CN105232087B - Ultrasonic elastograph imaging real time processing system - Google Patents

Ultrasonic elastograph imaging real time processing system Download PDF

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CN105232087B
CN105232087B CN201510746349.4A CN201510746349A CN105232087B CN 105232087 B CN105232087 B CN 105232087B CN 201510746349 A CN201510746349 A CN 201510746349A CN 105232087 B CN105232087 B CN 105232087B
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CN105232087A (en
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严凯
赵明昌
陆坚
莫善玨
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Wuxi Chison Medical Technologies Co Ltd
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Wuxi Chison Medical Technologies Co Ltd
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Abstract

The present invention relates to ultrasound medicine image field, and in particular to a kind of ultrasonic elastograph imaging system and its method of work realized based on FPGA.The system includes front end ultrasonic digital signal acquisition module, middle-end ultrasonic elastograph imaging real-time processing module, rear end elastic image display module.It is an advantage of the current invention that the elastogram signal transacting of core is only completed with FPGA, and real-time display elastic image, without front end ultrasound data is transferred into host computer, so as to simplify system, improve product cost.

Description

Ultrasonic elastograph imaging real time processing system
Technical field
The present invention relates to ultrasound medicine image field, the real-time ultrasound elastogram system specifically realized based on FPGA System.
Background technology
The elastic information of supersonic sounding target, the Biological indicators important as one, clinically there is certain finger Lead meaning.Quasistatic elastography, the hardness information for detecting target can be obtained by ultrasonic instrument.As super Sound shadow obtained in-depth study as the important clinical drop applications in field, this technology at past twenties years.
How quick acquisition in real time detects space displacement information of the target after being under pressure, and is quasistatic Ultrasonic elasticity The most thorny issue in imaging.There are some researches show the estimation of the space displacement information based on signal cross-correlation technique is to compare at present Accurately and reliably method.However, this algorithm contains a series of complicated logical operation such as multiplication and integration, to hardware resource Consumption is very big.At this stage, the exemplary process framework of ultrasonic elastograph imaging is that front radio-frequency data are uploaded to PC by FPGA, by PC carries out elastogram processing, and this processing method proposes very big challenge to PC performance.High performance PC is often needed Want high performance mainboard matched, this hardware system structure undoubtedly adds the cost of low-end product.
Embedded System Design scheme based on FPGA can be realized on piece by the algorithm integration of complexity into hardware system System, hardware cost is accomplished to minimize, and the product gone out using this conceptual design also has the advantages that portable, energy-conservation. Therefore, a FPGA platform scheme with powerful data acquisition and disposal ability is designed, is necessary.
The content of the invention
It is an object of the invention to be limited to hardware cost with low-end product for existing elastogram algorithm is computationally intensive Contradiction, there is provided a kind of ultrasonic elastograph imaging real time processing system based on FPGA, it goes for various to compile on a large scale On journey array Platform, real-time display elastic graph.
To achieve the above object, ultrasonic elastograph imaging real time processing system of the present invention is using one piece of FPGA and its outer The RAM connect, the FPGA front ends connection ultrasonic probe and analog front end circuit, FPGA rear ends connection display module;Inside FPGA Including ultrasonic digital signal acquisition module and ultrasonic elastograph imaging real-time processing module, the control of ultrasonic digital signal acquisition module is visited Hair penetrates the ultrasonic signal for elastogram, and receives echo-signal, then by ultrasonic elastograph imaging real-time processing module Reception signal is cached and handled, and the elastic image after processing is output to display module in real time;
The ultrasonic elastograph imaging real-time processing module include be sequentially connected computing cross-correlation module, comparison module, sky Between displacement output module, gradient algorithm module, elastic information output module, wherein computing cross-correlation module has N number of, comparison module Inputted with N, connect N number of computing cross-correlation module respectively;
N number of computing cross-correlation module, be respectively used to calculate a space pixel current frame data and data storage 1~ N cross-correlation coefficient;
The comparison module of the N inputs receives the cross-correlation coefficient of N number of computing cross-correlation module output, has for searching for The data storage of optimal cross-correlation coefficient;
The space displacement output module, for calculating the data storage spatial positional information with optimal cross-correlation coefficient With the difference of current pixel position information, i.e. displacement, and the displacement information of the space pixel is latched;
The gradient algorithm module, for space displacement information to be converted into elastic information;
The elastic information output module, refresh the elastic information of pixel of interest in scanning target for dynamic realtime.
The course of work of system is as follows:
Step 1, to the continuous scanning multiple image of target to be checked under the control of ultrasonic digital signal acquisition module, And ultrasonic radio frequency initial data is stored;
Step 2, computing cross-correlation module carry out mutual to the current frame data of a space pixel in step 1 and data storage Relevant treatment, calculate cross-correlation coefficient:
Assuming that frame data size is K, the current frame data of space pixel M adjacent sample values composition isWherein n is current spatial pixel M positional information,
I-th of adjacent history frame data be
I-th of adjacent history frame data is done into computing cross-correlation with this segment data, obtained cross-correlation coefficient is:
Wherein
Comparison module is according to maxI=-N/2~N/2Theta (i) is searched between-N/2~N/2 corresponding to maximum cross-correlation coefficient Offset location information i, space displacement output module realizes that space pixel M radio frequency initial data is converted into instead in FPGA Spatial offset distant (M)=i* (1/fs) * (c/2), wherein c for reflecting object elastic information is ultrasonic transmission speed, fs For systematic sampling rate;
Step 3, gradient algorithm module calculate gradient information to acquired results in step 2 Wherein x=(1/fs) * (c/2);
Step 4, to two-dimentional scanning figure traversal step two and step 3, the gradient information of all pixels is calculated, in FPGA Realize that gradient information is converted into biological tissue elasticity figure;
Step 5, elastic information output module driving display module real-time display elastic graph.
The present invention distinguishing feature be it is following some:
(1) the Embedded System Design scheme based on FPGA is used, the signal processing algorithm of complexity is integrated into hardware system In system, software and hardware integration is realized, the product of design has the advantages that small volume, portable, energy-conservation.
(2) in FPGA, front radio-frequency ultrasonic signal can be obtained, signal transacting is completed by hardware program language, subtracted The problem of signal processing algorithm data source is of low quality less.
(3) by being reconfigured to FPGA, spread F PGA signal processing function, system is made to go for pulse more Other applications of ultrasound patterns such as Pu Le, flow Doppler.
(4) embedded processing based on FPGA can reduce data flow, ensure real-time.
Brief description of the drawings
System block diagrams of the Fig. 1 based on the FPGA real-time ultrasound elastogram systems realized.
The flow chart of real-time processing modules of the Fig. 2 based on the FPGA ultrasonic elastograph imaging systems realized.
Embodiment
The embodiment of the present invention is described in further detail below according to accompanying drawing.
Reference picture 1, hardware unit of the present invention include probe and analog front end circuit, the FPGA of one piece of low-power consumption And its external RAM, a display module and its periphery configuration circuit.Wherein:Described probe and analog front circuit is used for Transmitting and received ultrasonic signal, analog front circuit can connect the conventional transducers such as linear array, convex battle array, phased array;Described FPGA And its external RAM forms low power processor, have in its piece logic units, multiplier that some support big data quantities calculate, Buffer unit etc., there is store function;Described display module is used to show FPGA output informations.Each hardware composition part it Between annexation be:Probe and analog front circuit are connected with FPGA;FPGA is connected with plug-in RAM, display module.
The signal processing flow of the ultrasonic elastograph imaging system based on FPGA is as follows shown in Fig. 1:
(1) different types of ultrasonic probe is connected by the AFE(analog front end) part such as pinboard circuit of popping one's head in FPGA, FPGA Inside includes ultrasonic digital signal acquisition module and ultrasonic elastograph imaging real-time processing module, ultrasonic digital signal acquisition module control Ultrasonic signal of the system probe transmitting for elastogram, and receives echo-signal;
(2) ultrasonic elastograph imaging real-time processing module is cached and handled to reception signal;
(3) elastic image after processing is output to display module by FPGA in real time.
Reference picture 2, the ultrasonic elastograph imaging real-time processing module of the invention based on FPGA include:N number of computing cross-correlation Module, the comparison module of a N input, a space displacement output module, a gradient algorithm module, an elastic information are defeated Go out module.Wherein:
Described N number of computing cross-correlation module, it is respectively used to calculate the current frame data and data storage 1 of certain space pixel ~N cross-correlation;
The comparison module of described N inputs, for searching for the data storage with optimal coefficient correlation;
Described space displacement output module, for calculating the data storage spatial positional information with optimal coefficient correlation With the difference of current pixel position information, and the shift differences information of the space pixel is latched;
Described gradient algorithm module, for space displacement information to be converted into elastic information;
Described elastic information output module, refresh the elasticity letter of pixel of interest in scanning target for dynamic realtime Breath.
Specific works method based on the FPGA ultrasonic elastograph imaging real time processing systems realized is as follows:
Step 1, to the continuous scanning multiple image of target to be checked, and ultrasonic radio frequency initial data is stored.
Step 2, programmed by verilog/vhdl, computing cross-correlation module in step 1 certain space pixel it is current Frame data and data storage carry out cross correlation process, calculate cross-correlation coefficient:
Assuming that frame data size is K, the current frame data of space pixel M adjacent sample values composition isWherein n is current spatial pixel M positional information,
I-th of adjacent history frame data be
I-th of adjacent history frame data is done into computing cross-correlation with this segment data, obtained cross-correlation coefficient is:
Wherein
Comparison module is according to maxI=-N/2~N/2Theta (i) is searched between-N/2~N/2 corresponding to maximum cross-correlation coefficient Offset location information i, space displacement output module realizes that space pixel M radio frequency initial data is converted into instead in FPGA Spatial offset distant (M)=i* (1/fs) * (c/2), wherein c for reflecting object elastic information is ultrasonic transmission speed 1540m/s, fs are systematic sampling rate;N is region of search size, it is assumed that is 100.
Step 3, programmed by verilog/vhdl, gradient algorithm module calculates acquired results in step 2 gradient letter BreathWherein x=(1/fs) * (c/2).
Step 4, to two-dimentional scanning figure traversal step two and step 3, the gradient information of all pixels is calculated, in FPGA Realize that gradient information is converted into biological tissue elasticity figure.
Step 5, programmed by verilog/vhdl, display module real-time display bullet is driven by elastic information output module Property figure.

Claims (2)

1. ultrasonic elastograph imaging real time processing system, it is characterized in that:Including one piece of FPGA and its external RAM, before the FPGA End connection ultrasonic probe and analog front end circuit, FPGA rear ends connection display module;Obtained inside FPGA including ultrasonic digital signal Modulus block and ultrasonic elastograph imaging real-time processing module, the control probe transmitting of ultrasonic digital signal acquisition module are used for elastogram Ultrasonic signal, then and receives echo-signal caches by ultrasonic elastograph imaging real-time processing module to reception signal And processing, and the elastic image after processing is output to display module in real time;
The ultrasonic elastograph imaging real-time processing module includes computing cross-correlation module, comparison module, the space bit being sequentially connected Output module, gradient algorithm module, elastic information output module are moved, wherein computing cross-correlation module has N number of, and comparison module has N is inputted, and connects N number of computing cross-correlation module respectively;
N number of computing cross-correlation module, it is respectively used to calculate 1~N's of current frame data and data storage of a space pixel Cross-correlation coefficient;
The comparison module of the N inputs receives the cross-correlation coefficient of N number of computing cross-correlation module output, for searching for optimal The data storage of cross-correlation coefficient;
The space displacement output module, for calculating the data storage spatial positional information with optimal cross-correlation coefficient with working as The difference of preceding pixel positional information, i.e. displacement, and latch the displacement information of the space pixel;
The gradient algorithm module, for space displacement information to be converted into elastic information;
The elastic information output module, refresh the elastic information of pixel of interest in scanning target for dynamic realtime.
2. ultrasonic elastograph imaging real time processing system as claimed in claim 1, it is characterized in that, the course of work of system is as follows:
Step 1, to the continuous scanning multiple image of target to be checked under the control of ultrasonic digital signal acquisition module, and it is right Ultrasonic radio frequency initial data is stored;
Step 2, computing cross-correlation module carry out cross-correlation to the current frame data of a space pixel in step 1 and data storage Processing, calculate cross-correlation coefficient:
Assuming that frame data size is K, the current frame data of space pixel M adjacent sample values composition isWherein n is current spatial pixel M positional information,
I-th of adjacent history frame data be <mrow> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mo>-</mo> <mfrac> <mi>K</mi> <mn>2</mn> </mfrac> <mo>+</mo> <mi>i</mi> </mrow> </msub> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mo>-</mo> <mfrac> <mi>K</mi> <mn>2</mn> </mfrac> <mo>+</mo> <mn>1</mn> <mo>+</mo> <mi>i</mi> </mrow> </msub> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mo>+</mo> <mfrac> <mi>K</mi> <mn>2</mn> </mfrac> <mo>+</mo> <mi>i</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mo>,</mo> </mrow>
I-th of adjacent history frame data is done into computing cross-correlation with this segment data, obtained cross-correlation coefficient is: <mrow> <mi>t</mi> <mi>h</mi> <mi>e</mi> <mi>t</mi> <mi>a</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>cov</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>/</mo> <msqrt> <mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>)</mo> </mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> </msqrt> <mo>,</mo> </mrow>
Wherein <mrow> <mi>cov</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mi>K</mi> </mfrac> <msubsup> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>-</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>+</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> </msubsup> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>m</mi> <mi>e</mi> <mi>a</mi> <mi>n</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>x</mi> <mo>&amp;lsqb;</mo> <msub> <mi>x</mi> <mrow> <mi>pre</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> </mrow> <mrow> <mi>m</mi> <mi>e</mi> <mi>a</mi> <mi>n</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> <mo>,</mo> </mrow>
<mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mi>K</mi> </mfrac> <msubsup> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>-</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>+</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>m</mi> <mi>e</mi> <mi>a</mi> <mi>n</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>w</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> <mo>,</mo> </mrow>
<mrow> <mi>D</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mi>K</mi> </mfrac> <msubsup> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>-</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mi>k</mi> <mo>=</mo> <mi>n</mi> <mo>+</mo> <mi>K</mi> <mo>/</mo> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>m</mi> <mi>e</mi> <mi>a</mi> <mi>n</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>e</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> <mo>;</mo> </mrow>
Comparison module is according to maxI=-N/2~N/2Theta (i) searches inclined corresponding to maximum cross-correlation coefficient between-N/2~N/2 Shifting amount positional information i, space displacement output module realize that space pixel M radio frequency initial data is converted into reflection mesh in FPGA Spatial offset distant (M)=i* (1/fs) * (c/2), wherein c of mark elastic information is ultrasonic transmission speed, and fs is to be System sample rate;
Step 3, gradient algorithm module calculate gradient information to acquired results in step 2 Wherein x=(1/fs) * (c/2);
Step 4, to two-dimentional scanning figure traversal step two and step 3, the gradient information of all pixels is calculated, is realized in FPGA Gradient information is converted into biological tissue elasticity figure;
Step 5, elastic information output module driving display module real-time display elastic graph.
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