: the above-mentioned embodiments are only used for illustrating the technical solution of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (2)
1. A CT spiral reconstruction image artifact removing method is characterized in that: the artifact removing method comprises the following steps: projection data collected by thin detector units in the multi-row detectors are not processed;
expanding projection data acquired by thick detector units in a multi-row detector, namely:
s21, expanding the projection data collected by each row of thick detector units into N rows of data; wherein N is: dividing the thickness of the thick row of detector units by the thickness of the thin row of detector units;
s22, expanding the projection data collected by the thick-row detector units into N rows of data, wherein each row of data is associated with the projection data collected by the two closest rows of original detector units, the weight ratio of the closest data in the projection data collected by the two rows of original detector units is large, the weight ratio of the next closest data is small, and the weight sum is 1.
2. The CT helical reconstruction image artifact removal method of claim 1, wherein: and the N is 2.
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