CN103745488A - Method and device for generating projection data in computer tomography - Google Patents
Method and device for generating projection data in computer tomography Download PDFInfo
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Abstract
The invention discloses a method and a device for generating projection data in computer tomography. The method comprises the following steps: obtaining originally-collected projection data as first current projection data; reconstructing an image by using the first current projection data to obtain a current estimated image; carrying out orthographic projection on the image to obtain second current projection data; combining projection data, which do not belong to an original region, in the second current projection data with projection data, which belong to the original region, in the first current projection data to obtain third current projection data; if the third current projection data do not meet an iteration terminating condition, taking the third current projection data as the first current projection data and returning to execute the step of using the first current projection data to reconstruct the image; if the third current projection data meet the iteration terminating condition, defining the third current projection data as target projection data. According to the technical scheme provided by the invention, the finally-generated projection data are more accurate, so that the more accurate image is reconstructed.
Description
Technical field
The application relates to technical field of image processing, particularly relates to the method and apparatus that generates data for projection in a kind of computer tomography.
Background technology
At present, such as various CT(Computed Tomography, computer tomography) equipment has been widely applied to medical diagnosis, utilizes CT device scan sufferer and the reconstruction image that obtains, doctor can obtain and dissect accurately location, thereby disease is made to judgement comprehensively and accurately.For example, on a kind of current comparatively advanced CT equipment, integrated PET(Positron Emission Computed Tomogaphy, positron emission computerized tomography) technology and CT technology, form a complete imaging system, i.e. PET-CT system; Adopt PET-CT system to carry out body scan rapidly to sufferer, obtain the anatomic image of CT reconstruction and the functional metabolism image that PET rebuilds simultaneously, make doctor also recognize biological metabolism information when acquisition is dissected location accurately.
In various CT equipment, the X ray projection that need to project surveyed area to radiographic source detects and collects data for projection, to utilize data for projection to rebuild image.And in order to reduce the radiation dose of CT to sufferer, tend to adopt the radiation source of small-bore to carry out radiation scanning, but under the scanning of small-bore, CT equipment cannot collect the data for projection of partial image region.At the data for projection shown in Fig. 1, gather in schematic diagram, in whole rectangle frame, it is complete reconstruction image-region, wherein, FOV(Field of Views, the image reconstruction visual field) image-region is the image-region that can collect data for projection, expanding FOV image-region is the image-region that cannot collect data for projection.In the string figure forming in data for projection orthogonal projection as shown in Figure 2, can find out, the part in the middle of string figure is to collect data for projection, and the part on string figure both sides does not collect data for projection.Therefore, owing to there being the image-region that cannot collect data for projection in the imaging of CT technology, this not only makes CT equipment rebuild the image obtaining and brings the incomplete problem of blocking, and for PET-CT equipment, in order significantly to shorten sweep time, the data for projection that the technology of CT just that the correction for attenuation of PET technology adopts collects, so the problem of blocking in the imaging of CT technology also can cause the inaccurate of PET correction for attenuation.Therefore, for fear of partial image region, cannot collect data for projection and the CT image that brings blocks problem and PET correction for attenuation is inaccurate, just need to obtain the data for projection in complete image region.
At present, occurred that some generate the implementation of the data for projection in complete image region.For example, a kind of available technology adopting be, based on acquired original to the data for projection of partial image region estimate the data for projection of whole image-region, and on the basis of the data for projection estimating by iteration repeatedly retrain estimate before and after the variation of data for projection, with this, finally generate the data for projection in complete image region.But, because the data for projection estimating exists deviation with respect to real data for projection, prior art, constantly the data for projection estimating being carried out in the process of iteration, will cause the final whole image-region inner projection data that generate all inaccurate, thereby cause rebuilding the inaccurate of image.
Summary of the invention
The application's technical matters to be solved is, the method and apparatus that generates data for projection in a kind of computer tomography is provided, to solve all inaccurate technical matterss of whole image-region inner projection data of the final generation causing according to carrying out repeatedly iteration in prior art on the basis of the data for projection estimating, and the inaccurate technical matters of image being reconstructed by the inaccurate data for projection of word.
First aspect, the embodiment of the present application provides a kind of method that generates data for projection in computer tomography, and the method comprises:
Obtain data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area;
Utilize described the first current data for projection to rebuild image, obtain current estimated image;
Described current estimated image is carried out to orthogonal projection, obtain the second current data for projection;
Merge and in described the second current data for projection, do not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtain the 3rd current data for projection;
In response to described the 3rd current data for projection, do not meet default stopping criterion for iteration, using described the 3rd current data for projection again as the first current data for projection, return and carry out described described the first current data for projection reconstruction image that utilizes, obtain current estimated image;
In response to described the 3rd current data for projection, meet described stopping criterion for iteration, described the 3rd current data for projection is defined as to the target projection data of whole image-region.
In the possible implementation of the first of first aspect, described stopping criterion for iteration is: the ratio of the first norm and the second norm is less than default termination threshold value; Described the first norm is the norm calculating with the difference of described the 3rd current data for projection and described the second current data for projection, and described the second norm is the norm calculating with described the 3rd current data for projection.
In the possible implementation of the second of first aspect, described method also comprises:
Using gray-scale value in described current estimated image, belong to pixel in tonal range to be regulated as current adjusting pixel, based on constraint weight by the gray-scale value of current adjusting pixel described in each direction constrain to reference gray level value, and using the image that obtains after constraint again as current estimated image, enter to carry out and described described current estimated image is carried out to orthogonal projection, obtain the second current data for projection.
In the third possible implementation of first aspect, in conjunction with the possible implementation of the second of first aspect, described tonal range to be regulated is the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, described gray scale maximal value to be regulated is to increase with range parameter the gray-scale value that described reference gray level value obtains, and described minimum gray value to be regulated is to reduce with described range parameter the gray-scale value that described reference gray level value obtains.
In the 4th kind of possible implementation of first aspect, in conjunction with the third possible implementation of first aspect, described range parameter is the gray-scale value mean square deviation of each pixel in described current estimated image.
In the 5th kind of possible implementation of first aspect, in conjunction with the possible implementation of the second of first aspect, described reference gray level value is the maximum gray-scale value of distributed points in the mean value of each pixel gray-scale value in described current estimated image or described current estimated image.
Second aspect, the embodiment of the present application also provides the device that generates data for projection in a kind of computer tomography, and this device comprises:
Acquired original module, for obtaining data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area;
Image reconstruction module, for utilizing described the first current data for projection to rebuild image, obtains current estimated image;
Image projection module, for described current estimated image is carried out to orthogonal projection, obtains the second current data for projection;
Data for projection merges module, for merging described the second current data for projection, does not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtains the 3rd current data for projection;
Rebuild again trigger module, for not meeting default stopping criterion for iteration in response to described the 3rd current data for projection, using described the 3rd current data for projection, again as the first current data for projection, again trigger described image reconstruction module;
Data for projection generation module, for meeting described stopping criterion for iteration in response to described the 3rd current data for projection, is defined as described the 3rd current data for projection the target projection data of whole image-region.
In the possible implementation of the first of second aspect, described stopping criterion for iteration is: the ratio of the first norm and the second norm is less than default termination threshold value; Described the first norm is the norm calculating with the difference of described the 3rd current data for projection and described the second current data for projection, and described the second norm is the norm calculating with described the 3rd current data for projection.
In the possible implementation of the second of second aspect, described device also comprises:
Image constraints module, for belonging to pixel in tonal range to be regulated as current adjusting pixel using described current estimated image gray-scale value, based on constraint weight by the gray-scale value of current adjusting pixel described in each direction constrain to reference gray level value, and using the image that obtains after constraint again as current estimated image, trigger described image projection module.
In the third possible implementation of second aspect, in conjunction with the possible implementation of the second of second aspect, described tonal range to be regulated is the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, described gray scale maximal value to be regulated is to increase with range parameter the gray-scale value that described reference gray level value obtains, and described minimum gray value to be regulated is to reduce with described range parameter the gray-scale value that described reference gray level value obtains.
In the 4th kind of possible implementation of second aspect, in conjunction with the third possible implementation of second aspect, described range parameter is the gray-scale value mean square deviation of each pixel in described current estimated image.
In the 5th kind of possible implementation of second aspect, in conjunction with the possible implementation of the second of second aspect, described reference gray level value is the maximum gray-scale value of distributed points in the mean value of each pixel gray-scale value in described current estimated image or described current estimated image.
Compared with prior art, the present invention has the following advantages:
The technical scheme of the embodiment of the present application, first using acquired original to data for projection as the first current data for projection, rebuild estimated image and the second current data for projection of obtaining estimating, then the first current data for projection that belongs to original area and the second current data for projection that does not belong to original area are merged as the 3rd current data for projection, and in the situation that the 3rd current data for projection does not meet stopping criterion for iteration using the 3rd current data for projection again as the first current data for projection estimated projection data again, until the 3rd current data for projection meets stopping criterion for iteration, again the 3rd current data for projection is defined as to the target projection data of whole image-region.As can be seen here, pass through the embodiment of the present application, due to what adopt, be that to merge with the second current data for projection that does not belong to original area the 3rd current data for projection forming be that Image Iterative process is carried out on basis for the first current data for projection of belonging to original area, each iteration for the first current data for projection of rebuilding image all original area retained acquired original to real data for projection and not adopt the inaccurate data for projection estimating, the data for projection estimating does not only belong to those regions of original area for being filled into whole image-region, therefore, on the basis of the first current data for projection, get on and constantly carry out in the process of iteration, the data for projection at every turn estimating can be more and more accurate, thereby make the final whole image-region inner projection data that generate more accurate, with this, reconstruct image more accurately.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present application or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, the accompanying drawing the following describes is only some embodiment that record in the application, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is that data for projection gathers schematic diagram;
The string figure schematic diagram that Fig. 2 forms for data for projection orthogonal projection;
Fig. 3 is the process flow diagram that generates method one embodiment of data for projection in the application's Computer fault imaging;
Fig. 4 is the contrast schematic diagram of current estimated image before and after constraint in the embodiment of the present application;
Fig. 5 is the schematic diagram of the merging mode of the first current data for projection and the second current data for projection in the embodiment of the present application;
Fig. 6 is the structural drawing that generates device one embodiment of data for projection in the application's Computer fault imaging;
Fig. 7 is the structural drawing that generates the another embodiment of device of data for projection in the embodiment of the present application in the application's Computer fault imaging.
Embodiment
In order to make those skilled in the art person understand better the application's scheme, below in conjunction with the accompanying drawing in the embodiment of the present application, technical scheme in the embodiment of the present application is clearly and completely described, obviously, described embodiment is only the application's part embodiment, rather than whole embodiment.Based on the embodiment in the application, those of ordinary skills are not making the every other embodiment obtaining under creative work prerequisite, all belong to the scope of the application's protection.
Inventor finds through research, the available technology adopting repeatedly mode of iteration generates the data for projection of whole image-region, each iteration is all take the data for projection estimating, as basis, again to carry out image reconstruction completely to reappraise new data for projection, particularly, what during current iteration, rebuild that image adopts is the data for projection that a front iterative estimate goes out, and rebuilds the data for projection that data for projection that image estimates later adopts when as a rear iterative approximation image during current iteration.And in whole image-region, original area for acquired original to data for projection, its acquired original to data for projection be real data for projection, if each iteration is for rebuilding the data for projection once estimating before the data for projection of whole image-region of image all adopts as the iterative process of prior art, to will inevitably there is deviation with real data for projection in the data for projection that wherein belongs to original area, and along with iterative process is constantly carried out, the data for projection of whole image-region all more and more departs from real data for projection by the deviation existing due to original area data for projection, thereby cause the final whole image-region inner projection data that generate all inaccurate, and finally cause and rebuild the inaccurate of image.
Based on above-mentioned discovery, the application's main thought is: in the data for projection adopting at each iterative approximation image, retain the original data for projection collecting in original area, the data for projection once estimating before those regions that do not belong to original area in whole image-region utilize is filled; And each iteration estimated go out data for projection, also only choose data for projection in the image-region that does not belong to original area come with original area in the original data that the collect data for projection that need to adopt while merging as a rear iterative approximation image.Therefore, because each iteration has retained for rebuilding the data for projection of image the true data for projection that guarantor's acquired original arrives, can avoid rebuilding the data for projection that image all goes out based on a front iterative estimate and the deviation causing, the data for projection that each iterative estimate is gone out is more and more accurate, thereby make the final whole image-region inner projection data that generate more accurate, with this, reconstruct image more accurately.
Below in conjunction with accompanying drawing, by embodiment, describe the specific implementation that generates the method and apparatus of data for projection in the application's Computer fault imaging in detail.
Referring to Fig. 3, show the process flow diagram of method one embodiment that generates data for projection in the application's Computer fault imaging.In the present embodiment, for example can comprise the following steps:
S301, obtain data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area.
Wherein, in the data acquisition schematic diagram shown in Fig. 1, what original area was corresponding is FOV image-region, and the data for projection in FOV image-region is the data for projection that acquired original arrives.In the string figure shown in Fig. 2, zone line is original area, and the data for projection in zone line is the data for projection that acquired original arrives.
It should be noted that, the first current data for projection is the data for projection for rebuilding image, wherein comprises and also comprises the data for projection in the image-region except original area by the data for projection in original area.In the process of iteration first, owing to also not carrying out image reconstruction and estimation, so the first current data for projection can all be set to 0 by the data for projection in the image-region except original area when iteration first, represent that this part data for projection does not collect, in string figure as shown in Figure 2, in the region of the right and left, there is no data for projection.Be understandable that, for iteration first, the first current data for projection is the truncated projection data that have truncated region in image.
S302, utilize described the first current data for projection to rebuild image, obtain current estimated image.
Wherein, rebuild the method for image, can adopt traditional method for reconstructing, for example FBP(Filtered Back Projection, filtered back projection) algorithm, ART(Algebraic Reconstruction Technique, algebraic reconstruction technique) algorithm, OSEM(Ordered Subsets Expectation Maximization, in order maximum expected value) algorithm etc.
Be understandable that, S302 is that iterative process all needs the step of carrying out each time.For iteration first, owing to only having in the first current data for projection, in original area, there is data for projection and other image-regions do not exist data for projection, for the first current data for projection of rebuilding image, be incomplete data for projection, therefore, concerning iteration first, rebuild image and need to reconstruct complete image based on incomplete the first current data for projection, and aforesaid FBP algorithm, ART algorithm and OSEM algorithm can meet this requirement, make the present embodiment can realize from acquired original to imperfect data for projection estimate complete data for projection.In addition,, for non-iteration first, because the first current data for projection has obtained complete data for projection by a front iterative process, thereby make to rebuild image, can rebuild image by the first current data for projection based on complete.Wherein, about the first current data for projection using in non-iteration first, the present embodiment will be introduced in subsequent step, not repeat them here.
It should be noted that, the current estimated image obtaining in S302 generates the second current data for projection for S303.In the present embodiment, a kind of possible embodiment is when S302 is finished and obtains current estimated image, can and then carry out S303 and utilize this current estimated image to generate the second data for projection.But under this embodiment, the data for projection that constantly iteration estimates later will make to rebuild the profile indistinguishable of scanning object in image.
For fear of scanning object almost illegible in final reconstruction image, in the another kind of possible embodiment of the present embodiment, after each S302 is finished, can also be first using gray-scale value in described current estimated image, belong to pixel in tonal range to be regulated as current adjusting pixel, based on constraint weight by the gray-scale value of current adjusting pixel described in each direction constrain to reference gray level value, and using the image that obtains after constraint again as current estimated image, then enter and carry out S303.In this embodiment, because near the gray-scale value of the pixel of gray-scale value reference gray level value in current estimated image is restrained to reference gray level value, this makes near image-region reference gray level value be exaggerated with the gray difference of other image-regions, thereby make to rebuild, forms more obvious profile in image between this two parts region.Like this, from represent the image-region of scanning object, choose reference gray level value, can make to rebuild the gray difference between scanning object and background in image and be widened, thereby make the profile of scanning object more obvious.For example, the contrast that is current estimated image before and after constraint shown in Fig. 4 obviously can be found out from Fig. 4, and than the image before constraint, in the image after constraint, the profile of scanning object is clearer.
When current estimated image is retrained, concerning current adjusting pixel, because its gray-scale value is near reference gray level value, for the difference that widens gray scale in image just need to be by the gray-scale value of current adjusting pixel to reference gray level value direction constrain, particularly, can adopt following formula to carry out the constraint of current adjusting pixel:
v
2=αv
1+(1-α)v
0，v
1∈Γ，0<α<1；
Wherein, v
2represent the gray-scale value of the rear current adjusting pixel of constraint, v
1represent the gray-scale value of the front current adjusting pixel of constraint, v
0represent reference gray level value, α represents to retrain weight, and Г represents the affiliated scope of gray-scale value of current adjusting pixel, i.e. tonal range to be regulated.
But be understandable that, for the pixel that does not belong to current adjusting pixel, can keep the gray-scale value of these pixels constant, or, also can the opposite direction constraint to reference gray level value by the gray-scale value of these pixels.
It should be noted that, for choosing of above-mentioned reference gray-scale value, need to consider the scanning object gray-scale value that general performance goes out in reconstruction image.For example, for the CT equipment in medical treatment, because the scanning object of CT equipment is all that human body and main scan mode are transmission scan, and the principal ingredient of human body is water, and therefore, the attenuation coefficient that can select water is as with reference to gray-scale value.And for example, for more general computer tomography, can be using the mean value of each pixel gray-scale value in current estimated image as with reference to gray-scale value, wherein, the just original area based in current estimated image of the calculating of mean value, whole region that also can be based in current estimated image; Or, also can be using the gray-scale value that in current estimated image, distributed points is maximum as with reference to gray-scale value, particularly, the pixel number that in current estimated image before can first statistical restraint, each gray-scale value is corresponding forms a grey level histogram, then finds out a gray-scale value that pixel number is maximum as with reference to gray-scale value from grey level histogram.
Be understandable that, for aforementioned constraint weight, can arrange according to the demand of gradation of image difference amplification degree.For example, if need the degree of gradation of image difference larger, less constraint weight can be set; If need the degree of gradation of image difference less, larger constraint weight can be set.
In addition,, for aforementioned tonal range to be regulated, the gray-scale value scope that can present in current estimated image based on scanning object is determined.For example, for transmission scan, because the attenuation coefficient of transmission mainly concentrates in certain span, therefore, can the empirical value based on attenuation coefficient span determine gray scale maximal value and the minimum gray value of tonal range to be regulated.And for example, for more general computer tomography, can be using gray-scale value scope the most concentrated distributed points in current estimated image as tonal range to be regulated, particularly, the pixel number that in current estimated image before can first statistical restraint, each gray-scale value is corresponding forms a grey level histogram, then finds out gray-scale value scope that pixel number is maximum as with reference to gray-scale value from grey level histogram; Or also can determine tonal range to be regulated based on a range parameter and reference gray level value, particularly, described tonal range to be regulated can be for being positioned at the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, the gray-scale value that described gray scale maximal value to be regulated can obtain for increase described reference gray level value with range parameter, described minimum gray value to be regulated can be for reducing the gray-scale value that described reference gray level value obtains with described range parameter.Determining in the embodiment of tonal range to be regulated with range parameter and reference gray level value, more specifically, tonal range to be regulated can be expressed as following formula:
Γ=((1-f)v
0,(1+f)v
0)；
Wherein, Г represents tonal range to be regulated, and f represents range parameter, v
0represent reference gray level value.
Be understandable that, for aforementioned range parameter, can be the fixed numbers of a setting in whole iterative process, or, the numerical value constantly changing according to current estimated image in the time of also can being each iteration.For example, the gray-scale value mean square deviation that can calculate each pixel in current estimated image is determined tonal range to be regulated as range parameter.
Then return to Fig. 3.
S303, described current estimated image is carried out to orthogonal projection, obtain the second current data for projection.
Current estimated image can obtain the data for projection that this iterative estimate goes out, i.e. the second current data for projection through orthogonal projection.Be understandable that, no matter whether this iteration be iteration first, all can have the data for projection of the image-region except original area in the second current data for projection estimating.
S304, merge and in described the second current data for projection, do not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtain the 3rd current data for projection.
Wherein, in the first current data for projection, belong to the data for projection of original area, be the data for projection that acquired original arrives, and in the second current data for projection, do not belong to the data for projection of original area, be this iteration estimated go out acquired original less than the data for projection of image-region.Therefore, in these two parts data, merge in the 3rd current data for projection obtaining, just can in original area, retain all the time the data for projection that acquired original arrives, and the data for projection just each iterative estimate being gone out is filled in other image-regions except original area.
In Fig. 5, shown in a be acquired original to the string figure that forms of data for projection, this string figure areas at both sides (being region 1 and region 2) does not have data for projection and only has zone line (being region 3) to have data for projection as seen; Shown in b is the string figure that the second current data for projection of estimating in this iteration forms, and this string figure comprises that region 1～3 all has data for projection in interior whole image-region as seen; Shown in c is the 3rd current data for projection that merges in this iteration, and the region 3 in this string figure is the region 3 in a string figure, and the region 1,2 in this string figure is respectively the region 1,2 in b string figure.
S305, in response to described the 3rd current data for projection, do not meet default stopping criterion for iteration, using described the 3rd current data for projection, again as the first current data for projection, return and carry out S302.
When the 3rd current data for projection does not meet stopping criterion for iteration, show that the data for projection that current estimation generates afterwards can't meet the demands, also need further estimation, the the first current data for projection that now is again used for rebuilding image using the 3rd current data for projection of this grey iterative generation as next iteration, returns to S302 and carries out the estimation of next iteration.Be understandable that, the first current data for projection obtaining in S305 is different from the first current data for projection obtaining in S301; In S301, obtain for the first current data for projection of iteration first, it has data for projection and other region projection data are 0 at original area; The right and wrong that obtain in S305 are the first current data for projection of iteration first, its in original area, have acquired original to data for projection and iterative process estimates before other regions have data for projection.
It should be noted that, stopping criterion for iteration can adopt any one by iteration, to realize the stopping criterion for iteration adopting in the method for image reconstruction.For example, can meet the requirements and be used as stopping criterion for iteration with the intensity of variation between the 3rd current data for projection after the first current data for projection before this iterative estimate and estimation.And for example, difference degree between the 3rd current data for projection that the second current data for projection that can go out with this iterative estimate and merging obtain meets the requirements and is used as stopping criterion for iteration, as a kind of concrete stopping criterion for iteration, the ratio that can be the first norm and the second norm is less than default termination threshold value, wherein, described the first norm is the norm calculating with the difference of described the 3rd current data for projection and described the second current data for projection, described the second norm is the norm calculating with described the 3rd current data for projection, this stopping criterion for iteration can be expressed as following formula:
Wherein, P
3represent the 3rd current data for projection, P
2represent the second current data for projection, L(X) represent norm that data X is calculated, ε represents to stop threshold value.For example, termination can be no more than a fixed numbers of 5%.
S306, in response to described the 3rd current data for projection, meet described stopping criterion for iteration, described the 3rd current data for projection is defined as to the target projection data of whole image-region.
When the 3rd current data for projection meets stopping criterion for iteration, show that the data for projection that current estimation generates afterwards can meet the demands, no longer need further estimation, now using the 3rd current data for projection of this grey iterative generation as target projection data.Be understandable that, these target projection data can be for reconstructing target CT image, or, further, can be for the correction for attenuation of PET scanning.
By the technical scheme of the present embodiment, due to what adopt, be that to merge with the second current data for projection that does not belong to original area the 3rd current data for projection forming be that Image Iterative process is carried out on basis for the first current data for projection of belonging to original area, each iteration for the first current data for projection of rebuilding image all original area retained acquired original to real data for projection and not adopt the inaccurate data for projection estimating, the data for projection estimating does not only belong to those regions of original area for being filled into whole image-region, therefore, on the basis of the first current data for projection, get on and constantly carry out in the process of iteration, the data for projection at every turn estimating can be more and more accurate, thereby make the final whole image-region inner projection data that generate more accurate, with this, reconstruct image more accurately.
Corresponding to preceding method embodiment, the application also provides the device that generates data for projection in a kind of computer tomography.
Referring to Fig. 6, show the structural drawing of device one embodiment that generates data for projection in the application's Computer fault imaging.In the present embodiment, described device for example can comprise:
Acquired original module 601, for obtaining data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area;
Data for projection merges module 604, for merging described the second current data for projection, does not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtains the 3rd current data for projection;
Rebuild again trigger module 605, for not meeting default stopping criterion for iteration in response to described the 3rd current data for projection, using described the 3rd current data for projection, again as the first current data for projection, again trigger described image reconstruction module;
Data for projection generation module 606, for meeting described stopping criterion for iteration in response to described the 3rd current data for projection, is defined as described the 3rd current data for projection the target projection data of whole image-region.
Wherein, optional, in the application's device embodiment, described stopping criterion for iteration can be: the ratio of the first norm and the second norm is less than default termination threshold value; Described the first norm is the norm calculating with the difference of described the 3rd current data for projection and described the second current data for projection, and described the second norm is the norm calculating with described the 3rd current data for projection.
Referring to Fig. 7, show the structural drawing that generates the another embodiment of device of data for projection in the application's Computer fault imaging.In the present embodiment, except all structures shown in Fig. 6, described device for example can also comprise:
Wherein, optionally, in the application's device embodiment, described tonal range to be regulated can be for being positioned at the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, the gray-scale value that described gray scale maximal value to be regulated can obtain for increase described reference gray level value with range parameter, described minimum gray value to be regulated can be for reducing the gray-scale value that described reference gray level value obtains with described range parameter.
Further alternatively, described range parameter can be the gray-scale value mean square deviation of each pixel in described current estimated image.
Wherein, optional, in the application's device embodiment, described reference gray level value can be the maximum gray-scale value of distributed points in the mean value of each pixel gray-scale value in described current estimated image or described current estimated image.
It should be noted that, in this article, relational terms such as the first and second grades is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply and between these entities or operation, have the relation of any this reality or sequentially.Term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thereby the process, method, article or the equipment that make to comprise a series of key elements not only comprise those key elements, but also comprise other key elements of clearly not listing, or be also included as the intrinsic key element of this process, method, article or equipment.The in the situation that of more restrictions not, the key element being limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment that comprises described key element and also have other identical element.
For device embodiment, because it corresponds essentially to embodiment of the method, so relevant part is referring to the part explanation of embodiment of the method.Device embodiment described above is only schematic, the wherein said unit as separating component explanation can or can not be also physically to separate, the parts that show as unit can be or can not be also physical locations, can be positioned at a place, or also can be distributed in multiple network element.Can select according to the actual needs some or all of module wherein to realize the object of the present embodiment scheme.Those of ordinary skills, in the situation that not paying creative work, are appreciated that and implement.
The above is only the application's embodiment; it should be pointed out that for those skilled in the art, do not departing under the prerequisite of the application's principle; can also make some improvements and modifications, these improvements and modifications also should be considered as the application's protection domain.
Claims (10)
1. a method that generates data for projection in computer tomography, is characterized in that, comprising:
Obtain data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area;
Utilize described the first current data for projection to rebuild image, obtain current estimated image;
Described current estimated image is carried out to orthogonal projection, obtain the second current data for projection;
Merge and in described the second current data for projection, do not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtain the 3rd current data for projection;
In response to described the 3rd current data for projection, do not meet default stopping criterion for iteration, using described the 3rd current data for projection again as the first current data for projection, return and carry out described described the first current data for projection reconstruction image that utilizes, obtain current estimated image;
In response to described the 3rd current data for projection, meet described stopping criterion for iteration, described the 3rd current data for projection is defined as to the target projection data of whole image-region.
2. method according to claim 1, is characterized in that, also comprises:
Using gray-scale value in described current estimated image, belong to pixel in tonal range to be regulated as current adjusting pixel, based on constraint weight by the gray-scale value of current adjusting pixel described in each direction constrain to reference gray level value, and using the image that obtains after constraint again as current estimated image, enter to carry out and described described current estimated image is carried out to orthogonal projection, obtain the second current data for projection.
3. method according to claim 2, it is characterized in that, described tonal range to be regulated is the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, described gray scale maximal value to be regulated is to increase with range parameter the gray-scale value that described reference gray level value obtains, and described minimum gray value to be regulated is to reduce with described range parameter the gray-scale value that described reference gray level value obtains.
4. method according to claim 3, is characterized in that, described range parameter is the gray-scale value mean square deviation of each pixel in described current estimated image.
5. method according to claim 2, is characterized in that, described reference gray level value is the maximum gray-scale value of distributed points in the mean value of each pixel gray-scale value in described current estimated image or described current estimated image.
6. a device that generates data for projection in computer tomography, is characterized in that, comprising:
Acquired original module, for obtaining data for projection that acquired original arrives as the first current data for projection, and the image-region using acquired original to data for projection is as original area;
Image reconstruction module, for utilizing described the first current data for projection to rebuild image, obtains current estimated image;
Image projection module, for described current estimated image is carried out to orthogonal projection, obtains the second current data for projection;
Data for projection merges module, for merging described the second current data for projection, does not belong to the data for projection that belongs to described original area in the data for projection of described original area and described the first current data for projection, obtains the 3rd current data for projection;
Rebuild again trigger module, for not meeting default stopping criterion for iteration in response to described the 3rd current data for projection, using described the 3rd current data for projection, again as the first current data for projection, again trigger described image reconstruction module;
Data for projection generation module, for meeting described stopping criterion for iteration in response to described the 3rd current data for projection, is defined as described the 3rd current data for projection the target projection data of whole image-region.
7. device according to claim 6, is characterized in that, also comprises:
Image constraints module, for belonging to pixel in tonal range to be regulated as current adjusting pixel using described current estimated image gray-scale value, based on constraint weight by the gray-scale value of current adjusting pixel described in each direction constrain to reference gray level value, and using the image that obtains after constraint again as current estimated image, trigger described image projection module.
8. device according to claim 7, it is characterized in that, described tonal range to be regulated is the gray-scale value scope between gray scale maximal value to be regulated and minimum gray value to be regulated, wherein, described gray scale maximal value to be regulated is to increase with range parameter the gray-scale value that described reference gray level value obtains, and described minimum gray value to be regulated is to reduce with described range parameter the gray-scale value that described reference gray level value obtains.
9. device according to claim 8, is characterized in that, described range parameter is the gray-scale value mean square deviation of each pixel in described current estimated image.
10. device according to claim 7, is characterized in that, described reference gray level value is the maximum gray-scale value of distributed points in the mean value of each pixel gray-scale value in described current estimated image or described current estimated image.
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