CN111882624A - Nano CT image motion artifact correction method and device based on multiple acquisition sequences - Google Patents

Nano CT image motion artifact correction method and device based on multiple acquisition sequences Download PDF

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CN111882624A
CN111882624A CN202010566815.1A CN202010566815A CN111882624A CN 111882624 A CN111882624 A CN 111882624A CN 202010566815 A CN202010566815 A CN 202010566815A CN 111882624 A CN111882624 A CN 111882624A
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韩玉
李磊
闫镔
席晓琦
尹召乐
朱林林
谭思宇
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Abstract

The invention belongs to the technical field of nanometer CT projection image correction, and particularly relates to a method and a device for correcting motion artifacts of a nanometer CT image based on a multi-acquisition sequence, wherein the method comprises the steps of setting the number of acquired turns of a circular track CT image and the number of projection images acquired in each turn, and acquiring the circular track CT image according to the parameters; reading a temperature change curve of a monitoring point of an objective table in a temperature detection system, and selecting a standard circular track CT projection sequence; preprocessing all the acquired projection images; calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle; performing motion artifact correction on other circular track CT projection sequences according to the obtained position deviation matrix; and performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction. The invention can effectively correct the motion artifact of the CT image and can improve the signal-to-noise ratio of the nano CT image.

Description

Nano CT image motion artifact correction method and device based on multiple acquisition sequences
Technical Field
The invention belongs to the technical field of nano CT projection image correction, and particularly relates to a nano CT image motion artifact correction method and device based on multiple acquisition sequences.
Background
A nano cone-beam CT (CBCT) system is mainly composed of an X-ray source, a flat panel detector, precision machinery and a computer, can obtain three-dimensional structural information inside an object under a non-contact and non-destructive condition, and has been widely applied to the fields of nondestructive testing, medical diagnosis, bionic materials, and the like. The imaging resolution of cone beam nano CT depends on the relative position of a sample and a detector, and projection data which can be directly subjected to three-dimensional reconstruction can be obtained only if the position change is smaller than the target resolution of the whole system theoretically.
The mechanical platform of nanoct is mostly made of aluminum, which is very sensitive to temperature variation, and when the temperature is increased from 25 ℃ to 26.6 ℃, a 100mm aluminum block is enlarged by 2.375 um. Nanoct typically has a magnification of about several tens to several hundreds, and therefore every 0.1 ℃ temperature change will result in a change of several or more than ten pixel positions of the sample projection. Temperature changes during projection image acquisition for tens of hours or even tens of hours can cause the projections to deviate from due positions, and the final three-dimensional reconstruction result is influenced. The system is integrated with a constant temperature system to reduce the influence of the environmental temperature change on the system, but because the internal space of the system is large, the temperature fluctuation range inside the system can be known to be +/-2 ℃ according to the temperature change curve of the temperature detection system. Therefore, a suitable motion artifact correction method needs to be designed to correct the acquired image.
The focal spot position of the light source used in the nanoct is not fixed, and the focal spot of the light source fluctuates by ± 100nm in the long-time projection acquisition, as shown in fig. 1. Although the low energy characteristic of the nano CT light source ensures the small focal spot size (i.e. beam concentration) of the light source, which is beneficial to increasing the number of photons in unit area and obtaining higher spatial resolution, the problems of reduced contrast, increased noise, reduced image quality and the like are also brought. To obtain high signal-to-noise ratio projections, the exposure time of the imaging can only be increased. But both the positional fluctuations of the focal spot itself and the geometric deviations of the imaging caused by temperature changes become larger with increasing exposure time. Therefore, the geometric size deviation needs to be reduced by adopting a proper nano CT image acquisition method.
Disclosure of Invention
In order to solve the problem of position deviation of a CT image caused by temperature change, mechanical jitter and focal spot drift, the invention provides a nano CT image motion artifact correction method and device based on a multi-acquisition sequence, which can effectively correct the CT image motion artifact and improve the signal-to-noise ratio of the nano CT image.
In order to solve the technical problems, the invention adopts the following technical scheme:
the invention provides a nano CT image motion artifact correction method based on multiple acquisition sequences, which comprises the following steps:
step 1, setting the number of acquired circles of a circular track CT image and the number of projected images acquired in each circle, and acquiring the circular track CT image according to the parameters;
step 2, reading a temperature change curve of a monitoring point of an objective table in a temperature detection system, and selecting a standard circular track CT projection sequence;
step 3, preprocessing all the acquired projection images;
step 4, calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
step 5, correcting the motion artifacts of other circular track CT projection sequences according to the obtained position deviation matrix;
and 6, performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
Further, before step 1, the method further comprises:
collecting a plurality of projection images with different exposure times, evaluating whether the sample to be detected is penetrated by X rays and evaluating the signal-to-noise ratio factors of the projection images, selecting proper exposure time and collecting corresponding bright field data.
Furthermore, the nano-CT continuously acquires K times of circular track circle CT images, and the number of the projection images acquired by each circular track and the exposure time are different.
Further, in step 2, the circular trajectory CT projection sequence in the corresponding period with the minimum temperature change is selected from the read temperature change curves as a standard circular trajectory CT projection sequence.
Further, all the acquired projection images are pre-processed, including:
and performing gain correction on the projection image data according to the collected bright field data, and filtering salt and pepper noise of the projection image data.
Furthermore, the acquired images of other circular track CT projection sequences and the acquired images of the standard circular track CT projection sequence are similar to only have translation change under the same angle, and the position deviation is calculated through a sub-pixel image registration algorithm based on Fourier transform to obtain a position deviation matrix.
And further, taking the round track CT projection sequence with the largest number of acquired images as a reference, and performing multi-frame accumulation on projections at the same angle to obtain a CT projection image finally used for three-dimensional reconstruction.
The invention also provides a nano CT image motion artifact correction device based on a multi-acquisition sequence, which comprises:
the circular track CT image acquisition module is used for setting the number of acquired turns of the circular track CT image and the number of projected images acquired in each turn, and acquiring the circular track CT image according to the parameters;
the standard circular track CT projection sequence selection module is used for reading a temperature change curve of a monitoring point of an objective table in the temperature detection system and selecting a standard circular track CT projection sequence;
the preprocessing module is used for preprocessing all the acquired projection images;
the position deviation calculation module is used for calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
the motion artifact correction module is used for correcting the motion artifact of other circular track CT projection sequences according to the obtained position deviation matrix;
and the three-dimensional reconstruction CT projection image enhancement module is used for performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
Compared with the prior art, the invention has the following advantages:
the method can effectively reduce the requirements on temperature control equipment and experimental environment, and obtain clear three-dimensional reconstruction results under the condition of not changing the conventional CT equipment and external environment variables. The geometric size of a sample to be detected in nano CT is generally less than 1 mm, so that the marker is very difficult to manufacture on the sample, and the marker is not required to be manufactured on the sample by adopting the method, so that the experimental difficulty is effectively reduced.
The method has the advantages that projected images of multiple circles of circular tracks are collected, sub-pixel position deviation correction is carried out, multi-frame accumulation is carried out on the projected images subjected to deviation correction at the same angle, the actual positions of the images can be quickly recovered, motion artifacts are effectively corrected, the signal-to-noise ratio of CT images is improved, the position drift of the CT images caused by temperature change and focal spot drift in long-time image collection is avoided, and the definition is reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a diagram of fluctuations in focal spot position of a light source;
FIG. 2 is a flowchart of a method for correcting motion artifacts of a nano CT image based on multiple acquisition sequences according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a kth circular trajectory acquisition in accordance with an embodiment of the present invention;
FIG. 4 is a graph of photon threshold discrimination counts for an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a motion artifact correction performed on a k-th circular trajectory CT projection sequence according to an embodiment of the present invention;
fig. 6 is a comparison graph of a reconstruction result slice (left) without bias correction and a reconstruction result slice (right) after bias correction according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
As shown in fig. 2, the method for correcting motion artifacts in nano CT images based on multiple acquisition sequences of the present embodiment includes the following steps:
step S101, collecting a plurality of projection images with different exposure times, evaluating whether a sample to be detected is penetrated by X rays or not and evaluating the signal-to-noise ratio factors of the projection images, accordingly selecting proper exposure time and collecting corresponding bright field data;
s102, setting the number of acquired turns of the circular track CT image and the number of projected images acquired in each turn, and acquiring the circular track CT image according to the parameters;
in this example, the nano-CT continuously performs K times of circular track circle CT image acquisition, and the number of projection images acquired by each circular track and the exposure time are different.
Step S103, reading a temperature change curve of a monitoring point of an objective table in a temperature detection system, and selecting a circular track CT projection sequence in a time period corresponding to the minimum temperature change as a standard circular track CT projection sequence;
step S104, preprocessing all the acquired projection images, including:
and performing gain correction on the projection image data according to the collected bright field data, and filtering salt and pepper noise of the projection image data.
Step S105, calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
in this example, the collected images of other circular trajectory CT projection sequences and the collected images of the standard circular trajectory CT projection sequence are similar to only have translational changes under the same angle, and the position deviation is calculated by a sub-pixel image registration algorithm based on fourier transform to obtain a position deviation matrix.
Step S106, correcting motion artifacts of other circular track CT projection sequences according to the obtained position deviation matrix;
and S107, taking the circular track CT projection sequence with the largest number of acquired images as a reference, and performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
The following is a specific example to better explain the present invention.
The nano CT image motion artifact correction method based on multiple acquisition sequences of the present embodiment includes the following steps:
in step S201, the penetration depth of monochromatic X-rays for different wavelengths can be expressed as:
Figure BDA0002548130330000061
in the formula I0For attenuation of X-rays from initial intensity to e-1Thickness of sample passed through, μmDenotes the material absorption coefficient, and ρ is the material density.The nano CT light source emits multi-energy X rays, and the X ray intensity I penetrating through a sample to be detected is as follows:
Figure BDA0002548130330000071
wherein I is the transmitted X-ray intensity, I0For the incident X-ray intensity, s (E) is the ray energy spectrum distribution, μ (E) is the attenuation coefficient corresponding to the material, and L is the thickness of the transmitted sample.
In practical applications, the attenuation coefficient of the sample to be detected cannot be estimated, and whether the sample is penetrated is usually estimated according to formula (3), and the voltage, the current and the exposure time of the light source can be adjusted according to the estimation result in experiments. Suppose that the exposure time is t0The contrast and signal-to-noise ratio of the sample projection are at the minimum of the acceptable range. In order to obtain three-dimensional volume data with good spatial resolution and density resolution in an experiment, the exposure time needs to be correspondingly increased, if the exposure time adopted in the experiment is t ═ t (t)1t2… tK),(tk>t0). After the exposure time is determined, J bright field projections of the corresponding time are collected.
Figure BDA0002548130330000072
In the formula PminvalIs the minimum gray value, P, in the projected imagemaxvalIs the gray value in the projected image at the initial ray intensity.
Step S2021, as shown in fig. 1, the position of the focal spot of the nano CT light source fluctuates greatly at the initial stage of the experiment, and the shielding box needs to be opened when the sample to be detected is fixed, which may affect the temperature balance in the shielding box to a certain extent, so that the first circular trajectory CT projection sequence is not used as the standard sequence. The temperature change in the shielding box is small in a relatively short time, so that the number of projection images acquired and the exposure time should be appropriately reduced when setting a CT projection sequence of a circle trajectory to be normalized.
Step S2022, set the nano CT to continuously perform K times of circle-track CT image acquisition, as shown in FIG. 3, wherein the K-th circleProjection image acquisition angle of ith of track
Figure BDA0002548130330000073
Comprises the following steps:
Figure BDA0002548130330000074
formula (III) M, NkIs a positive integer, M represents the angle number of the k-th round track acquisition, NkRepresents the number of projections, theta, at each acquisition anglem＝mθ，△θ＝θ/NkAnd theta is 360 DEG/M. Then the number of k-th trace acquisitions is M NkExposure time of a single projection is tkAnd after the experimental parameters are set, acquiring a circular track CT image.
Step S203, after the projection image data are acquired, reading a temperature change curve of a monitoring point of an objective table in the temperature detection system, and selecting a circular track CT projection sequence in a period corresponding to the minimum temperature change as a standard circular track CT projection sequence, namely, the k' th circular track CT projection sequence is the standard sequence.
Step S204, after data acquisition is completed, preprocessing all the acquired projection data, and selecting different preprocessing methods according to the type of the detector, which is described in this embodiment by taking a photon counting detector as an example.
In step S2041, each pixel unit of the photon counting detector responds to photons with a certain energy and generates a pulse signal, which can reduce the noise generated by low-energy photons by setting a proper energy threshold, as shown in fig. 4.
Step S2042, in the actual production of the photon counting detector, the performance parameters of all the detector elements cannot be completely consistent, so that even under the same X-ray irradiation, the gray values of the images obtained by the photon counting detector are different. In order to make the response of each probe element consistent and reduce the intrinsic noise in the image, all projection data are corrected by using the formula (5);
Figure BDA0002548130330000081
Figure BDA0002548130330000082
in the formula (f)0(x, y) represents the gray value of the pixel point (x, y) in the original projection image, fflat(x, y) represents the gray value of the pixel (x, y) in the bright-field projection image, R (x, y) represents the mean of the gray values of the pixel (x, y) in the bright-field projection image, R0Is the median of R (x, y), and f (x, y) represents the gray value of the pixel point (x, y) in the corrected projected image.
Step S2043, the dead pixel correction and median filtering are performed on the corrected projection image.
And step S205, calculating the position deviation of the k-th projection image of the circular track CT projection sequence and the k' -th projection image of the standard circular track CT projection sequence by adopting a sub-pixel image registration algorithm. At a standard acquisition sequence acquisition angle of
Figure BDA0002548130330000091
Is fi(x, y), the projection image of the kth circular trajectory acquisition sequence at the same angle is fi k(x, y), then:
Figure BDA0002548130330000092
fourier transform of equation (7) yields:
Figure BDA0002548130330000093
calculating a normalized cross-power spectrum:
Figure BDA0002548130330000094
in the formula Fi *(u, v) is Fi(u, v) complex conjugation. Inverse transformation of the cross-power spectrum yields the pulse function:
Figure BDA0002548130330000095
thereby obtaining the position deviation
Figure BDA0002548130330000096
By analogy, the position deviation matrixes under all the acquisition angles can be obtained.
Step S206, performing motion artifact correction on the CT projection sequence of other circular tracks by using the position deviation matrix obtained in step S205, as shown in fig. 5, using the principle of proximity to the k-th circular track circle at θmAnd thetam+1The projection image acquired at the acquisition angle therebetween uses θmPositional deviation of angle
Figure BDA0002548130330000097
Motion artifact correction is performed.
Step S207, when performing three-dimensional reconstruction using the projection images, generally selecting a circular trajectory CT projection sequence with the largest number of acquired projection images, that is, selecting a circular trajectory CT projection sequence with the largest M. In order to fully utilize other projection data, a multi-frame noise reduction mode can be used for eliminating random noise and improving the signal to noise ratio of a projection image to be reconstructed. Assuming that there are L projection images at a certain acquisition angle, the L-th projection image can be represented as:
f(x,y)＝gl(x,y)+nl(x,y) (11)
in the formula gl(x, y) is a noise-free projection image, g at the same anglel(x, y) are equal, nl(x, y) is gaussian noise, and after the superposition averaging, can be expressed as:
Figure BDA0002548130330000101
and after multi-frame noise reduction is completed, reading the projection image and performing three-dimensional reconstruction to obtain the volume data of the sample to be detected.
The effectiveness of the method is verified by specific experiments, and the relevant parameters are shown in table 1.
TABLE 1 relevant parameters of the experiment
Figure BDA0002548130330000102
The slice of the sample reconstruction result of the 3 rd projection without bias correction is shown in the left image of fig. 6, and obvious geometric artifacts can be seen, and detailed information is blurred. The slice of the sample reconstruction result after the 3 rd circle of CT image is corrected by the motion artifact is shown in the right picture of figure 6, no geometric artifact exists, and the details of the sample are clear and distinguishable. The nano CT image motion artifact correction method based on the multiple acquisition sequences can effectively correct the CT image motion artifact and improve the signal-to-noise ratio of the nano CT image.
The embodiment also provides a nano CT image motion artifact correction device based on multiple acquisition sequences, which comprises a circular track CT image acquisition module, a standard circular track CT projection sequence selection module, a preprocessing module, a position deviation calculation module, a motion artifact correction module and a three-dimensional reconstruction CT projection image enhancement module.
The circular track CT image acquisition module is used for setting the number of acquired turns of the circular track CT image and the number of projected images acquired in each turn, and acquiring the circular track CT image according to the parameters;
the standard circular track CT projection sequence selection module is used for reading a temperature change curve of a monitoring point of an objective table in the temperature detection system and selecting a standard circular track CT projection sequence;
the preprocessing module is used for preprocessing all the acquired projection images;
the position deviation calculation module is used for calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
the motion artifact correction module is used for correcting the motion artifact of other circular track CT projection sequences according to the obtained position deviation matrix;
and the three-dimensional reconstruction CT projection image enhancement module is used for performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it is to be noted that: the above description is only a preferred embodiment of the present invention, and is only used to illustrate the technical solutions of the present invention, and not to limit the protection scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims (8)

1. A nano CT image motion artifact correction method based on a multi-acquisition sequence is characterized by comprising the following steps:
step 1, setting the number of acquired circles of a circular track CT image and the number of projected images acquired in each circle, and acquiring the circular track CT image according to the parameters;
step 2, reading a temperature change curve of a monitoring point of an objective table in a temperature detection system, and selecting a standard circular track CT projection sequence;
step 3, preprocessing all the acquired projection images;
step 4, calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
step 5, correcting the motion artifacts of other circular track CT projection sequences according to the obtained position deviation matrix;
and 6, performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
2. The nanoct image motion artifact correction method based on multiple acquisition sequences as claimed in claim 1, further comprising, before step 1:
collecting a plurality of projection images with different exposure times, evaluating whether the sample to be detected is penetrated by X rays and evaluating the signal-to-noise ratio factors of the projection images, selecting proper exposure time and collecting corresponding bright field data.
3. The method of claim 2, wherein the nanoct continuously performs K times of circular trajectory CT image acquisition, and the number of projection images and the exposure time of each circular trajectory acquisition are different from each other.
4. The method of claim 1, wherein the circle trajectory CT projection sequence in the corresponding time period with the minimum temperature variation is selected as the standard circle trajectory CT projection sequence in the read temperature variation curve in step 2.
5. The method of claim 2, wherein the preprocessing of all the acquired projection images comprises:
and performing gain correction on the projection image data according to the collected bright field data, and filtering salt and pepper noise of the projection image data.
6. The method for correcting the motion artifacts of the nano CT images based on multiple acquisition sequences as claimed in claim 1, wherein the acquired images of other circular CT projection sequences and the acquired images of the standard circular CT projection sequences are similar to only have translation changes under the same angle, and the position deviation is calculated by a Fourier transform-based sub-pixel image registration algorithm to obtain a position deviation matrix.
7. The method of claim 1, wherein the projections at the same angle are accumulated in multiple frames based on a circular trajectory CT projection sequence with the largest number of acquired images, so as to obtain a CT projection image for three-dimensional reconstruction.
8. A nano CT image motion artifact correction device based on a multi-acquisition sequence is characterized by comprising:
the circular track CT image acquisition module is used for setting the number of acquired turns of the circular track CT image and the number of projected images acquired in each turn, and acquiring the circular track CT image according to the parameters;
the standard circular track CT projection sequence selection module is used for reading a temperature change curve of a monitoring point of an objective table in the temperature detection system and selecting a standard circular track CT projection sequence;
the preprocessing module is used for preprocessing all the acquired projection images;
the position deviation calculation module is used for calculating a position deviation matrix of other circular track CT projection sequences and a standard circular track CT projection sequence under the same angle;
the motion artifact correction module is used for correcting the motion artifact of other circular track CT projection sequences according to the obtained position deviation matrix;
and the three-dimensional reconstruction CT projection image enhancement module is used for performing multi-frame accumulation on the CT images subjected to deviation correction at corresponding angles to obtain the CT projection images finally used for three-dimensional reconstruction.
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