CN106256327B - A kind of cone beam computed tomography (CT) scattering correction system and bearing calibration based on big data - Google Patents
A kind of cone beam computed tomography (CT) scattering correction system and bearing calibration based on big data Download PDFInfo
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Abstract
The invention discloses a kind of, and the cone beam computed tomography (CT) scattering based on big data corrects system, including cone-beam CT system and computer system；Also disclose a kind of cone beam CT scatter correction method based on big data, it is achieved by correcting system as previously described, using cloud computing, cloud storage technology, it constructs the local scattering data library being mutually in step and disperses like the clouds and penetrate database, it forms patient and checks data, the big data of scattering data, during reconstruction, it will be closest to the scattering data of measurand, adjustment estimation scatter projection contribution is calculated by two dimension appropriate, under the premise of data volume is sufficient, the lesser scattering estimation of error can be provided, to make Cone-Beam CT quickly obtain more accurate reconstructed results.
Description
Technical field
The present invention relates to a kind of cone beam computed tomography (CT) scattering correction system and bearing calibration based on big data, belong to Cone-Beam CT detection
Technical field.
Background technique
Cone-Beam CT causes X-ray exposure area ratio fan beam CT much larger because axial covering increases, and scattering ingredient exists
The contribution in gross energy that detector detects is very big, causes scatter artefacts, contrast reduction, image detail reduction, CT value not
The problems such as accurate, finally reduces picture quality.Therefore, Cone-Beam CT is usually adopted is scattered correction in many ways.Scatter correction
Target be the effect in correction, dosage, in terms of meet user application the needs of.
Commonly scatter correction method includes:
1, the air gap method: because scattering be not along light source to detector line, increase object and detector
Distance can make partial dispersion line not can enter detector region.
The shortcomings that the method is that bigger detector is needed when compared to other methods to same image objects.
2, anti-scattered grid method: anti-scattered grid are made of a series of spaced thin slices strong to X-ray attenuation.It can allow beam direction
Ray pass through, and to deviate beam direction ray effectively decayed, thus reduce scattered rays be detected probability.It is anti-
Scattered grid are divided into one-dimensional anti-scattered grid and the anti-scattered grid of two dimension.
The shortcomings that the method is, because strong attenuating material causes part to stop beam, to reduce dose utilization.
3, bowknot compensator: the original intention that bowknot compensator is selected in CT system is to receive detector cells
Amount of x-ray it is identical, to make up the problem of detector dynamic range deficiency.The use of bowknot compensator can also bring other good
Place, as radiation dosage of patient reduction, scatter ingredient reduction.
The shortcomings that the method is that bowknot compensator reduces partial dispersion, but also brings the scattering of itself；In addition butterfly
If it is bad to tie compensator design, it is also possible to introduce new artifact.
4, projection pre-procession method:
Simplest method is homogenous diffusion sampling becomes point-score (Uniform Scatter Fraction), according in projection most
The size direct estimation scattered quantum of subtotal figure and object, then removes from projection.The method of another projection pre-procession is
Scatter kernel method (Scatter Kernel Method), by object it is equivalent by equal centers, be parallel to the plane of detector,
By counting scattering ingredient with the convolution of scattering nucleus, then deducted from projection.
5, iterative method:
The method is first based on original projection and rebuilds object, is passing through analytic method (convolution kernel) or Monte-carlo Simulation Method
Contribution of the scattering to projection is obtained, then after deducting scattering influence in original projection, rebuilds object.
The method of the method, especially Monte Carlo simulation, the disadvantage is that calculating overlong time.But with changing for computing platform
The kind especially application of video processing board-card (GPU) and the simplification and optimization of algorithm, it is believed that have in the near future more and more
Practical application.
6, wire-blocking board method:
In addition to normal projection acquisition, the method will also additionally carry out the acquisition of a sub-band wire-blocking board, and wire-blocking board has dotted
(static or movement) is two kinds linear.The region of wire-blocking board is divided into two kinds, and one is X-rays to pass freely through region, this kind
Region accounts for relatively high；Another is the highly attenuating region of X-ray；The X-ray of direct projection can not substantially penetrate highly attenuating region
Into detector, therefore the X-ray that the corresponding detector pixel in highly attenuating region detects, it is the contribution of scattered rays.Consider
To the slow spatial variations of scattering ingredient, the scattering that can be obtained according to highly attenuating region measurement, interpolation, extrapolation obtain all areas
Contribution of scatters.Contribution of scatters is subtracted in the projection of normal acquisition, the perspective view of no scattering can be obtained.
The shortcomings that the method, is that additional single pass increases the radioactive dose of patient, simultaneously as mobile presence, it can
Correction artifact can be introduced.
Summary of the invention
Therefore, the purpose of the present invention is to overcome the defects in the prior art, and providing one kind quickly can accurately be weighed
Build the cone beam computed tomography (CT) scattering correction system and bearing calibration based on big data of result.
To achieve the goals above, a kind of cone beam computed tomography (CT) scattering based on big data of the invention corrects system, comprising:
Cone-beam CT system is connected with computer system, the original projection for being tested position for acquiring patient, and will collect
Original projection be sent to computer system；
Computer system, including scattering data library be used for store several patient informations and tested position appearance information and its
Corresponding scattering data；The appearance information at the computer system, patient information for receiving input and tested position and
The original projection for receiving the cone-beam CT system acquisition, for the appearance information according to the patient information and tested position received
Similar scattering data is transferred in scattering data library, for forming each projected angle after being adjusted to the scattering data being deployed into
Scatter projection contribution under degree is used for carrying out rudimentary model reconstruction after subtracting the scatter projection contribution in original projection
Accurate model reconstruction is carried out in iterative method of the use based on monte carlo method and calculates corresponding scattering data, and to calculating
Scattering data out carries out storage to update scattering data library.
The computer system includes local computer and Cloud Server, and the local computer is connected to ... through the network
The Cloud Server, the local computer include local scattering data library, and the Cloud Server includes dispersing like the clouds to penetrate database.
The cone-beam CT system includes x-ray focus and flat panel detector, and measurand is in x-ray focus and plate is visited
It surveys between device, intrinsic filter, preceding collimator and bowknot compensation is set gradually between the x-ray focus and measurand
Anti-scattered grid are arranged in device between measurand and flat panel detector.
A kind of cone beam CT scatter correction method based on big data, is achieved by correcting system as previously described, packet
Include following steps:
1) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
2) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
3) similar scattering data is transferred in scattering data library according to the appearance information at patient information and tested position, it is right
The scattering data being deployed into forms the contribution of the scatter projection under each projection angle after being adjusted；
4) rudimentary model reconstruction is carried out after subtracting the scatter projection contribution in original projection；
5) accurate model reconstruction is carried out using the iterative method based on monte carlo method and calculates corresponding scattering data；
6) storage is carried out to update scattering data library to calculated scattering data.
A kind of cone beam CT scatter correction method based on big data, is achieved by correcting system as previously described, packet
Include following steps:
11) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
12) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
13) local computer transfers phase in local scattering data library according to the appearance information at patient information and tested position
Close scattering data forms the scatter projection contribution under each projection angle after being adjusted to the scattering data being deployed into；
14) local computer carries out rudimentary model reconstruction after subtracting the scatter projection contribution in original projection；
15) patient information of measurand, the appearance information at tested position and Raw projection data are sent to cloud service
Device；
16) Cloud Server carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates corresponding
Scattering data；
17) Cloud Server carries out storage to calculated scattering data and penetrates database to update to disperse like the clouds；
18) the calculated scattering data of Cloud Server and storage is carried out to update this in local computer download step 17
Ground scattering data library.
There are also following steps before the step 15:
151) local computer judges whether with Cloud Server through network-in-dialing, if it is judged that be it is yes, then enter
Step 15；If it is judged that be it is no, then enter step 152；
152) local computer carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates pair
The scattering data answered；
153) local computer carries out storage to calculated scattering data to update local scattering data library, and at this
Calculated scattering data is uploaded to Cloud Server after the network-in-dialing of ground computer and Cloud Server and carries out storage to more
It newly disperses like the clouds and penetrates database.
The patient information includes nationality, native place, surname, age, weight and the height of patient.
In the step 11, the appearance information at the tested position by positioning picture or camera acquisition measurand.
In the step 13, the adjustment to the scattering data being deployed into includes translation, rotation, scaling and interpolation.
By adopting the above technical scheme, in the cone beam computed tomography (CT) scattering correction system and bearing calibration of the invention based on big data,
Using cloud computing, cloud storage technology, constructs the local scattering data library being mutually in step and disperse like the clouds and penetrate database, form patient and inspection
Data, the big data of scattering data are looked into, during reconstruction, by closest to the scattering data of measurand, by appropriate
Two dimension calculate adjustment estimation scatter projection contribution and can provide the lesser scattering of error under the premise of data volume is sufficient and estimate,
To make Cone-Beam CT quickly obtain more accurate reconstructed results.
Detailed description of the invention
Fig. 1 is the structural representation of the cone-beam CT system in the cone beam computed tomography (CT) scattering correction system of the invention based on big data
Figure；
Fig. 2 is the schematic diagram of the network architecture in the cone beam computed tomography (CT) scattering correction system of the invention based on big data.
Specific embodiment
Below by way of the drawings and specific embodiments, the present invention is described in further detail.
As shown, the present embodiment provides a kind of, the cone beam computed tomography (CT) scattering based on big data corrects system, including is connected with each other
Cone-beam CT system and local computer, wherein cone-beam CT system includes x-ray focus 1 and flat panel detector 7, measurand again
5 in set gradually between x-ray focus 1 and flat panel detector 7, between x-ray focus and measurand intrinsic filter 2,
Anti-scattered grid 6 are arranged in preceding collimator 3 and bowknot compensator 4 between measurand and flat panel detector；The specifications parameter of anti-scattered grid
It is calculated using monte carlo method simulation；The local of cone-beam CT system is arranged in local computer, is arrived by network connection
Communication server, communication server are connected to the Cloud Server of distal end, and Cloud Server includes cloud computing server and cloud storage clothes
Business device is connected, and local scattering data library is arranged on local computer, and setting, which disperses like the clouds, on cloud storage service device penetrates database, above-mentioned
Scattering data in scattering data library be collected in different patients and according to the appearance information at different patient informations and tested position and its
Corresponding scattering data and store.
The cone-beam CT system, the original projection for being tested position for acquiring patient, and collected original projection is sent out
It send to computer system；
The appearance information and the reception cone-beam at computer system, patient information for receiving input and tested position
The original projection of CT system acquisition, for according to the appearance information of patient information and tested position received in scattering data library
In transfer similar scattering data, scattering for being formed under each projection angle after being adjusted to the scattering data being deployed into is thrown
Shadow contribution carries out rudimentary model reconstruction for being subtracted after the scatter projection is contributed in original projection, for using based on illiteracy
The iterative method of special Carlow method carries out accurate model reconstruction and calculates corresponding scattering data, and to calculated scattering data
Storage is carried out to update scattering data library.
The present invention also provides a kind of cone beam CT scatter correction methods based on big data, by correcting system as previously described
It is achieved, comprising the following steps:
1) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
2) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
3) similar scattering data is transferred in scattering data library according to the appearance information at patient information and tested position, it is right
The scattering data being deployed into forms the contribution of the scatter projection under each projection angle after being adjusted；
4) rudimentary model reconstruction is carried out after subtracting the scatter projection contribution in original projection；
5) accurate model reconstruction is carried out using the iterative method based on monte carlo method and calculates corresponding scattering data；
6) storage is carried out to update scattering data library to calculated scattering data.
Cone beam CT scatter correction method the present invention also provides another kind based on big data is by correcting as previously described
System is achieved, comprising the following steps:
11) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
12) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
13) local computer transfers phase in local scattering data library according to the appearance information at patient information and tested position
Close scattering data forms the scatter projection contribution under each projection angle after being adjusted to the scattering data being deployed into；
14) local computer carries out rudimentary model reconstruction after subtracting the scatter projection contribution in original projection；
15) patient information of measurand, the appearance information at tested position and Raw projection data are sent to cloud service
Device；
16) Cloud Server carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates corresponding
Scattering data；
17) Cloud Server carries out storage to calculated scattering data and penetrates database to update to disperse like the clouds；
18) the calculated scattering data of Cloud Server and storage is carried out to update this in local computer download step 17
Ground scattering data library.
There are also following steps before the step 15:
151) local computer judges whether with Cloud Server through network-in-dialing, if it is judged that be it is yes, then enter
Step 15；If it is judged that be it is no, then enter step 152；
152) local computer carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates pair
The scattering data answered；
153) local computer carries out storage to calculated scattering data to update local scattering data library, and at this
Calculated scattering data is uploaded to Cloud Server after the network-in-dialing of ground computer and Cloud Server and carries out storage to more
It newly disperses like the clouds and penetrates database, so that local and cloud scattering data library keeps synchronized update, constantly to expand in scattering data library
Data volume improve the precision of reconstructed results to adapt to different patients.
The patient information includes nationality, native place, surname, age, weight and the height of patient.The patient information of offer is got over
To be detailed, the dimension of reference is more, the actual state of the scattering data and measurand that are finally matched to just more close to.
In the step 11, the appearance information at the tested position by positioning picture or camera acquisition measurand, on
State two kinds of optional one of acquisition mode.
In the step 13, the adjustment to the scattering data being deployed into includes translation, rotation, scaling and interpolation.Specifically
Adjustment mode chosen according to actual application situation.
By adopting the above technical scheme, in the cone beam computed tomography (CT) scattering correction system and bearing calibration of the invention based on big data,
Using cloud computing, cloud storage technology, constructs the local scattering data library being mutually in step and disperse like the clouds and penetrate database, form patient and inspection
Data, the big data of scattering data are looked into, during reconstruction, by closest to the scattering data of measurand, by appropriate
Two dimension calculate adjustment estimation scatter projection contribution and can provide the lesser scattering of error under the premise of data volume is sufficient and estimate,
To make Cone-Beam CT quickly obtain more accurate reconstructed results.
Obviously, above-described embodiment is only intended to clearly illustrate example, and does not limit the embodiments.For
For those of ordinary skill in the art, other various forms of variations or change can also be made on the basis of the above description
It is dynamic.There is no necessity and possibility to exhaust all the enbodiments.And obvious variation extended from this or change
It moves still within the protection scope of the invention.
Claims (9)
1. a kind of cone beam computed tomography (CT) scattering based on big data corrects system characterized by comprising
Cone-beam CT system is connected with computer system, the original projection for being tested position for acquiring patient, and by collected original
Begin to project and is sent to computer system；
Computer system is used to store the appearance information and its correspondence at several patient informations and tested position including scattering data library
Scattering data；The appearance information and reception at the computer system, patient information for receiving input and tested position
The original projection of the cone-beam CT system acquisition, for being dissipated according to the appearance information of the patient information and tested position received
It penetrates in database and transfers similar scattering data, for being formed under each projection angle after being adjusted to the scattering data being deployed into
Scatter projection contribution, for carrying out rudimentary model reconstruction after subtracting scatter projection contribution in original projection, for adopting
Accurate model reconstruction is carried out with the iterative method based on monte carlo method and calculates corresponding scattering data, and to calculated
Scattering data carries out storage to update scattering data library.
2. the cone beam computed tomography (CT) scattering based on big data corrects system as described in claim 1, which is characterized in that the department of computer science
System includes local computer and Cloud Server, and the local computer is connected to ... through the network the Cloud Server, and described
Ground computer includes local scattering data library, and the Cloud Server includes dispersing like the clouds to penetrate database.
3. the cone beam computed tomography (CT) scattering based on big data corrects system as claimed in claim 1 or 2, which is characterized in that the cone-beam
CT system includes x-ray focus and flat panel detector, and measurand is between x-ray focus and flat panel detector, and the X is penetrated
Intrinsic filter, preceding collimator and bowknot compensator, measurand and plate are set gradually between line focus and measurand
Anti-scattered grid are set between detector.
4. a kind of cone beam CT scatter correction method based on big data, which is characterized in that by correcting as described in claim 1
System is achieved, comprising the following steps:
1) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
2) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
3) similar scattering data is transferred in scattering data library according to the appearance information at patient information and tested position, to transferring
To scattering data be adjusted after formed under each projection angle scatter projection contribution；
4) rudimentary model reconstruction is carried out after subtracting the scatter projection contribution in original projection；
5) accurate model reconstruction is carried out using the iterative method based on monte carlo method and calculates corresponding scattering data；
6) storage is carried out to update scattering data library to calculated scattering data.
5. a kind of cone beam CT scatter correction method based on big data, which is characterized in that by correcting as claimed in claim 2
System is achieved, comprising the following steps:
11) patient information for collecting measurand and the patient for acquiring measurand are tested the appearance information at position；
12) position is tested by patient of the cone-beam CT system to measurand and carries out tomoscan to obtain original projection；
13) local computer is transferred in local scattering data library similar according to the appearance information at patient information and tested position
Scattering data forms the scatter projection contribution under each projection angle after being adjusted to the scattering data being deployed into；
14) local computer carries out rudimentary model reconstruction after subtracting the scatter projection contribution in original projection；
15) patient information of measurand, the appearance information at tested position and Raw projection data are sent to Cloud Server；
16) Cloud Server carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates corresponding scattering
Data；
17) Cloud Server carries out storage to calculated scattering data and penetrates database to update to disperse like the clouds；
18) the calculated scattering data of Cloud Server and storage is carried out to update local dissipate in local computer download step 17
Penetrate database.
6. as claimed in claim 5 based on the cone beam CT scatter correction method of big data, which is characterized in that in the step 15
There are also following steps before:
151) local computer judges whether with Cloud Server through network-in-dialing, if it is judged that be it is yes, then enter step
15；If it is judged that be it is no, then enter step 152；
152) local computer carries out accurate model reconstruction using the iterative method based on monte carlo method and calculates corresponding
Scattering data；
153) local computer carries out storage to calculated scattering data to update local scattering data library, and in local meter
Calculated scattering data is uploaded to Cloud Server after the network-in-dialing of calculation machine and Cloud Server and carries out storage to update cloud
Scattering data library.
7. such as the cone beam CT scatter correction method described in claim 5 or 6 based on big data, which is characterized in that the patient
Information includes nationality, native place, surname, age, weight and the height of patient.
8. such as the cone beam CT scatter correction method described in claim 5 or 6 based on big data, which is characterized in that in the step
In rapid 11, the appearance information at the tested position by positioning picture or camera acquisition measurand.
9. such as the cone beam CT scatter correction method described in claim 5 or 6 based on big data, which is characterized in that in the step
In rapid 13, the adjustment to the scattering data being deployed into includes translation, rotation, scaling and interpolation.
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| CN109191541B (en) * | 2018-08-06 | 2023-08-25 | 沈阳晟诺科技有限公司 | CT remote image reconstruction method |
| CN109389654B (en) * | 2018-09-30 | 2022-11-18 | 上海联影医疗科技股份有限公司 | CT data reconstruction method, device, equipment and storage medium |
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| US8144829B2 (en) * | 2008-02-27 | 2012-03-27 | The Board Of Trustees Of The Leland Stanford Junior University | Cone-beam CT imaging scheme |
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