CN107730455A - Obtain the method and device of MAR images - Google Patents
Obtain the method and device of MAR images Download PDFInfo
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- CN107730455A CN107730455A CN201610655886.2A CN201610655886A CN107730455A CN 107730455 A CN107730455 A CN 107730455A CN 201610655886 A CN201610655886 A CN 201610655886A CN 107730455 A CN107730455 A CN 107730455A
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- 238000000034 method Methods 0.000 title claims abstract description 62
- 239000002184 metal Substances 0.000 claims abstract description 69
- 229910052751 metal Inorganic materials 0.000 claims abstract description 69
- 230000008569 process Effects 0.000 claims abstract description 28
- 238000004364 calculation method Methods 0.000 claims abstract description 13
- 238000012937 correction Methods 0.000 claims abstract description 10
- 230000009467 reduction Effects 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims description 30
- 238000010606 normalization Methods 0.000 claims description 5
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 claims description 2
- 239000010931 gold Substances 0.000 claims description 2
- 229910052737 gold Inorganic materials 0.000 claims description 2
- 238000002591 computed tomography Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 101000911772 Homo sapiens Hsc70-interacting protein Proteins 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 210000004394 hip joint Anatomy 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Classifications
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- G06T5/75—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/25—Process efficiency
Abstract
The present invention relates to the method for the image (MAR images) for obtaining metal artifacts reduction and its corresponding device.Methods described includes：Back projection is carried out to initial sinusoids to obtain original image；Metal mask is obtained from the original image, and metallic traces are obtained based on the metal mask；Enter the ray hardened correction (BHC) of row metal to the original image to obtain metal BHC images；Projection, which is obtained, from the metallic traces completes (PC) image；Calculation process is carried out to obtain prior image to the metal BHC images and the PC images；Forward projection is carried out to the prior image to obtain priori sine curve；And the priori sine curve is handled to finally give MAR images.By the above method and device, the bar element shape artifact as caused by high-density matter can be reduced in the MAR images finally given.
Description
Technical field
The present invention relates to the technical field of image procossing, is more particularly to used to obtain metal artifacts reduction (MAR) image
Method and device.
Background technology
Metal artifacts are the generic terms for being used to describe artifact in fields of measurement, and these artifacts because of high-density objects by being drawn
The ray hardened, scattering that rises, noise and non-linear partial volume effect are brought.Metal artifacts are with thin bar element shape artifact and bright
Dark banding artifact occurs, and they seriously destroy the picture quality in computed tomography (CT) image, and therefore frequent
Reduce the diagnostic value of these CT images.There is many MAR technology, the part that these technologies will be influenceed in initial data by metal
All regard insecure data as and therefore replace them.Although these sine curve restorative procedures are eliminating metal puppet
Success is can be said to be on shadow on the whole, but they also reduce the resolution ratio for being corrected image, and especially, they can not be extensive exactly
The true value being replaced again, and the image being therefore corrected will be presented and obscured.For example, to be damaged initial data in replacement same
When inhibit in the normalization MAR (NMAR) of most of new artifact, still using the scheme replaced completely, this causes data for it
Loss.
In order to balance artifact and resolution ratio, often using the method for mixing.Specifically, adaptive normalization metal is introduced
Artifact reduces (ANMAR), and this is a kind of algorithm based on initial data, and it is tied original projection and NMAR or MAR projections
Close.In other words, in order to increase the resolution ratio of MAR images, the original image for not passing through MAR is introduced.However, at the same time,
Metal artifacts in original image have been also introduced into last MAR images.Fig. 1 is just showing conventional hybrid as described above
The MAR images that method is obtained, it reflects, to (for example, being obtained by the hip joint of human body carrying out CT scan)
After original CT image carries out MAR, leave as the white bars element shape artifact caused by the high-density matter in the original CT image.
The content of the invention
The present invention exemplary embodiment aim to overcome that it is of the prior art above-mentioned and/or other the problem of.
Therefore, exemplary embodiment of the invention provides a kind of method and device of acquisition MAR images, and it can reduce the MAR
The bar element shape artifact as caused by high-density matter in image.
According to exemplary embodiment, a kind of method of acquisition MAR images comprises the following steps：Initial sinusoids are carried out
Back projection is to obtain original image；Metal mask is obtained from the original image, and metal rail is obtained based on the metal mask
Mark；Enter the ray hardened correction (BHC) of row metal to the original image to obtain metal BHC images；Obtained from the metallic traces
(PC) image is completed to projection；Calculation process is carried out to obtain prior image to the metal BHC images and the PC images；It is right
The prior image carries out forward projection to obtain priori sine curve；And the priori sine curve is handled with most
MAR images are obtained eventually.
According to another exemplary embodiment, a kind of device of acquisition MAR images includes：Original image acquisition module, is used for
Back projection is carried out to initial sinusoids to obtain original image；Metallic traces acquisition module, for from the original image
Metal mask is obtained, and metallic traces are obtained based on the metal mask；Metal BHC modules, for being carried out to the original image
Metal BHC is to obtain metal BHC images；PC image collection modules, for obtaining PC images from the metallic traces；Calculation process
Module, for carrying out calculation process to the metal BHC images and the PC images to obtain prior image；Priori sine curve
Acquisition module, for carrying out forward projection to the prior image to obtain priori sine curve；And at priori sine curve
Module is managed, for being handled the priori sine curve to finally give MAR images.
By following detailed description, accompanying drawing and claim, other features and aspect can be made apparent from.
Brief description of the drawings
It is described in conjunction with the accompanying drawings for the exemplary embodiment of the present invention, the present invention may be better understood,
In accompanying drawing：
Fig. 1 shows the MAR images obtained by prior art；
Fig. 2 is the flow chart according to an exemplary embodiment of the present invention for being used to obtain the method for MAR images；
Fig. 3 show it is according to an exemplary embodiment of the present invention be used to obtain in the methods of MAR images from the metal
Track obtains the flow chart of one embodiment of the step of PC images；
Fig. 4 show it is according to an exemplary embodiment of the present invention be used to obtain in the methods of MAR images to the metal
BHC images and the PC images carry out the flow chart of the one embodiment for the step of calculation process is to obtain prior image；
Fig. 5 show it is according to an exemplary embodiment of the present invention be used to obtain in the methods of MAR images to the priori
Sine curve is handled the flow chart of one embodiment the step of to finally give MAR images；
Fig. 6 show it is according to an exemplary embodiment of the present invention be used to obtain in the methods of MAR images to the priori
Sine curve is handled the flow chart of another embodiment the step of to finally give MAR images；
Fig. 7 is the schematic block diagram according to an exemplary embodiment of the present invention for being used to obtain the device of MAR images；
Fig. 8 shows that traditional MAR image obtainment methods and current MAR images according to an exemplary embodiment of the present invention obtain
Comparative result between method；
Fig. 9 respectively illustrates the image obtained without MAR, obtains image using the MAR of conventional art and adopt
The image obtained with current MAR according to an exemplary embodiment of the present invention.
Specific embodiment
Embodiment of the invention explained below, it should be pointed out that in the specific descriptions of these embodiments
During, in order to carry out brief and concise description, this specification can not possibly be made in detail to all features of the embodiment of reality
Most description.It is to be understood that in the actual implementation process of any one embodiment, as in any one work
During journey project or design object, in order to realize the objectives of developer, in order to meet system it is related or business
The related limitation of industry, various specific decision-makings can be usually made, and this can also be implemented from a kind of embodiment to another kind
Changed between mode.Moreover, it is to be understood that although effort made in this development process is probably complicated
And it is tediously long, but for one of ordinary skill in the art related to present disclosure, in the disclosure
Some designs carried out on the basis of the technology contents of exposure, the change such as manufacture or production is conventional technology, no
It should be understood to that content of this disclosure is insufficient.
Unless otherwise defined, the technical term or scientific terminology used in claims and specification should be this hair
The ordinary meaning that the personage with general technical ability is understood in bright art.Present patent application specification and power
" first ", " second " and the similar word used in sharp claim is not offered as any order, quantity or importance, and
It is used only to distinguish different parts.The similar word such as "one" or " one " is not offered as quantity limitation, but represents
Exist at least one.Either the similar word such as "comprising" means to appear in the element before " comprising " or "comprising" " comprising "
Either object covers the element for appearing in " comprising " or "comprising" presented hereinafter or object and its equivalent element, it is not excluded that
Other elements or object." connection " either the similar word such as " connected " is not limited to physics or mechanical connection,
It is also not necessarily limited to direct or indirect connection.
According to an embodiment of the invention, there is provided a kind of method of acquisition MAR images.
With reference to figure 2, Fig. 2 is the flow according to an exemplary embodiment of the present invention for being used to obtain the method 200 of MAR images
Figure.Method 200 can comprise the following steps 210 to 270.
As shown in Fig. 2 in step 210, back projection is carried out to initial sinusoids to obtain original image.This is original
The sine curve that sine curve is obtained by the scanned object of CT scan.The sweep object can be specially certain part of human body,
Such as human hip.
In a step 220, metal mask is obtained from the original image, and metallic traces is obtained based on the metal mask.
Specifically, the metal mask is obtained by carrying out threshold value extraction to the original image.And then by the metal
Mask carries out forward projection to obtain the metallic traces.
In step 230, the ray hardened correction (BHC) of row metal is entered to the original image to obtain metal BHC images.
By the step, reduce the metal beam hardening artifact in the original image.
In step 240, obtain projection from the metallic traces obtained in a step 220 and complete (PC) image.
In one embodiment of the invention, with reference to figure 3, step 240 may further include following sub-step 241 to
242。
In sub-step 241, PC sine curves are obtained first from the metallic traces obtained in a step 220.
Then, in sub-step 242, back projection is carried out to obtain the PC images to the PC sine curves obtained.
Fig. 2 is returned to, next in step 250, to being obtained in the metal BHC images and step 240 that are obtained in step 230
PC images carry out calculation process to obtain prior image.
In one embodiment of the invention, with reference to figure 4, step 250 may further include following sub-step 251 to
255.In sub-step 251, the metal BHC images obtained in step 230 are carried out at full variation processing and gaussian frequency decomposition
Manage to obtain the first high fdrequency component and the first low frequency component.
In sub-step 252, it is high to obtain second that gaussian frequency resolution process is carried out to the PC images obtained in step 240
Frequency component and the second low frequency component.
In sub-step 253, based on first high fdrequency component, first low frequency component, second high fdrequency component
An intermediate variable is obtained with second low frequency component.
In sub-step 254, segmentationization processing is carried out respectively to the PC images and the intermediate variable to obtain first
Image and the second image.
In sub-step 255, described first image is corrected, and second image is applied to the after correction
One image is to obtain the prior image.With continued reference to Fig. 2, next, in step 260, being carried out just to the prior image
To projection to obtain priori sine curve.
Then, in step 270, the priori sine curve is handled to finally give MAR images.
In one embodiment of the invention, with reference to figure 5, step 270 may further include following sub-step 2711 to
2712。
In sub-step 2711, interpolation processing is carried out to the priori sine curve obtained in step 260 and gone at normalization
Manage to obtain adaptively normalizing MAR (ANMAR) sine curve.
In sub-step 2712, back projection is carried out to the ANMAR sine curves to obtain final MAR images.
It should be strongly noted that the realization of above-mentioned steps 270 can also use other manner.Such as the present invention's
In another embodiment, with reference to figure 6, step 270 may further include following sub-step 2721 to 2722.
In sub-step 2721, summation process is weighted to the priori sine curve obtained in step 260 and removes normalizing
Change processing to obtain ANMAR sine curves.Specifically, the process of summation process is being weighted to the priori sine curve
In, from two nearest nonmetallic points of metallic traces described in distance on the priori sine curve, it is weighted summation.
In sub-step 2722, back projection is carried out to the ANMAR sine curves to obtain final MAR images.
So far the method for describing acquisition MAR images according to an exemplary embodiment of the present invention.From comparison illustrated in fig. 8
As a result as can be seen that the MAR images obtained using conventional method, are deposited because not passing through at it in original image of MAR processing
In metal beam hardening artifact, so the white bars significantly as caused by high-density matter be present in continuous prior image behind
Plain shape artifact, therefore the white bars element shape artifact is also remained in its MAR finally obtained image；And use the present invention's
MAR image obtainment methods, because especially having carried out the ray hardened correction of metal to it before its original image is without MAR processing
(BHC), i.e. BHC processing will be carried out and keep the image of low contrast resolution to be used to produce prior image, so behind
White bars element shape artifact is wholly absent as caused by high-density matter in continuous prior image, is correspondingly also eliminated the need for most
The white bars element shape artifact as caused by high-density matter in the MAR images obtained afterwards.Thus, compared with prior art, it is of the invention
MAR image obtainment methods can more significantly reduce metal artifacts in the case where not reducing MAR image resolution ratios, so as to
The quality of CT images is greatly enhanced, is advantageous to doctor and more accurately makes diagnostic result.
Similar with the above method, present invention also offers corresponding device.
Fig. 7 is the schematic block diagram according to an exemplary embodiment of the present invention for being used to obtain the device of MAR images.
As shown in fig. 7, device 800 can include：Original image acquisition module 810, for being carried out to initial sinusoids
Back projection is to obtain original image；Metallic traces acquisition module 820, for obtaining metal mask from the original image, and
Metallic traces are obtained based on the metal mask；Metal BHC modules 830, for entering row metal BHC to the original image to obtain
Metal BHC images；PC image collection modules 840, for obtaining PC images from the metallic traces；Calculation process module 850, use
In carrying out calculation process to the metal BHC images and the PC images to obtain prior image；Priori sine curve obtains mould
Block 860, for carrying out forward projection to the prior image to obtain priori sine curve；And priori sine curve processing mould
Block 870, for being handled the priori sine curve to finally give MAR images.
In one embodiment of the invention, the metallic traces acquisition module 820 to the original image by carrying out
Threshold value is extracted to obtain the metal mask, and then by carrying out forward projection to the metal mask to obtain the gold
Belong to track.
In one embodiment of the invention, the PC image collection modules 840 may further include：PC sine curves
Acquisition module, for obtaining PC sine curves from the metallic traces；With back projection module, for the PC sine curves
Back projection is carried out to obtain the PC images.
In one embodiment of the invention, the calculation process module 850 may further include：Metal BHC images
Processing module, for carrying out full variation processing and gaussian frequency resolution process to the metal BHC images to obtain the first high frequency
Component and the first low frequency component；PC image processing modules, for carrying out gaussian frequency resolution process to the PC images to obtain
Second high fdrequency component and the second low frequency component；Intermediate variable acquisition module, for based on first high fdrequency component, described first
Low frequency component, second high fdrequency component and second low frequency component obtain an intermediate variable；Split module, for institute
State PC images and the intermediate variable and carry out segmentationization processing respectively to obtain the first image and the second image；And prior image
Acquisition module, for being corrected to described first image, and by second image be applied to correction after the first image with
Obtain the prior image.
In one embodiment of the invention, the priori sine curve processing module 870 may further include：It is adaptive
MAR (ANMAR) sine curve acquisition module should be normalized, for carrying out interpolation processing to the priori sine curve and removing normalizing
Change processing to obtain ANMAR sine curves；With MAR image collection modules, for reversely being thrown the ANMAR sine curves
Shadow is to obtain the MAR images.
In another embodiment of the present invention, the priori sine curve processing module 870 may further include：
ANMAR sine curve acquisition modules, for the priori sine curve is weighted summation process and go normalized with
Obtain ANMAR sine curves；With MAR image collection modules, for carrying out back projection to the ANMAR sine curves to obtain
The MAR images.
So far the device of acquisition MAR images according to an exemplary embodiment of the present invention is described.From comparison illustrated in fig. 8
As a result as can be seen that the MAR images obtained using conventional apparatus, are deposited because not passing through at it in original image of MAR processing
In metal beam hardening artifact, so the white bars significantly as caused by high-density matter be present in continuous prior image behind
Plain shape artifact, therefore the white bars element shape artifact is also remained in its MAR finally obtained image；And use the present invention's
MAR image-acquisition devices, because especially having carried out the ray hardened correction of metal to it before its original image is without MAR processing
(BHC), i.e. BHC processing will be carried out and keep the image of low contrast resolution to be used to produce prior image, so behind
White bars element shape artifact is wholly absent as caused by high-density matter in continuous prior image, is correspondingly also eliminated the need for most
The white bars element shape artifact as caused by high-density matter in the MAR images obtained afterwards.Thus, compared with prior art, it is of the invention
MAR image-acquisition devices can more significantly reduce metal artifacts in the case where not reducing MAR image resolution ratios, so as to
The quality of CT images is greatly enhanced, is advantageous to doctor and more accurately makes diagnostic result.
Fig. 9 respectively illustrates the image obtained without MAR, obtains image using the MAR of conventional art and adopt
The image obtained with current MAR according to an exemplary embodiment of the present invention.There it can be seen that after using improvement of the invention
MAR image obtainment methods and device so that obtained in the image that is obtained without MAR and using the MAR of conventional art
High-visible white bars element shape artifact completely eliminates in image.The present inventor is exactly based on X ray physics is special
Property with traditional image repair algorithm carry out unexpected combination, obtained acquisition according to an exemplary embodiment of the present invention
The method and apparatus of MAR images, it greatly enhances the reduction of high-density matter artifact compared with prior art, so as to greatly
Ground improves the quality of CT images, facilitates doctor more accurately to make diagnostic result.
Some exemplary embodiments are described above.It should be understood, however, that various modifications may be made.Example
Such as, if described technology is executed in different order and/or if in described system, framework, equipment or circuit
Component is combined and/or is substituted or supplemented by other component or its equivalent by different way, then can realize suitable knot
Fruit.Correspondingly, other embodiment is also fallen into scope of the claims.
Claims (14)
1. a kind of method for the image (MAR images) for obtaining metal artifacts reduction, comprises the following steps：
Back projection is carried out to initial sinusoids to obtain original image；
Metal mask is obtained from the original image, and metallic traces are obtained based on the metal mask；
Enter the ray hardened correction (BHC) of row metal to the original image to obtain metal BHC images；
Projection, which is obtained, from the metallic traces completes (PC) image；
Calculation process is carried out to obtain prior image to the metal BHC images and the PC images；
Forward projection is carried out to the prior image to obtain priori sine curve；And
The priori sine curve is handled to finally give MAR images.
2. the method as described in claim 1, it is characterised in that computing is carried out to the metal BHC images and the PC images
The step of processing is to obtain prior image further comprises：
Full variation processing and gaussian frequency resolution process are carried out to the metal BHC images to obtain the first high fdrequency component and first
Low frequency component；
Gaussian frequency resolution process is carried out to the PC images to obtain the second high fdrequency component and the second low frequency component；
Based on first high fdrequency component, first low frequency component, second high fdrequency component and second low frequency component
Obtain an intermediate variable；
Segmentationization processing is carried out respectively to the PC images and the intermediate variable to obtain the first image and the second image；And
Described first image is corrected, and second image is applied to the first image after correction to obtain the elder generation
Test image.
3. the method as described in claim 1, it is characterised in that obtaining metal mask from the original image and be based on the gold
In the step of category mask obtains metallic traces, the metal mask is obtained by carrying out threshold value extraction to the original image.
4. method as claimed in claim 3, it is characterised in that by carrying out forward projection to the metal mask to obtain
State metallic traces.
5. the method as described in claim 1, it is characterised in that the step of obtaining PC images from the metallic traces is further wrapped
Include：
PC sine curves are obtained from the metallic traces；With
Back projection is carried out to the PC sine curves to obtain the PC images.
6. the method as described in claim 1, it is characterised in that handled the priori sine curve to finally give
The step of MAR images, further comprises：
Interpolation processing is carried out to the priori sine curve and goes normalized to obtain adaptively normalizing MAR (ANMAR)
Sine curve；With
Back projection is carried out to the ANMAR sine curves to obtain the MAR images.
7. the method as described in claim 1, it is characterised in that handled the priori sine curve to finally give
The step of MAR images, further comprises：
Summation process is weighted to the priori sine curve and goes normalized to obtain ANMAR sine curves；With
Back projection is carried out to the ANMAR sine curves to obtain the MAR images.
8. a kind of device for the image (MAR images) for obtaining metal artifacts reduction, including：
Original image acquisition module, for carrying out back projection to initial sinusoids to obtain original image；
Metallic traces acquisition module, for obtaining metal mask from the original image, and metal is obtained based on the metal mask
Track；
Ray hardened correction (BHC) module of metal, for entering row metal BHC to the original image to obtain metal BHC images；
(PC) image collection module is completed in projection, for obtaining PC images from the metallic traces；
Calculation process module, for carrying out calculation process to the metal BHC images and the PC images to obtain prior image；
Priori sine curve acquisition module, for carrying out forward projection to the prior image to obtain priori sine curve；With
And
Priori sine curve processing module, for being handled the priori sine curve to finally give MAR images.
9. device as claimed in claim 8, it is characterised in that the calculation process module further comprises：
Metal BHC image processing modules, for carrying out full variation processing and gaussian frequency resolution process to the metal BHC images
To obtain the first high fdrequency component and the first low frequency component；
PC image processing modules, for carrying out gaussian frequency resolution process to the PC images to obtain the second high fdrequency component and the
Two low frequency components；
Intermediate variable acquisition module, for based on first high fdrequency component, first low frequency component, the second high frequency division
Amount and second low frequency component obtain an intermediate variable；
Split module, for the PC images and the intermediate variable are carried out respectively segmentationization handle with obtain the first image with
Second image；And
Prior image acquisition module, it is applied to for being corrected to described first image, and by second image after correcting
The first image to obtain the prior image.
10. device as claimed in claim 8, it is characterised in that the metallic traces acquisition module passes through to the original graph
The metal mask is obtained as carrying out threshold value extraction.
11. device as claimed in claim 10, it is characterised in that the metallic traces acquisition module to the metal by covering
Mould carries out forward projection to obtain the metallic traces.
12. device as claimed in claim 8, it is characterised in that the PC image collection modules further comprise：
PC sine curve acquisition modules, for obtaining PC sine curves from the metallic traces；With
Back projection module, for carrying out back projection to the PC sine curves to obtain the PC images.
13. device as claimed in claim 8, it is characterised in that the priori sine curve processing module further comprises：
Adaptive normalization MAR (ANMAR) sine curve acquisition module, for carrying out interpolation processing to the priori sine curve
With normalized is gone to obtain ANMAR sine curves；With
MAR image collection modules, for carrying out back projection to the ANMAR sine curves to obtain the MAR images.
14. device as claimed in claim 8, it is characterised in that the priori sine curve processing module further comprises：
ANMAR sine curve acquisition modules, for being weighted summation process to the priori sine curve and going at normalization
Manage to obtain ANMAR sine curves；With
MAR image collection modules, for carrying out back projection to the ANMAR sine curves to obtain the MAR images.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111524200A (en) * | 2019-02-05 | 2020-08-11 | 西门子医疗有限公司 | Method, apparatus, program and medium for segmenting metal object in projection image |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002067201A1 (en) * | 2001-02-15 | 2002-08-29 | The Regents Of The University Of Michigan | Statistically reconstructing an x-ray computed tomography image with beam hardening corrector |
| US20110007956A1 (en) * | 2009-07-07 | 2011-01-13 | Esther Meyer | Sinogram processing to reduce metal artifacts in computed tomography |
| US20130039556A1 (en) * | 2011-08-10 | 2013-02-14 | Siemens Aktiengesellschaft | Method, computing unit, ct system and c-arm system for reducing metal artifacts in ct image datasets |
| CN103310432A (en) * | 2013-06-25 | 2013-09-18 | 西安电子科技大学 | Computerized Tomography (CT) image uniformization metal artifact correction method based on four-order total-variation shunting |
| CN103617598A (en) * | 2013-11-10 | 2014-03-05 | 北京工业大学 | Track-based CT image metal artifact removing method |
| US20140328450A1 (en) * | 2013-05-02 | 2014-11-06 | General Electric Company | System and method for reducing high density artifacts in computed tomography imaging |
| CN104504655A (en) * | 2014-12-04 | 2015-04-08 | 沈阳东软医疗系统有限公司 | CT (computer tomography) metal artifact processing method and device |
| CN104517263A (en) * | 2013-09-30 | 2015-04-15 | Ge医疗系统环球技术有限公司 | Artifact reducing method and device for CT (computed tomography) image reconstruction |
| CN104644200A (en) * | 2013-11-25 | 2015-05-27 | Ge医疗系统环球技术有限公司 | Method and device for reducing artifacts in computed tomography image reconstruction |
| JP2015156966A (en) * | 2014-02-24 | 2015-09-03 | 株式会社テレシステムズ | Dental x-ray imaging apparatus and image correction method |
-
2016
- 2016-08-11 CN CN201610655886.2A patent/CN107730455B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002067201A1 (en) * | 2001-02-15 | 2002-08-29 | The Regents Of The University Of Michigan | Statistically reconstructing an x-ray computed tomography image with beam hardening corrector |
| US20110007956A1 (en) * | 2009-07-07 | 2011-01-13 | Esther Meyer | Sinogram processing to reduce metal artifacts in computed tomography |
| US20130039556A1 (en) * | 2011-08-10 | 2013-02-14 | Siemens Aktiengesellschaft | Method, computing unit, ct system and c-arm system for reducing metal artifacts in ct image datasets |
| CN103190928A (en) * | 2011-08-10 | 2013-07-10 | 西门子公司 | Method, computing unit, CT system and C-arm system for reducing metal artifacts |
| US20140328450A1 (en) * | 2013-05-02 | 2014-11-06 | General Electric Company | System and method for reducing high density artifacts in computed tomography imaging |
| CN103310432A (en) * | 2013-06-25 | 2013-09-18 | 西安电子科技大学 | Computerized Tomography (CT) image uniformization metal artifact correction method based on four-order total-variation shunting |
| CN104517263A (en) * | 2013-09-30 | 2015-04-15 | Ge医疗系统环球技术有限公司 | Artifact reducing method and device for CT (computed tomography) image reconstruction |
| CN103617598A (en) * | 2013-11-10 | 2014-03-05 | 北京工业大学 | Track-based CT image metal artifact removing method |
| CN104644200A (en) * | 2013-11-25 | 2015-05-27 | Ge医疗系统环球技术有限公司 | Method and device for reducing artifacts in computed tomography image reconstruction |
| JP2015156966A (en) * | 2014-02-24 | 2015-09-03 | 株式会社テレシステムズ | Dental x-ray imaging apparatus and image correction method |
| CN104504655A (en) * | 2014-12-04 | 2015-04-08 | 沈阳东软医疗系统有限公司 | CT (computer tomography) metal artifact processing method and device |
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| CN111524200A (en) * | 2019-02-05 | 2020-08-11 | 西门子医疗有限公司 | Method, apparatus, program and medium for segmenting metal object in projection image |
| CN111524200B (en) * | 2019-02-05 | 2024-03-22 | 西门子医疗有限公司 | Method, apparatus and medium for segmenting a metal object in a projection image |
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