CN106821380A - Biomedical electrical impedance imaging method and device based on the regularization of multiplying property - Google Patents
Biomedical electrical impedance imaging method and device based on the regularization of multiplying property Download PDFInfo
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- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
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Abstract
The invention discloses a kind of biomedical electrical impedance imaging method and device based on the regularization of multiplying property, wherein method includes：Multiple electrodes are arranged around object to be imaged, and in measurement process, two electrodes in turn in constant current drive multiple electrodes simultaneously measure the potential difference on other electrodes in multiple electrodes, to obtain a frame measurement data；The data error of electrical impedance imaging problem is calculated according to measurement data and Forward simulation data, and cost functional is calculated according to default multiplying property regular terms and data error term；By alternative manner minimization cost functional carrying out image reconstruction.The method can well retain the edge configuration of organism organ, reconstruction image is had " piecemeal constant " characteristic, and with good noise robustness.
Description
Technical field
The present invention relates to biomedical Review of Electrical Impedance Tomography field, more particularly to a kind of biology based on the regularization of multiplying property
Medical Electrical Impedance Tomography method and apparatus.
Background technology
With the progress of science and technology, Medical Imaging Technology achieves significant progress.These technologies are by by certain
Energy extracts the letter of form, structure and some physiological functions of biological in-vivo tissue or organ with the interaction of organism
Breath, is that biological fabric study and clinical diagnosis provide image information, for example, x-ray imaging, ultrasonic imaging, magnetic resonance imaging, red
The Medical Imaging Technologies such as outer line imaging, radionuclide imaging, optical imagery, electrical impedance tomography.Wherein, electrical impedance tomography
Imaging (Electrical Impedance Tomography, English abbreviation：EIT) it is then a kind of electricity using detected object
The technology that impedance operator is imaged.The technology has light temporal resolution high, low cost, equipment, non-intruding, radiationless etc.
Advantage, therefore be a technology with attractive prospect.
However, when rebuilding biological in-vivo tissue or organ morphology image using Review of Electrical Impedance Tomography in actual applications,
Because the measurement data for obtaining is limited, and the unknown quantity number for needing inverting is typically less than, therefore image reconstruction problem often has
There are serious pathosis.In order to improve this pathosis, in the related art, regularization generally is carried out to problem.Wherein, canonical
Change method is varied, for example Tikhonov regularizations, full variation (Total Variation) regularization etc..
Although however, traditional regularization method can improve the pathosis of Problems of Reconstruction, still having several drawbacks.
For example, Tikhonov regularizations cause that the border of organism organ is excessively smooth；Original full variation regular terms does not have can be micro-
Property, therefore, it is difficult to carry out image reconstruction using Newton-like method.
In addition, traditional additivity regularization mode needs to set a parameter in cost functional to adjust data error
With the relative weighting of regular terms.However, the parameter value needs to determine by quite cumbersome numerical experiment, this considerably increases
The computation complexity of imaging algorithm.
The content of the invention
The purpose of the present invention is intended at least solve one of above-mentioned technical problem to a certain extent.
Therefore, first purpose of the invention is to propose a kind of biomedical electrical impedance imaging based on the regularization of multiplying property
Method.The method can well retain the edge configuration of organism organ, reconstruction image is had " piecemeal constant " characteristic, and
And with good noise robustness.
Second object of the present invention is to propose a kind of biomedical electrical impedance imaging device based on the regularization of multiplying property.
To achieve these goals, the biomedical electrical impedance based on the regularization of multiplying property of first aspect present invention embodiment
Imaging method, comprises the following steps：Multiple electrodes are arranged around object to be imaged, and in measurement process, constant current in turn swashs
Encourage two electrodes in the multiple electrode and measure the potential difference on other electrodes in the multiple electrode, to obtain a frame
Measurement data；According to the measurement data and the data error of Forward simulation data calculating electrical impedance imaging problem, and according to
Default multiplying property regular terms and the data error calculate cost functional；By cost functional described in alternative manner minimization with
Carry out image reconstruction.
The biomedical electrical impedance imaging method based on the regularization of multiplying property of the embodiment of the present invention, by using constant-current source wheel
Two electrodes in flowing to multiple electrodes enter row energization and measure, and obtain measurement data, and according to measurement data and forward direction
Emulation data calculate the data error of electrical impedance imaging problem, and mesh is calculated according to default multiplying property regular terms and data error term
Mark functional, and then by alternative manner minimization cost functional to carry out image reconstruction, so as to retain organism organ well
Edge configuration, make reconstruction image that there is " piecemeal constant " characteristic, and with good noise robustness.
To achieve these goals, the biomedical electrical impedance based on the regularization of multiplying property of second aspect present invention embodiment
Imaging device, including：Measurement module, it is permanent in turn for arranging multiple electrodes around object to be imaged, and in measurement process
Stream encourages two electrodes in the multiple electrode and measures the potential difference on other electrodes in the multiple electrode, to obtain
One frame measurement data；Computing module, for calculating electrical impedance imaging problem according to the measurement data and Forward simulation data
Data error, and cost functional is calculated according to default multiplying property regular terms and the data error；Image reconstruction module, uses
In by cost functional described in alternative manner minimization carrying out image reconstruction.
The biomedical electrical impedance imaging device based on the regularization of multiplying property of the embodiment of the present invention, by using constant-current source wheel
Two electrodes in flowing to multiple electrodes enter row energization and measure, and obtain measurement data, and according to measurement data and forward direction
Emulation data calculate the data error of electrical impedance imaging problem, and mesh is calculated according to default multiplying property regular terms and data error term
Mark functional, and then by alternative manner minimization cost functional to carry out image reconstruction, so as to retain organism organ well
Edge configuration, make reconstruction image that there is " piecemeal constant " characteristic, and with good noise robustness.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partly become from the following description
Obtain substantially, or recognized by practice of the invention.
Brief description of the drawings
The above-mentioned and/or additional aspect of the present invention and advantage will become from the following description of the accompanying drawings of embodiments
Substantially and be readily appreciated that, wherein,
Fig. 1 is the flow of the biomedical electrical impedance imaging method based on the regularization of multiplying property according to embodiments of the present invention
Figure；
Fig. 2 is the imitative of the structure of the biomedical electrical impedance imaging method based on the regularization of multiplying property according to embodiments of the present invention
True mode exemplary plot；
Image reconstruction result schematic diagram when Fig. 3 (a) is the noiseless of the embodiment of the present invention；
Image reconstruction result schematic diagram when Fig. 3 (b) is an applying noise of the embodiment of the present invention；
Image reconstruction result schematic diagram when Fig. 3 (c) is another applying noise of the embodiment of the present invention；
Fig. 4 is that the structure of the biomedical electrical impedance imaging device based on the regularization of multiplying property according to embodiments of the present invention is shown
It is intended to.
Specific embodiment
Embodiments of the invention are described below in detail, the example of the embodiment is shown in the drawings, wherein from start to finish
Same or similar label represents same or similar element or the element with same or like function.Below with reference to attached
It is exemplary to scheme the embodiment of description, it is intended to for explaining the present invention, and be not considered as limiting the invention.
Below with reference to the accompanying drawings biomedical electrical impedance imaging based on the regularization of multiplying property according to embodiments of the present invention is described
Method and apparatus.
Fig. 1 is the flow of the biomedical electrical impedance imaging method based on the regularization of multiplying property according to embodiments of the present invention
Figure.As shown in figure 1, the biomedical electrical impedance imaging method that should be based on the regularization of multiplying property can include：
S101, arranges multiple electrodes around object to be imaged, and in measurement process, in turn constant current drive multiple electrodes
In two electrodes and measure the potential difference on other electrodes in multiple electrodes, to obtain a frame measurement data.
Specifically, in order to obtain the reconstruction image of object to be imaged, multiple electrodes can be arranged around object to be imaged,
And in measurement process, with two electrodes in constant current drive multiple electrodes and measure on other electrodes in multiple electrodes in turn
Potential difference, to obtain a frame measurement data.It is illustrated below：
Assuming that multiple electrodes are arranged around torso model, in measurement process, to the two of which in multiple electrodes
Electrode adds constant current drive and measures the potential difference of other electrodes, while constantly changing the position of exciting electrode and being surveyed accordingly
Amount, finally obtains a frame measurement data, can be designated as a vector m.
Wherein, the multiple electrodes in the present embodiment can be 16, or other numbers, it not limited herein
It is fixed.
It should be noted that in the present embodiment, in addition to can be in the thoracic cavity of human body arrangement multiple electrodes, can be with
Multiple electrodes are arranged in the brain of human body, the position of specific arrangement can be arranged in human body corresponding site according to actual needs,
The position not to multiple electrodes is specifically limited herein.
Further, in the present embodiment, for the constant current drive for determining, the Potential distribution in object to be imaged needs full
The following Poisson's equation of foot and boundary condition：
At border Top electrode l (2)
On border elsewhere (3)
Wherein, φ is the Potential distribution in the object to be imaged, and σ is its distribution of conductivity, IlIt is the electricity by electrode l
Stream, n is border normal direction, and r is space coordinates.Above-mentioned partial differential equation can be solved by FInite Element, and then can be in the hope of
Obtain the potential difference of border Top electrode.
S102, according to measurement data and the data error of Forward simulation data calculating electrical impedance imaging problem, and according to
Default multiplying property regular terms and data error term calculate cost functional.
Specifically, after measurement data is obtained, electricity can be calculated by the way that Forward simulation data and measurement data are subtracted each other
The data error of impedance imaging problem.
Wherein, the data error of electrical impedance imaging problem can be calculated by below equation and obtained：
Data error item=| | S (σ)-m | |2 (4)
Wherein, to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is measurement data.
And then, cost functional can be calculated according to default multiplying property regular terms and data error term.
It should be noted that in the present embodiment, default multiplying property regular terms is set based on full variation principle, should
Multiplying property regular terms may include various forms, such as L2Norm regular terms, weighting L2Norm regular terms etc..
Wherein, process is implemented according to what default multiplying property regular terms and data error term calculated cost functional, can be wrapped
Include following steps：
Data error is carried out into multiplication calculating with the multiplying property regular terms based on full variation principle, to obtain cost functional.
The calculating of cost functional can be realized by equation below：
Cn(σ)=| | S (σ)-m | |2×Rn(σ) (5)
Wherein, Cn(σ) is cost functional, and to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is
Measurement data, Rn(σ) is multiplying property regular terms, and n is iterations.
S103, by alternative manner minimization cost functional carrying out image reconstruction.
Specifically, carrying out minimization to cost functional can be accomplished in several ways.For example, steepest descent method, Gauss-
Newton method, conjugate gradient method etc..Certainly there are other alternative manners, it is not repeated herein.
Minimization cost functional is described in detail by taking Gauss-Newton method as an example below.
First, the gradient vector g of cost functional is solvedn(σ) and Hessian matrix Gn(σ), can specifically be written as respectively：
Wherein,It is the gradient vector of multiplying property regular terms,It is the Hessian matrix of multiplying property regular terms, J (σ) is
Jacobian matrix, to treat the discrete electrical conductivity of inverting, S () is the forward direction operator of the solution direct problem of discretization to σ, and m is measurement number
According to n is iterations.
It should be noted that above-mentioned Jacobian matrix can quickly be obtained by formula (8)：
Wherein, Ω is problem solving region, φiThe Potential distribution produced in the Ω of region during for i-th pair electrode excitation, uj
It is the Potential distribution produced in the Ω of region when jth is to electrode excitation, δ σ (e) is the characteristic function of unit e.
Secondly, treat that inverting electrical conductivity can be updated by the following direction of search：
Δσn=-[Gn]-1·gn (9)
Wherein, gnIt is the gradient vector of cost functional, GnIt is the Hessian matrix of cost functional.
And then, by above-mentioned alternative manner minimization cost functional after, can obtain the reconstruction image of object to be imaged.
A simulation model is also constructed in order to carry out performance verification to above-mentioned method for reconstructing, in the embodiment of the present invention, its
Finite element fission is as shown in Figure 2.Background conductance rate is 0.25S/m in the model, and semicircular electricity is included with sharp edges
Conductance is 0.1S/m, and 16 around model round dot represents electrode.Can be produced using finite element model for solving direct problem by the model
Raw simulated measurement data, and then the performance of above-mentioned method for reconstructing can be verified according to the simulated measurement data for producing.
Further, imaging object can be treated under different noise levels by above-mentioned simulation model carries out image weight
Build.For details, reference can be made to Fig. 3 (a)-Fig. 3 (c).Wherein, Fig. 3 (a) is simulated measurement data without image weight when applying noise
Build result schematic diagram；Fig. 3 (b) is image reconstruction result schematic diagram of the simulated measurement data when 1% noise is applied with；Fig. 3 (c)
For simulated measurement data when 2% noise is applied with image reconstruction result schematic diagram.Wherein, the image in Fig. 3 (a)-Fig. 3 (c)
Reconstruction has used the grids different from Fig. 2.
Based on the above-mentioned image reconstruction example for treating imaging object under different noise levels, it can be seen that simulation model
The edge of inclusion can clearly be rebuild, and the image rebuild has " piecemeal constant " characteristic, also, to simulated measurement
When data applying noise level is of a relatively high, such as 2%, the edge of image also can preferably be rebuild, therefore the explanation present invention
The biomedical electrical impedance imaging method based on the regularization of multiplying property in embodiment has good noiseproof feature.
To sum up, the biomedical electrical impedance imaging method based on the regularization of multiplying property of the embodiment of the present invention, by using perseverance
Stream source in turn to multiple electrodes in two electrodes enter row energization and measure, obtain measurement data, and according to measurement data
With the data error that Forward simulation data calculate electrical impedance imaging problem, according to default multiplying property regular terms and data error term
Cost functional is calculated, and then by alternative manner minimization cost functional to carry out image reconstruction, so as to retain well biological
The edge configuration of body organ, makes reconstruction image have " piecemeal constant " characteristic, and with good noise robustness.In addition,
For compared to additivity regularization mode, multiplying property regularization mode disclosed in this invention in cost functional without setting one
Parameter adjusts the relative weighting of data error and regular terms, because the data error during minimization cost functional
Relative weighting with regular terms can be adjusted dynamically, eliminate by quite cumbersome numerical experiment to determine the step of the parameter value
Suddenly.
In order to realize above-described embodiment, the invention allows for a kind of biomedical electrical impedance based on the regularization of multiplying property into
As device.
Fig. 4 is that the structure of the biomedical electrical impedance imaging device based on the regularization of multiplying property according to embodiments of the present invention is shown
It is intended to.
As shown in figure 4, the biomedical electrical impedance imaging device that should be based on the regularization of multiplying property may include：Measurement module 110,
Computing module 120 and image reconstruction module 130.
Wherein, measurement module 110 is used to arrange multiple electrodes around object to be imaged, and in measurement process, in turn
Two electrodes in constant current drive multiple electrodes simultaneously measure the potential difference on other electrodes in multiple electrodes, to obtain frame survey
Amount data.
Specifically, in order to obtain the reconstruction image of object to be imaged, multiple electrodes can be arranged around object to be imaged,
And in measurement process, with two electrodes in constant current drive multiple electrodes and measure on other electrodes in multiple electrodes in turn
Potential difference, to obtain a frame measurement data.It is illustrated below：
Assuming that multiple electrodes are arranged around torso model, in measurement process, to the two of which in multiple electrodes
Electrode adds constant current drive and measures the potential difference of other electrodes, while constantly changing the position of exciting electrode and being surveyed accordingly
Amount, finally obtains a frame measurement data, can be designated as a vector m.
Wherein, the multiple electrodes in the present embodiment can be 16, or other numbers, it not limited herein
It is fixed.
It should be noted that in the present embodiment, in addition to can be in the thoracic cavity of human body arrangement multiple electrodes, can be with
Multiple electrodes are arranged in the brain of human body, the position of specific arrangement can be arranged in human body corresponding site according to actual needs,
The position not to multiple electrodes is specifically limited herein.
Further, in the present embodiment, for the constant current drive for determining, the Potential distribution in object to be imaged needs full
The following Poisson's equation of foot and boundary condition：
At border Top electrode l (2)
On border elsewhere (3)
Wherein, φ is the Potential distribution in the object to be imaged, and σ is its distribution of conductivity, IlIt is the electricity by electrode l
Stream, n is border normal direction, and r is space coordinates.Above-mentioned partial differential equation can be solved by FInite Element, and then can be in the hope of
Obtain the potential difference of border Top electrode.
Computing module 120 is used to be calculated according to measurement data and Forward simulation data the data error of electrical impedance imaging problem
, and cost functional is calculated according to default multiplying property regular terms and data error term；
Specifically, computing module 120 can further calculate the number of electrical impedance imaging problem after measurement data is obtained
According to error term.
Wherein, the data error of electrical impedance imaging problem can be calculated by below equation and obtained：
Data error item=| | S (σ)-m | |2 (4)
Wherein, to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is measurement data.
And then, cost functional can be calculated according to default multiplying property regular terms and data error term.
It should be noted that in the present embodiment, default multiplying property regular terms is set based on full variation principle, should
Multiplying property regular terms may include various forms, such as L2Norm regular terms, weighting L2Norm regular terms etc..
Wherein, process is implemented according to what default multiplying property regular terms and data error term calculated cost functional, can be wrapped
Include following steps：
Data error is carried out into multiplication calculating with the multiplying property regular terms based on full variation principle, to obtain cost functional.
The calculating of cost functional can be realized by equation below：
Cn(σ)=| | S (σ)-m | |2×Rn(σ) (5)
Wherein, Cn(σ) is cost functional, and to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is
Measurement data, Rn(σ) is multiplying property regular terms, and n is iterations.
Image reconstruction module 130 is used for by alternative manner minimization cost functional to carry out image reconstruction.Specifically,
Carrying out minimization to cost functional can be accomplished in several ways.For example, steepest descent method, Gauss-Newton method, conjugate gradient method
In any one.Certainly there are other alternative manners, it is not repeated herein.
Minimization cost functional is described in detail by taking Gauss-Newton method as an example below.
First, the gradient vector g of cost functional is solvedn(σ) and Hessian matrix Gn(σ), can specifically be written as respectively：
Wherein,It is the gradient vector of multiplying property regular terms,It is the Hessian matrix of multiplying property regular terms, J (σ) is
Jacobian matrix, to treat the discrete electrical conductivity of inverting, S () is the forward direction operator of the solution direct problem of discretization to σ, and m is measurement number
According to n is iterations.
It should be noted that above-mentioned Jacobian matrix can quickly be obtained by formula (8)：
Wherein, Ω is problem solving region, φiThe Potential distribution produced in the Ω of region during for i-th pair electrode excitation, uj
It is the Potential distribution produced in the Ω of region when jth is to electrode excitation, δ σ (e) is the characteristic function of unit e.
Secondly, treat that inverting electrical conductivity can be updated by the following direction of search：
Δσn=-[Gn]-1·gn (9)
Wherein, gnIt is the gradient vector of cost functional, GnIt is the Hessian matrix of cost functional.
And then, image reconstruction module 130 can obtain to be imaged after by above-mentioned alternative manner minimization cost functional
The reconstruction image of object.
A simulation model is also constructed in order to carry out performance verification to above-mentioned method for reconstructing, in the embodiment of the present invention, its
Finite element fission is as shown in Figure 2.Background conductance rate is 0.25S/m in the model, and semicircular electricity is included with sharp edges
Conductance is 0.1S/m, and 16 around model round dot represents electrode.Can be produced using finite element model for solving direct problem by the model
Raw simulated measurement data, and then the performance of above-mentioned method for reconstructing can be verified according to the simulated measurement data for producing.
Further, imaging object can be treated under different noise levels by above-mentioned simulation model carries out image weight
Build.For details, reference can be made to Fig. 3 (a)-Fig. 3 (c).Wherein, Fig. 3 (a) is simulated measurement data without image weight when applying noise
Build result schematic diagram；Fig. 3 (b) is image reconstruction result schematic diagram of the simulated measurement data when 1% noise is applied with；Fig. 3 (c)
For simulated measurement data when 2% noise is applied with image reconstruction result schematic diagram.Wherein, the image in Fig. 3 (a)-Fig. 3 (c)
Reconstruction has used the grids different from Fig. 2.
The example images that imaging object is rebuild under different noise levels are treated based on above-mentioned, it can be seen that simulation model
The edge of inclusion can clearly be rebuild, and the image rebuild has " piecemeal constant " characteristic, also, to simulated measurement
When data applying noise level is of a relatively high, such as 2%, the edge of image also can preferably be rebuild, therefore the explanation present invention
The biomedical electrical impedance imaging method based on the regularization of multiplying property in embodiment has good noiseproof feature.
The biomedical electrical impedance imaging device based on the regularization of multiplying property of the embodiment of the present invention, by using constant-current source wheel
Two electrodes in flowing to multiple electrodes enter row energization and measure, and obtain measurement data, and according to measurement data and forward direction
Emulation data calculate the data error of electrical impedance imaging problem, and mesh is calculated according to default multiplying property regular terms and data error term
Mark functional, and then by alternative manner minimization cost functional to carry out image reconstruction, so as to retain organism organ well
Edge configuration, make reconstruction image that there is " piecemeal constant " characteristic, and with good noise robustness.In addition, compared to
For additivity regularization mode, multiplying property regularization mode disclosed in this invention is come without setting a parameter in cost functional
The relative weighting of regulation data error and regular terms, because data error and canonical during minimization cost functional
The relative weighting of item can be adjusted dynamically, the step of eliminating by quite cumbersome numerical experiment to determine the parameter value.
Additionally, term " first ", " second " are only used for describing purpose, and it is not intended that indicating or implying relative importance
Or the implicit quantity for indicating indicated technical characteristic.Thus, define " first ", the feature of " second " can express or
Implicitly include at least one this feature.In the description of the invention, " multiple " is meant that at least two, such as two, three
It is individual etc., unless otherwise expressly limited specifically.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means to combine specific features, structure, material or spy that the embodiment or example are described
Point is contained at least one embodiment of the invention or example.In this manual, to the schematic representation of above-mentioned term not
Identical embodiment or example must be directed to.And, the specific features of description, structure, material or feature can be with office
Combined in an appropriate manner in one or more embodiments or example.Additionally, in the case of not conflicting, the skill of this area
Art personnel can be tied the feature of the different embodiments or example described in this specification and different embodiments or example
Close and combine.
Any process described otherwise above or method description in flow chart or herein is construed as, and expression includes
It is one or more for realizing specific logical function or process the step of the module of code of executable instruction, fragment or portion
Point, and the scope of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussion suitable
Sequence, including function involved by basis by it is basic simultaneously in the way of or in the opposite order, carry out perform function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Represent in flow charts or logic and/or step described otherwise above herein, for example, being considered use
In the order list of the executable instruction for realizing logic function, in may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (such as computer based system, including the system of processor or other can be held from instruction
The system of row system, device or equipment instruction fetch and execute instruction) use, or with reference to these instruction execution systems, device or set
It is standby and use.For the purpose of this specification, " computer-readable medium " can any can be included, store, communicate, propagate or pass
The dress that defeated program is used for instruction execution system, device or equipment or with reference to these instruction execution systems, device or equipment
Put.The more specifically example (non-exhaustive list) of computer-readable medium includes following：With the electricity that one or more are connected up
Connecting portion (electronic installation), portable computer diskette box (magnetic device), random access memory (RAM), read-only storage
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device, and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can thereon print described program or other are suitable
Medium, because optical scanner for example can be carried out by paper or other media, then enters edlin, interpretation or if necessary with it
His suitable method is processed electronically to obtain described program, is then stored in computer storage.
It should be appreciated that each several part of the invention can be realized with hardware, software, firmware or combinations thereof.Above-mentioned
In implementation method, the software that multiple steps or method can in memory and by suitable instruction execution system be performed with storage
Or firmware is realized.If for example, realized with hardware, and in another embodiment, can be with well known in the art
Any one of row technology or their combination are realized：With the logic gates for realizing logic function to data-signal
Discrete logic, the application specific integrated circuit with suitable combinational logic gate circuit, programmable gate array (PGA), scene
Programmable gate array (FPGA) etc..
Those skilled in the art are appreciated that to realize all or part of step that above-described embodiment method is carried
The rapid hardware that can be by program to instruct correlation is completed, and described program can be stored in a kind of computer-readable storage medium
In matter, the program upon execution, including one or a combination set of the step of embodiment of the method.
Additionally, during each functional unit in each embodiment of the invention can be integrated in a processing module, it is also possible to
It is that unit is individually physically present, it is also possible to which two or more units are integrated in a module.Above-mentioned integrated mould
Block can both be realized in the form of hardware, it would however also be possible to employ the form of software function module is realized.The integrated module is such as
Fruit is to realize in the form of software function module and as independent production marketing or when using, it is also possible to which storage is in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only storage, disk or CD etc..Although having been shown above and retouching
Embodiments of the invention are stated, it is to be understood that above-described embodiment is exemplary, it is impossible to be interpreted as to limit of the invention
System, one of ordinary skill in the art can be changed to above-described embodiment, change, replace and become within the scope of the invention
Type.
Claims (10)
1. a kind of biomedical electrical impedance imaging method based on the regularization of multiplying property, it is characterised in that comprise the following steps：
Multiple electrodes are arranged around object to be imaged, and in measurement process, in turn in the multiple electrode of constant current drive
Two electrodes simultaneously measure the potential difference on other electrodes in the multiple electrode, to obtain a frame measurement data；
The data error of electrical impedance imaging problem is calculated according to the measurement data and Forward simulation data, and according to default
Multiplying property regular terms and the data error calculate cost functional；
By cost functional described in alternative manner minimization carrying out image reconstruction.
2. the biomedical electrical impedance imaging method of multiplying property regularization is based on as claimed in claim 1, it is characterised in that described
The data error of electrical impedance imaging problem is calculated by below equation and obtained：
Data error item=| | S (σ)-m | |2
Wherein, to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is the measurement data.
3. the biomedical electrical impedance imaging method of multiplying property regularization is based on as claimed in claim 1 or 2, it is characterised in that
Default the multiplying property regular terms is set based on full variation principle, wherein, it is described according to default multiplying property regular terms and
The data error calculates cost functional, including：
The data error is carried out into multiplication calculating with the multiplying property regular terms based on full variation principle, to obtain the mesh
Mark functional.
4. the biomedical electrical impedance imaging method of multiplying property regularization is based on as claimed in claim 1, it is characterised in that for
The constant current drive for determining, the Potential distribution in the object to be imaged meets following Poisson's equation and boundary condition：
At border Top electrode l
On border elsewhere
Wherein, φ is the Potential distribution in the object to be imaged, and σ is its distribution of conductivity, IlIt is the electric current by electrode l, n
It is border normal direction, r is space coordinates.
5. the biomedical electrical impedance imaging method of multiplying property regularization is based on as claimed in claim 1, it is characterised in that described
Alternative manner includes any one in steepest descent method, Newton method, conjugate gradient method.
6. a kind of biomedical electrical impedance imaging device based on the regularization of multiplying property, it is characterised in that including：
Measurement module, for arranging multiple electrodes around object to be imaged, and in measurement process, in turn described in constant current drive
Two electrodes in multiple electrodes simultaneously measure the potential difference on other electrodes in the multiple electrode, to obtain frame measurement number
According to；
Computing module, the data error for calculating electrical impedance imaging problem according to the measurement data and Forward simulation data
, and cost functional is calculated according to default multiplying property regular terms and the data error；
Image reconstruction module, for by cost functional described in alternative manner minimization carrying out image reconstruction.
7. the biomedical electrical impedance imaging device of multiplying property regularization is based on as claimed in claim 6, it is characterised in that described
The data error of electrical impedance imaging problem is calculated by below equation and obtained：
Data error item=| | S (σ)-m | |2
Wherein, to treat inverting electrical conductivity, S () is the forward direction operator for solving direct problem to σ, and m is the measurement data.
8. the biomedical electrical impedance imaging device based on the regularization of multiplying property as claimed in claims 6 or 7, it is characterised in that
Default the multiplying property regular terms is set based on full variation principle, wherein, the computing module specifically for：
The data error is carried out into multiplication calculating with the multiplying property regular terms based on full variation principle, to obtain the mesh
Mark functional.
9. the biomedical electrical impedance imaging device of multiplying property regularization is based on as claimed in claim 6, it is characterised in that for
The constant current drive for determining, the Potential distribution in the object to be imaged meets following Poisson's equation and boundary condition：
At border Top electrode l
On border elsewhere
Wherein, φ is the Potential distribution in the object to be imaged, and σ is its distribution of conductivity, IlIt is the electric current by electrode l, n
It is border normal direction, r is space coordinates.
10. the biomedical electrical impedance imaging device of multiplying property regularization is based on as claimed in claim 6, it is characterised in that institute
Stating alternative manner includes any one in steepest descent method, Newton method, conjugate gradient method.
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