CN111462266B - Image reconstruction method, device, CT equipment and CT system - Google Patents
Image reconstruction method, device, CT equipment and CT system Download PDFInfo
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
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Abstract
The embodiment of the invention provides an image reconstruction method, an image reconstruction device, CT equipment and a CT system. According to the embodiment of the invention, the two-dimensional projection data obtained by cone beam CT scanning of the target tissue of the subject is obtained, the two-dimensional projection data is subjected to filtering processing by utilizing a preset standard filtering function, so that first data is obtained, the first data is subjected to smooth filtering, second data is obtained, the data of a preset frequency band in the second data are enhanced by adopting a first parameter, the data of other frequency bands except the preset frequency band in the second data are enhanced by adopting a second parameter, so that third data is obtained, the value of the first parameter is smaller than the value of the second parameter, the preset frequency band is the frequency band corresponding to the target tissue, three-dimensional image reconstruction is carried out based on the third data, a reconstructed image is obtained, and the image quality of the three-dimensional reconstructed image is improved.
Description
Technical Field
The present invention relates to the field of medical image processing technologies, and in particular, to an image reconstruction method, an image reconstruction device, a CT apparatus, and a CT system.
Background
Electronic computed tomography (Computed Tomography, CT) imaging is a safe, accurate, noninvasive imaging technique. Currently, CT scans include normal CT scans and CBCT (Cone Beam Computed Tomography, cone beam CT) scans.
Whether normal CT or CBCT, filtering is a critical step in some three-dimensional reconstruction algorithms. In the related art, standard filter functions such as hamming, ram-Lak, shepp-Logan and the like are used for filtering. In the three-dimensional reconstructed image obtained by the technology, the problem of blurred and unclear edges exists in the imaging of the tissue of interest, and the image quality is poor.
Disclosure of Invention
In order to overcome the problems in the related art, the invention provides an image reconstruction method, an image reconstruction device, a CT device and a CT system, and the image quality is improved.
According to a first aspect of an embodiment of the present invention, there is provided an image reconstruction method including:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
Enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
According to a second aspect of an embodiment of the present invention, there is provided an image reconstruction apparatus including:
the acquisition module is used for acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and carrying out filtering processing on the two-dimensional projection data by utilizing a preset standard filtering function to obtain first data;
the smoothing module is used for carrying out smoothing filtering on the first data to obtain second data;
the enhancement module is used for enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
And the reconstruction module is used for reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
According to a third aspect of embodiments of the present invention, there is provided a CT apparatus comprising: an internal bus, and a memory, a processor and an external interface connected through the internal bus; the external interface is used for being connected with a detector of the CT system, and the detector comprises a plurality of detector chambers and corresponding processing circuits;
the memory is used for storing machine-readable instructions corresponding to control logic of image reconstruction;
the processor is configured to read the machine-readable instructions on the memory and perform operations comprising:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
And reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
According to a fourth aspect of embodiments of the present invention, there is provided a CT system comprising a detector, a scan bed and a CT apparatus, the detector comprising a plurality of detector cells and corresponding processing circuitry; wherein:
the detector chamber is used for detecting X-rays passing through a scanning object and converting the X-rays into electric signals in the scanning process of the CT system;
the processing circuit is used for converting the electric signal into a pulse signal and collecting energy information of the pulse signal;
the CT device is used for:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
And reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
according to the embodiment of the invention, the two-dimensional projection data obtained by cone beam CT scanning of the target tissue of the subject is obtained, the two-dimensional projection data is subjected to filtering processing by utilizing a preset standard filtering function to obtain the first data, the first data is subjected to smooth filtering to obtain the second data, the data of the preset frequency band in the second data are enhanced by adopting the first parameter, the data of other frequency bands except the preset frequency band in the second data are enhanced by adopting the second parameter to obtain the third data, the value of the first parameter is smaller than the value of the second parameter, the preset frequency band is the frequency band corresponding to the target tissue, the three-dimensional image reconstruction is carried out based on the third data to obtain the reconstructed image, the artifacts around the target tissue in the three-dimensional reconstructed image can be reduced, the edges of the target tissue can be clearer, and more details can be more clearly displayed, so that the image quality of the three-dimensional reconstructed image is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the specification and together with the description, serve to explain the principles of the specification.
Fig. 1 is a flowchart illustrating an image reconstruction method according to an embodiment of the present invention.
Fig. 2 is an exemplary view of two-dimensional projection data of a certain angle obtained by cone beam CT scanning.
Fig. 3 is an exemplary graph of a high frequency filter function curve.
Fig. 4 is a graph showing the comparison of the high frequency enhancement filter function curves of equation (7) and equation (9).
Fig. 5 is a schematic diagram showing a comparison of a basic filter function curve and a filter function curve modified by adding a high-frequency enhancement filter function on the basis of the basic filter function.
Fig. 6 is a tomographic image obtained by three-dimensionally reconstructing a blood vessel using basic filter function filtering.
Fig. 7 is a tomographic image obtained by three-dimensionally reconstructing a blood vessel using a filter function modified by adding a high-frequency enhancement filter function on the basis of a basic filter function.
Fig. 8 is a three-dimensional blood vessel image obtained by three-dimensional reconstruction using a basic filter function.
Fig. 9 is a three-dimensional blood vessel image obtained by three-dimensional reconstruction with the addition of a high-frequency enhancement filter function based on a basic filter function.
Fig. 10 is an enlarged image of the three-dimensional blood vessel image in fig. 8.
Fig. 11 is an enlarged image of the three-dimensional blood vessel image in fig. 9.
Fig. 12 is a functional block diagram of an image reconstruction device according to an embodiment of the present invention.
Fig. 13 is a hardware configuration diagram of a CT apparatus according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of embodiments of the invention as detailed in the accompanying claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments of the invention only and is not intended to be limiting of embodiments of the invention. As used in this application 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 or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used in embodiments of the present invention to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information, without departing from the scope of embodiments of the present invention. The term "if" as used herein may be interpreted as "at..once" or "when..once" or "in response to a determination", depending on the context.
Both the data of the common CT scan and the data of the CBCT scan can be used for reconstructing three-dimensional images. These three-dimensional reconstructed images are used to assist doctors in diagnosis and treatment, and the quality of the images has an important influence on the observation and judgment of the doctors, so that reconstructing high-quality three-dimensional images has an important meaning.
Currently, CBCT imaging techniques are widely used in medical diagnosis and treatment procedures.
Taking the field of vascular intervention as an example, CBCT imaging of neurovascular has important clinical implications for diagnosis and treatment. Because the common two-dimensional X-ray imaging is overlapped in the depth direction of the object, the relative relation among blood vessels, blood vessels and tissues is not easy to display, the three-dimensional blood vessel image generated by CBCT can comprehensively display the relative position relation among different blood vessels and tissue structures, and doctors can also rotate the image according to the interested lesion position and observe according to any angle to find the optimal treatment position. Therefore, the quality of the three-dimensional blood vessel image directly influences diagnosis and treatment of doctors, and if the blood vessel is blurred and the edge is displayed unclearly, the three-dimensional blood vessel image is not beneficial to observation, and the measurement accuracy can be influenced.
Currently, in common CT and CBCT, three-dimensional reconstruction mostly adopts FDK algorithm, and one key step in the algorithm is filtering. The filtering in the algorithm uses basic filters, such as hamming filters, ram-Lak filters, shepp-Logan filters, etc. When the filters are directly used, the main blood vessel of the blood vessel bundle obtained according to the reconstruction algorithm is visible, but the problems that the edge of the blood vessel is not clear and smooth enough, the periphery of the blood vessel is provided with burr artifacts, and the display of tiny branches is fuzzy exist, and the problems influence the judgment and measurement of the conditions of vascular malformation, stenosis and the like by doctors.
The image reconstruction method provided by the embodiment of the invention can be applied to a three-dimensional image reconstruction scene of the data obtained by CBCT scanning. The image reconstruction method provided by the embodiment of the invention can be applied to three-dimensional image reconstruction of blood vessels, such as cerebral blood vessels, and can also be applied to three-dimensional image reconstruction of other tissues, such as bones, tissues and the like.
The image reconstruction method is described in detail by way of examples.
Fig. 1 is a flowchart illustrating an image reconstruction method according to an embodiment of the present invention. As shown in fig. 1, in this embodiment, the image reconstruction method may include:
S101, acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data.
S102, smoothing filtering is carried out on the first data to obtain second data.
And S103, enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization.
And S104, reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
Prior to reconstruction, a cone beam CT scan is performed on the target tissue to obtain two-dimensional projection data (which may also be referred to as a two-dimensional projection sequence). For example, a three-dimensional brain angiography of the head of a patient may be performed to obtain a two-dimensional projection sequence of the brain blood vessel. Fig. 2 is an exemplary view of two-dimensional projection data of a certain angle obtained by cone beam CT scanning.
In this embodiment, the target tissue may be a vascular tissue such as a cerebral blood vessel, an abdominal blood vessel, a cervical blood vessel, or the like. The target tissue may also be bone, soft tissue, or other tissue.
In this embodiment, the reconstruction algorithm used may be an FDK algorithm.
In an exemplary implementation process, filtering the two-dimensional projection data with a preset standard filtering function may further include, before obtaining the first data:
preprocessing the two-dimensional projection data to obtain preprocessed data;
and filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, wherein the filtering comprises the following steps: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
For preprocessing the two-dimensional projection data, refer to the related art, and will not be described herein.
In this embodiment, the standard filter function may be a Shepp-Logan function. The time domain expression of the Shepp-Logan function is equation (1).
In one exemplary implementation, the method of equation (1)N is the detector widthThe number of pixels, due to the symmetry of the function, +.>When the time domain expression of the Shepp-Logan function is formula (2).
Although the standard filter function can eliminate a part of artifacts, more artifacts still exist around the edge of the target tissue, the edge of the target tissue is blurred, not smooth enough, and there are spike artifacts. Therefore, in this embodiment, after the first data is obtained through the filtering process of the standard filter function, the smoothing filter process is further performed on the first data.
Taking three-dimensional imaging of cerebral vessels as an example, it is described how smoothing filtering is performed during reconstruction.
Assuming that a two-dimensional projection data set obtained by cerebral vascular scanning is A, filtering data in the set A by a standard filter function (such as a Shepp-Logan function) to obtain a set X1, and processing the data X in the set X1 by adopting the following formula (3):
smooths (x) is a frequency domain smoothing filter function.
In formula (3), x ε (0, N-1), c and n are adjustable parameters. In an exemplary implementation, c=1, n=2, where the smoothing effect on the cerebral vessels is better.
The three-dimensional blood vessel image mainly shows the blood vessel shape, and the blood vessel edge is required to be smooth and burr-free. The embodiment multiplies the smooth filter function on the basis of the Shepp-Logan function, so that blood vessels can be smoothed, and noise can be reduced.
After the processing in step S102, the smoothness of the image may achieve a satisfactory effect, however, when the voxel size of the reconstruction matrix is larger than the pixel size of the detector, the resolution of the reconstruction is lower than the original image of the detector, and the reconstructed image cannot fully represent the high-frequency information, high-frequency aliasing artifact may occur, and noise may increase.
In order to solve the problem of high frequency aliasing artifact, the present embodiment may perform cut-off filtering on the smoothed filtered data after step S102 and before step S103, where the purpose of the cut-off filtering is to cut off the high frequency signal in the signal.
In an exemplary implementation process, after step S102 and before step S103, the method may further include:
acquiring the voxel size of a reconstruction matrix corresponding to the image reconstruction and the pixel size of a detector used for cone beam CT scanning of the target tissue;
judging whether the voxel size is larger than the pixel size;
if yes, setting the data with the corresponding frequency higher than the preset frequency in the second data to be 0, and obtaining fourth data;
at this time, step S103 may include: and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
In this embodiment, the preset frequency may be determined according to the pixel size of the detector and the voxel size of the reconstruction matrix.
For example. Assuming that the data in the set X1 is processed by the above formula (3) to obtain the set X2, the following formulas (4) and (5) may be used to process the data X in the set X2.
Definition m=n×size projectedpixel /size voxel Wherein the size is projectedpixel Is the pixel size of the detector voxel Is the voxel size of the reconstruction matrix, N is the detector width pixel count.
When the data X epsilon (0, M-1) in the set X2, the frequency domain cut-off filter function is as formula (4):
for data x outside the data interval (0, m-1), the frequency domain cut-off filter function is formula (5):
Cutoff(x)＝0 (5)
the Shepp-Logan formula is a time domain filter function formula, which requires FFT (fast fourier transform) to be transformed into the frequency domain, then multiplied by other filter functions, and finally subjected to inverse fast fourier transform, and the result is recorded as a basic filter function F. Thus, in this embodiment, the basic filter function F required for three-dimensional reconstruction may be equation (6):
F＝IFFT(FFT(h)*Smooth*Cutoff) (6)
it should be noted that if the voxel size of the reconstruction matrix is smaller than or equal to the pixel size of the detector, the cut-off filtering may not be performed, i.e., the high-frequency enhancement filtering is directly performed in step S103 after the smoothing filtering.
After the processing of the basic filter function, the noise of the image is suppressed and the blood vessel is smoothed. However, the edges of the blood vessels remain blurred and not clear enough. Therefore, the present embodiment employs step S103 to improve the contrast of the blood vessel and the sharpness of the edge of the blood vessel so as to enhance the display of the blood vessel in the tomographic image.
In this embodiment, the preset frequency band may be set according to application requirements. For example, in three-dimensional image reconstruction of cerebral blood vessels, the preset frequency band may be a frequency range corresponding to a blood vessel pixel point.
In this embodiment, by enhancing data in different frequency bands by using different parameters, the contrast between the target tissue and the background area outside the target tissue can be improved, and the sharpness of the edge of the target tissue can be improved, so that the display of the target tissue in the tomographic image can be enhanced.
Step S103 will be described with respect to three-dimensional image reconstruction of a cerebral blood vessel as an example.
The data X in the set X2 is processed by the above formula (4) and formula (5) to obtain a set X3, and the data X in the set X3 may be processed by using the following high-frequency enhancement filter function filter 1.
Definition of the definitionWhere boost1 scale is an enhancement factor, in one example, the value of boost1 scale is 2.N is the number of pixels of the detector width. When->I.e.When, the high frequency enhancement filter function filter1 is as shown in formula (7):
filter1(x)＝1+boost1*(1-coS(arg1) power1 ) (7)
for intervals ofThe outer data x, the high frequency enhancement filter function filter1 is shown in equation (8):
filter1(x)＝1+boost1 (8)
in the formula (7) and the formula (8), power1 and boost1 are enhancement parameters. In different applications, the values of the parameters power1 and boost1 can be flexibly adjusted according to target tissues in the applications, so that the degree of high-frequency filtering is adjusted to achieve the desired filtering effect.
In one example, power1=128 and boost 1=1 may be taken, where the curve of the high frequency filtering function in the frequency domain is shown in fig. 3. Fig. 3 is an exemplary graph of a high frequency filter function curve. The filters are symmetrical, half of which is shown in fig. 3.
After the high-frequency enhancement filter function is used for filtering, the peripheral artifact of the blood vessel part is less, the edge of the blood vessel is clearer and sharper, the contrast is stronger, the three-dimensional blood vessel image effect is better, more blood vessels can be displayed, the branches of the tiny blood vessels are clear to display, the edge of the blood vessel is smooth and sharper, and the wall of the blood vessel is continuous and complete, thereby being beneficial to diagnosis and treatment of doctors.
In order to achieve the desired sharpness of the edge of the target tissue, the high-frequency enhancement filtering may be performed once or twice or more.
Thus, in one exemplary implementation, step S103 may include:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
The high-frequency enhancement filtering twice or more may be implemented by performing the filtering process using a plurality of high-frequency enhancement filter functions in succession. Each high frequency enhancement filter function corresponds to a high frequency enhancement filter, and the plurality of high frequency enhancement filter functions corresponds to a high frequency enhancement filter bank.
In an exemplary implementation process, after step S103 and before step S104, the method may further include:
filtering the third data by using an exponential type filtering function to obtain fifth data, wherein a first function value corresponding to the exponential type filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in other frequency bands in the third data;
at this time, step S104 includes: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
For example, assuming that the data in the set X3 is processed by the above-described formulas (7) and (8) to obtain the set X4, the data X in the set X4 may be processed by the following exponential filter function (the functions represented by the formulas (9) and (10)).
Definition of the definitionWhen->I.e. < ->When the exponential filter function adopts the expression of formula (9):
otherwise, when x does not belong to the intervalWhen the exponential filter function adopts the expression of formula (10):
filter(x)＝filter1(x)+boost2 (10)
wherein filter1 (x) is the aforementioned high frequency enhancement filter function.
In the formula (9) and the formula (10), boost2 and power2 are enhancement parameters. In one example, boost 2=1 and power2=15, where there is a better enhancement to the vessel edge.
The exponential filter function is also a high frequency enhancement filter function. The high-frequency enhancement filter function of the above formula (7) and the high-frequency enhancement filter function of the above formula (9) may be used separately or may be used in combination and adjusted. Fig. 4 is a graph showing the comparison of the high frequency enhancement filter function curves of equation (7) and equation (9). In fig. 4, the upper curve is the high-frequency enhancement filter function curve of formula (9), and the lower curve is the high-frequency enhancement filter function curve of formula (7). In contrast, the high frequency enhancement filter function of equation (9) works better.
The filter function added with the high-frequency enhancement filter function on the basis of the basic filter function is expressed as a formula (11), and the filter function is expressed as F', wherein the expression is as follows:
F′＝IFFT(FFT(h)*Smooth*Cutoff*filter) (11)
Fig. 5 is a schematic diagram showing a comparison of a basic filter function curve and a filter function curve modified by adding a high-frequency enhancement filter function on the basis of the basic filter function. In fig. 5, the lower curve is a basic filter function curve, and the upper curve is a filter function curve improved by adding a high-frequency enhancement filter function on the basis of the basic filter function. As can be seen from fig. 5, the high frequency part in the image is enhanced. By adjusting the adjustable parameters in the formula, the enhancement part can just correspond to the frequency domain of the target tissue signal, so that the enhancement of the target tissue signal can be realized. For example, by adjusting the formula parameters such that the enhancement portion exactly corresponds to the frequency domain of the vascular signal, targeted enhancement of the vascular signal can be achieved.
Fig. 6 is a tomographic image obtained by three-dimensionally reconstructing a blood vessel using basic filter function filtering. Fig. 7 is a tomographic image obtained by three-dimensionally reconstructing a blood vessel using a filter function modified by adding a high-frequency enhancement filter function on the basis of a basic filter function. As can be seen by comparing fig. 6 and fig. 7, the blood vessel portion in the tomographic image shown in fig. 7 has a stronger contrast with the background and sharper edges.
Fig. 8 is a three-dimensional blood vessel image obtained by three-dimensional reconstruction using a basic filter function. Fig. 9 is a three-dimensional blood vessel image obtained by three-dimensional reconstruction with the addition of a high-frequency enhancement filter function based on a basic filter function. Fig. 10 is an enlarged image of the three-dimensional blood vessel image in fig. 8. Fig. 11 is an enlarged image of the three-dimensional blood vessel image in fig. 9. Comparing fig. 8 and 9 with fig. 10 and 11, it can be seen that, in the three-dimensional blood vessel image obtained by adding the high-frequency enhancement filter function on the basis of the basic filter function and performing three-dimensional reconstruction, the peripheral artifact of the blood vessel part is less, the edge is clearer and sharper, the contrast is stronger, more blood vessels can be displayed, the display of tiny branches is clearer, and the wall of the tube is continuous and complete. Such high quality images can help doctors to diagnose and treat more accurately, and have important clinical significance.
According to the image reconstruction method provided by the embodiment of the invention, the two-dimensional projection data obtained by cone beam CT scanning of the target tissue of the subject is obtained, the two-dimensional projection data is subjected to filtering processing by utilizing the preset standard filtering function to obtain the first data, the first data is subjected to smooth filtering to obtain the second data, the data of the preset frequency range in the second data is enhanced by adopting the first parameter, the data of the other frequency ranges except the preset frequency range in the second data is enhanced by adopting the second parameter to obtain the third data, the value of the first parameter is smaller than the value of the second parameter, the preset frequency range is the frequency range corresponding to the target tissue, and the three-dimensional image reconstruction is carried out based on the third data to obtain the reconstructed image, so that the artifacts around the target tissue in the three-dimensional reconstructed image can be reduced, the edges of the target tissue can be clearer, more details can be displayed more clearly, and therefore, the image quality of the three-dimensional reconstructed image is improved.
Based on the method embodiment, the embodiment of the invention also provides a corresponding device, equipment and storage medium embodiment.
Fig. 12 is a functional block diagram of an image reconstruction device according to an embodiment of the present invention. As shown in fig. 12, in the present embodiment, the image reconstruction apparatus may include:
The acquisition module 210 is configured to acquire two-dimensional projection data obtained by cone beam CT scanning on a target tissue of a subject, and perform filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
a smoothing module 220, configured to perform smoothing filtering on the first data to obtain second data;
the enhancement module 230 is configured to enhance data of a preset frequency band in the second data by using a first parameter, enhance data of other frequency bands except the preset frequency band in the second data by using a second parameter, and obtain third data, where a value of the first parameter is smaller than a value of the second parameter, and the preset frequency band is a frequency band corresponding to the target organization;
and a reconstruction module 240, configured to reconstruct a three-dimensional image based on the third data, to obtain a reconstructed image.
In an exemplary implementation, the apparatus may further include:
the size acquisition module is used for acquiring the voxel size of a reconstruction matrix corresponding to the reconstruction of the image and the pixel size of a detector used for cone beam CT scanning of the target tissue;
a judging module, configured to judge whether the voxel size is larger than the pixel size;
The cut-off filtering module is used for setting data with the corresponding frequency higher than the preset frequency in the second data to be 0 if the voxel size is larger than the pixel size, so as to obtain fourth data;
the enhancement module 230 is specifically configured to:
and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
In one exemplary implementation, the enhancement module 230 may be specifically configured to:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
In an exemplary implementation, the apparatus may further include:
the exponential filtering module is used for filtering the third data by using an exponential filtering function to obtain fifth data, a first function value corresponding to the exponential filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in the other frequency bands in the third data;
The reconstruction module 240 is specifically configured to: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
In an exemplary implementation, the apparatus may further include:
the preprocessing module is used for preprocessing the two-dimensional projection data to obtain preprocessed data;
filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, which may include: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
In one exemplary implementation, the target tissue is a cerebral blood vessel.
In one exemplary implementation, the standard filter function is a Shepp-Logan function.
The embodiment of the invention also provides CT equipment. Fig. 13 is a hardware configuration diagram of a CT apparatus according to an embodiment of the present invention. As shown in fig. 13, the CT apparatus includes: an internal bus 301, and a memory 302, a processor 303 and an external interface 304 connected by the internal bus, wherein the external interface is used for connecting a detector of the CT system, and the detector comprises a plurality of detector chambers and corresponding processing circuits;
The memory 302 is configured to store machine-readable instructions corresponding to the image reconstruction logic;
the processor 303 is configured to read machine-readable instructions on the memory 302 and execute the instructions to implement the following operations:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter, before obtaining the third data, further includes:
Acquiring the voxel size of a reconstruction matrix corresponding to the image reconstruction and the pixel size of a detector used for cone beam CT scanning of the target tissue;
judging whether the voxel size is larger than the pixel size;
if yes, setting the data with the corresponding frequency higher than the preset frequency in the second data to be 0, and obtaining fourth data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter, and obtaining third data, wherein the method comprises the following steps:
and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter to obtain third data includes:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
In an exemplary implementation, the three-dimensional image reconstruction is performed based on the third data, and before obtaining the reconstructed image, the method further includes:
filtering the third data by using an exponential type filtering function to obtain fifth data, wherein a first function value corresponding to the exponential type filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in other frequency bands in the third data;
performing three-dimensional image reconstruction based on the third data to obtain a reconstructed image, including: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
In an exemplary implementation process, the filtering processing is performed on the two-dimensional projection data by using a preset standard filtering function, and before obtaining the first data, the method further includes:
preprocessing the two-dimensional projection data to obtain preprocessed data;
and filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, wherein the filtering comprises the following steps: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
In one exemplary implementation, the target tissue is a cerebral blood vessel.
In one exemplary implementation, the standard filter function is a Shepp-Logan function.
The embodiment of the invention also provides a CT system, which comprises a detector, a scanning bed and CT equipment, wherein the detector comprises a plurality of detector chambers and corresponding processing circuits; wherein:
the detector chamber is used for detecting X-rays passing through a scanning object and converting the X-rays into electric signals in the scanning process of the CT system;
the processing circuit is used for converting the electric signal into a pulse signal and collecting energy information of the pulse signal;
the CT device is used for:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
And reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter, before obtaining the third data, further includes:
acquiring the voxel size of a reconstruction matrix corresponding to the image reconstruction and the pixel size of a detector used for cone beam CT scanning of the target tissue;
judging whether the voxel size is larger than the pixel size;
if yes, setting the data with the corresponding frequency higher than the preset frequency in the second data to be 0, and obtaining fourth data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter, and obtaining third data, wherein the method comprises the following steps:
and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter to obtain third data includes:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
In an exemplary implementation, the three-dimensional image reconstruction is performed based on the third data, and before obtaining the reconstructed image, the method further includes:
filtering the third data by using an exponential type filtering function to obtain fifth data, wherein a first function value corresponding to the exponential type filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in other frequency bands in the third data;
Performing three-dimensional image reconstruction based on the third data to obtain a reconstructed image, including: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
In an exemplary implementation process, the filtering processing is performed on the two-dimensional projection data by using a preset standard filtering function, and before obtaining the first data, the method further includes:
preprocessing the two-dimensional projection data to obtain preprocessed data;
and filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, wherein the filtering comprises the following steps: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
In one exemplary implementation, the target tissue is a cerebral blood vessel.
In one exemplary implementation, the standard filter function is a Shepp-Logan function.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, wherein the program when executed by a processor realizes the following operations:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
Smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter, before obtaining the third data, further includes:
acquiring the voxel size of a reconstruction matrix corresponding to the image reconstruction and the pixel size of a detector used for cone beam CT scanning of the target tissue;
judging whether the voxel size is larger than the pixel size;
if yes, setting the data with the corresponding frequency higher than the preset frequency in the second data to be 0, and obtaining fourth data;
Enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter, and obtaining third data, wherein the method comprises the following steps:
and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
In an exemplary implementation process, the enhancing the data of the preset frequency band in the second data by using the first parameter, and enhancing the data of the other frequency bands except the preset frequency band in the second data by using the second parameter to obtain third data includes:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
In an exemplary implementation, the three-dimensional image reconstruction is performed based on the third data, and before obtaining the reconstructed image, the method further includes:
Filtering the third data by using an exponential type filtering function to obtain fifth data, wherein a first function value corresponding to the exponential type filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in other frequency bands in the third data;
performing three-dimensional image reconstruction based on the third data to obtain a reconstructed image, including: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
In an exemplary implementation process, the filtering processing is performed on the two-dimensional projection data by using a preset standard filtering function, and before obtaining the first data, the method further includes:
preprocessing the two-dimensional projection data to obtain preprocessed data;
and filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, wherein the filtering comprises the following steps: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
In one exemplary implementation, the target tissue is a cerebral blood vessel.
In one exemplary implementation, the standard filter function is a Shepp-Logan function.
For the device and apparatus embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present description. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Other embodiments of the present description will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This specification is intended to cover any variations, uses, or adaptations of the specification following, in general, the principles of the specification and including such departures from the present disclosure as come within known or customary practice within the art to which the specification pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the specification being indicated by the following claims.
It is to be understood that the present description is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present description is limited only by the appended claims.
The foregoing description of the preferred embodiments is provided for the purpose of illustration only, and is not intended to limit the scope of the disclosure, since any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the disclosure are intended to be included within the scope of the disclosure.
Claims (10)
1. An image reconstruction method, comprising:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
Smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
2. The method of claim 1, wherein the step of enhancing the data of the preset frequency band in the second data by using a first parameter and enhancing the data of the other frequency bands except the preset frequency band in the second data by using a second parameter, before obtaining the third data, further comprises:
acquiring the voxel size of a reconstruction matrix corresponding to the image reconstruction and the pixel size of a detector used for cone beam CT scanning of the target tissue;
judging whether the voxel size is larger than the pixel size;
if yes, setting the data with the corresponding frequency higher than the preset frequency in the second data to be 0, and obtaining fourth data;
In response to obtaining fourth data, the step of enhancing the data of the preset frequency band in the second data by using a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the second data by using a second parameter, so as to obtain third data, includes the following steps:
and enhancing the data of the preset frequency band in the fourth data by adopting a first parameter, and enhancing the data of other frequency bands except the preset frequency band in the fourth data by adopting a second parameter to obtain third data.
3. The method of claim 1, wherein enhancing the data of the preset frequency band in the second data with the first parameter and enhancing the data of the other frequency bands except the preset frequency band in the second data with the second parameter to obtain third data comprises:
and continuously enhancing the data of the preset frequency band in the second data by adopting a plurality of first parameters, continuously enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a plurality of second parameters to obtain third data, wherein the number of the first parameters is equal to that of the second parameters.
4. The method of claim 1, wherein reconstructing a three-dimensional image based on the third data, prior to obtaining a reconstructed image, further comprises:
filtering the third data by using an exponential type filtering function to obtain fifth data, wherein a first function value corresponding to the exponential type filtering function is larger than a second function value, the first function value is a function value corresponding to data in the preset frequency band in the third data, and the second function value is a function value corresponding to data in other frequency bands in the third data;
in response to obtaining the fifth data, performing three-dimensional image reconstruction based on the third data to obtain a reconstructed image, including the following steps: and reconstructing a three-dimensional image based on the fifth data to obtain a reconstructed image.
5. The method of claim 1, wherein filtering the two-dimensional projection data using a predetermined standard filter function, before obtaining the first data, further comprises:
preprocessing the two-dimensional projection data to obtain preprocessed data;
and filtering the two-dimensional projection data by using a preset standard filtering function to obtain first data, wherein the filtering comprises the following steps: and filtering the preprocessed data by using a preset standard filtering function to obtain first data.
6. The method of claim 1, wherein the target tissue is a cerebral blood vessel.
7. The method of claim 1, wherein the standard filter function is a Shepp-Logan function.
8. An image reconstruction apparatus, comprising:
the acquisition module is used for acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and carrying out filtering processing on the two-dimensional projection data by utilizing a preset standard filtering function to obtain first data;
the smoothing module is used for carrying out smoothing filtering on the first data to obtain second data;
the enhancement module is used for enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and the reconstruction module is used for reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
9. A CT apparatus, comprising: an internal bus, and a memory, a processor and an external interface connected through the internal bus; the external interface is used for being connected with a detector of the CT system, and the detector comprises a plurality of detector chambers and corresponding processing circuits;
The memory is used for storing machine-readable instructions corresponding to control logic of image reconstruction;
the processor is configured to read the machine-readable instructions on the memory and perform operations comprising:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
10. A CT system comprising a detector, a scan bed and a CT apparatus, the detector comprising a plurality of detector cells and corresponding processing circuitry; wherein:
the detector chamber is used for detecting X-rays passing through a scanning object and converting the X-rays into electric signals in the scanning process of the CT system;
The processing circuit is used for converting the electric signal into a pulse signal and collecting energy information of the pulse signal;
the CT device is used for:
acquiring two-dimensional projection data obtained by cone beam CT scanning of target tissues of a subject, and performing filtering processing on the two-dimensional projection data by using a preset standard filtering function to obtain first data;
smoothing and filtering the first data to obtain second data;
enhancing the data of the preset frequency band in the second data by adopting a first parameter, enhancing the data of other frequency bands except the preset frequency band in the second data by adopting a second parameter to obtain third data, wherein the value of the first parameter is smaller than that of the second parameter, and the preset frequency band is the frequency band corresponding to the target organization;
and reconstructing a three-dimensional image based on the third data to obtain a reconstructed image.
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