CN111429506A - Volume fraction obtaining method, device and system based on three-dimensional reconstruction and storage medium - Google Patents
Volume fraction obtaining method, device and system based on three-dimensional reconstruction and storage medium Download PDFInfo
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Abstract
The invention discloses a volume fraction obtaining method and device based on three-dimensional reconstruction and a storage medium. Wherein, the method comprises the following steps: acquiring a projection image set of each two-dimensional slice layer of the three-dimensional object to be detected in a set projection angle range; performing initial image reconstruction based on the projection image set corresponding to each two-dimensional slice layer to obtain an initial reconstruction image corresponding to each two-dimensional slice layer; updating the image of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected; and determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected. The invention can reduce the input of the prior knowledge and reduce the influence of the input parameters on the reconstruction result.
Description
Technical Field
The invention relates to the field of transmission electron microscope application and image processing, in particular to a volume fraction obtaining method and device based on three-dimensional reconstruction and a storage medium.
Background
The volume fraction is very important for predicting the material performance, and in the related art, a quantitative calculation method (for example, measuring the volume fraction of precipitated phases in an aluminum alloy) mainly has two types, namely, the first type is used for measuring the surface density, and the second type is used for measuring the three-dimensional atom probe. Among them, the method of measuring the areal density requires the measurement of the thickness of a sample by CBED (Convergent Beam Electron Diffraction), and the error of this method is nearly 30%. The method for measuring the volume fraction by using the three-dimensional atom probe is usually limited to a region of a few nanometers, is not representative and is not suitable for calculating the volume fraction of a precipitated phase in a bulk material.
In addition, in the related art, there is a case where the volume fraction of the precipitated phase is measured by a scanning electron microscope method, but this method is only suitable for a case where the precipitated phase is relatively coarse. In addition, the three-dimensional electron tomography reconstruction method (3DET) can characterize structural information at a nanometer scale, and the distribution of S phases in aluminum alloy and the distribution of second phases in 7xxx aluminum alloy which can be characterized by the method show that the 3DET has been well applied to qualitative analysis for describing shape, position and the like. However, since the tilting angle of the 3DET is limited, and generally only from 70 to-70 degrees, the object reconstructed by the 3DET is always affected by the missing cone (missing wedge) to generate artifacts, which makes the quantitative application such as volume fraction acquisition still difficult.
In order to overcome the above problems, in the related art, the Reconstruction accuracy is improved by a discrete algebraic Reconstruction algorithm (DART), and is successfully applied in the porosity calculation. However, the DART method requires many parameters to be input and requires the user to have experience, and thus is difficult to obtain wide application.
Disclosure of Invention
In view of this, embodiments of the present invention provide a volume fraction obtaining method and apparatus based on three-dimensional reconstruction, and a storage medium, which aim to reduce input of prior knowledge, reduce influence of input parameters on a reconstruction result, and thereby improve accuracy of obtaining a volume fraction.
The technical scheme of the embodiment of the invention is realized as follows:
the embodiment of the invention provides a volume fraction obtaining method based on three-dimensional reconstruction, which comprises the following steps:
acquiring a projection image set of each two-dimensional slice layer of a three-dimensional object to be detected in a set projection angle range, wherein the projection image set comprises projection images corresponding to different projection angles in the set projection angle range;
performing initial image reconstruction based on the projection image set corresponding to each two-dimensional slice layer to obtain an initial reconstruction image corresponding to each two-dimensional slice layer;
updating the image of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected;
and determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
In the above scheme, the image updating the initial reconstructed image until the number of updating times reaches a set threshold to obtain a final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be measured includes:
determining an independent region in the initial reconstructed image based on a boundary region in the initial reconstructed image;
assigning the pixel parameters in each independent area, and updating the initial reconstructed image based on the assigned image parameters;
and if the updating times are smaller than a set threshold value, based on the projection image set of the updated initial reconstruction image in the set projection angle range, performing initial image reconstruction again, determining independent areas for the initial reconstruction image after the initial image reconstruction again, and assigning values to pixel parameters in each independent area to update the initial reconstruction image until the updating times reach the set threshold value, so as to obtain a final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
In the foregoing solution, the assigning the pixel parameters in each independent area includes:
acquiring the peak value of the gray value distribution histogram of each independent area;
and replacing the gray value of the pixel point in each independent area with the corresponding peak value.
In the foregoing solution, the determining the volume fraction of the target region of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be detected includes:
and determining the volume fraction of the target area based on the ratio of the sum of the pixel points of the target area of the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected to the total number of the pixel points of the three-dimensional object to be detected.
In the above scheme, the method further comprises:
reconstructing based on the projection image set of each two-dimensional slice layer to obtain a three-dimensional model;
determining a first volume fraction of the target region based on the three-dimensional model;
acquiring a projection image set of each two-dimensional slice of the three-dimensional model in the set projection angle range, and determining a final reconstruction image corresponding to each two-dimensional slice of the three-dimensional model to obtain a second volume fraction of the target area;
and correcting the volume fraction based on the first volume fraction and the second volume fraction to obtain a corrected volume fraction.
In the above scheme, the method further comprises:
and carrying out component distinguishing on the three-dimensional object to be detected based on the gray values of the pixel points in the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected.
In the above scheme, reconstructing the projection image set based on each two-dimensional slice layer to obtain a three-dimensional model includes:
and carrying out three-dimensional modeling on the projection image set of each two-dimensional slice layer based on a Filtering Back Projection (FBP) method to obtain the three-dimensional model.
The embodiment of the invention also provides a volume fraction acquiring device based on three-dimensional reconstruction, which comprises:
the projection image acquisition module is used for acquiring a projection image set of each two-dimensional slice layer of the three-dimensional object to be detected in a set projection angle range, wherein the projection image set comprises projection images corresponding to different projection angles in the set projection angle range;
the image reconstruction module is used for performing initial image reconstruction based on the projection image sets corresponding to the two-dimensional slice layers to obtain initial reconstruction images corresponding to the two-dimensional slice layers;
the image updating module is used for updating the images of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected;
and the volume fraction determining module is used for determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
The embodiment of the invention also provides volume fraction obtaining equipment based on three-dimensional reconstruction, which comprises: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor, when running the computer program, is adapted to perform the steps of the method according to any of the embodiments of the present invention.
The embodiment of the invention also provides a storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the method of any embodiment of the invention are realized.
According to the technical scheme provided by the embodiment of the invention, the initial image reconstruction is carried out on the basis of the projection image set corresponding to each two-dimensional slice layer of the three-dimensional object to be detected, the initial reconstruction image of each two-dimensional slice layer is obtained, the image of the initial reconstruction image is updated until the updating frequency reaches the set threshold value, the final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected is obtained, the volume fraction of the target area of the three-dimensional object to be detected is determined on the basis of the final reconstruction image of each two-dimensional slice layer, the input of priori knowledge can be reduced, the influence of input parameters on reconstruction results is reduced, the dependency of volume fraction detection on specific personnel is reduced, and therefore, the.
Drawings
FIG. 1 is a schematic flow chart of a volume fraction obtaining method based on three-dimensional reconstruction according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating the reconstruction effect of the method according to the embodiment of the present invention;
FIG. 3 is a schematic diagram of a reconstructed image and a histogram of gray scale value distribution obtained by the method of the embodiment of the present invention and a schematic diagram of an original image and a histogram of gray scale value distribution of the original image;
FIG. 4 is a 7xxx aluminum alloy tilt series HAADF-STEM image taken with a transmission electron microscope FEI Tecnai F20;
FIG. 5 is a graphical representation of the volume fraction of precipitated phases in a 7N01 aluminum alloy calculated by the method of an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a volume fraction acquiring apparatus based on three-dimensional reconstruction according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a volume fraction acquiring apparatus based on three-dimensional reconstruction according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
In the related art, in order to obtain the volume fraction quantitatively, when the DART is used to improve the image reconstruction accuracy, the user needs to have experience and input more parameters, wherein the parameters needing to be input by the user include, but are not limited to: once the parameters input by the user are not ideal, the object to be reconstructed contains several components and the gray value range corresponding to the object of each component, which directly results in errors in the reconstruction result.
Based on this, in various embodiments of the present invention, initial image reconstruction is performed based on a projection image set corresponding to each two-dimensional slice of a three-dimensional object to be detected, after an initial reconstruction image of each two-dimensional slice is obtained, the initial reconstruction image is further subjected to image update until the number of updates reaches a set threshold, a final reconstruction image of each two-dimensional slice is obtained, and a volume fraction of a target region of the three-dimensional object to be detected is determined, so that input of prior knowledge can be reduced, influence of input parameters on a reconstruction result is reduced, and dependency of volume fraction detection on a specific person is reduced, so that the present invention has wide applicability.
As shown in fig. 1, an embodiment of the present invention provides a volume fraction obtaining method based on three-dimensional reconstruction, including:
101, acquiring a projection image set of each two-dimensional slice layer of a three-dimensional object to be detected in a set projection angle range, wherein the projection image set comprises projection images corresponding to different projection angles in the set projection angle range;
here, the projection image of each two-dimensional slice of the three-dimensional object to be measured may be acquired by means of projection. In one embodiment, the projection angles are set to range from-60 to 60 degrees and are spaced apart by 1.5 degrees, so that there are 81 projection images for each two-dimensional slice, it being understood that in other possible embodiments, the projection angles and spacings may be varied, and the greater the number of projection images, the wider the coverage angle, and the higher the reconstruction accuracy.
As shown in fig. 2, fig. 2(a) is a simulated two-dimensional image, which can be regarded as a two-dimensional slice of a three-dimensional object, and in order to verify the feasibility of the method of the present invention, 81 projection images are obtained by projecting fig. 2(a) to-60 ° to 60 ° at an interval of 1.5 ° for the projection of the three-dimensional object.
In an application example, the obtained 7xxx aluminum alloy tilt series HAADF-STEM (high angle annular dark field image-scanning transmission electron microscope) images were taken with a transmission electron microscope FEI Tecnai F20 for a total of 81 sheets, and the projection images shown in fig. 4 were obtained at angles of-60 ° to 60 °, respectively, and at intervals of 1.5 °.
In practical application, the method for acquiring the projection image set of each two-dimensional slice of the three-dimensional object to be measured in the set projection angle range specifically comprises the following steps: in the experimental process, the three-dimensional object is projected under each angle, for example, the three-dimensional object is projected under-70 to 70 degrees to obtain a total of 141 two-dimensional projection images, then the projection of the first slice under-70 to 70 degrees, i.e. the first line of each two-dimensional projection, the projection of the second slice under-70 to 70 degrees, i.e. the second line of each two-dimensional projection, and so on, to obtain the projection image set corresponding to each two-dimensional slice.
102, performing initial image reconstruction based on the projection image set corresponding to each two-dimensional slice layer to obtain an initial reconstruction image corresponding to each two-dimensional slice layer;
here, SIRT (temporal iterative reconstruction Technique) reconstruction may be performed on the projection image set corresponding to each two-dimensional slice to obtain an initial reconstructed image. For example, after the projection of fig. 2(a), an initial reconstructed image as shown in fig. 2(b) is reconstructed. In other embodiments, other existing image reconstruction methods may also be adopted to perform the initial image reconstruction, for example, the initial image reconstruction is performed based on an Algebraic Reconstruction Technique (ART) or a Discrete Algebraic Reconstruction Technique (DART), which is not specifically limited in the present invention.
103, updating the image of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected;
in the embodiment of the present invention, the image updating the initial reconstructed image until the number of updating times reaches a set threshold to obtain a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be measured includes:
determining an independent region in the initial reconstructed image based on a boundary region in the initial reconstructed image;
assigning the pixel parameters in each independent area, and updating the initial reconstructed image based on the assigned image parameters;
and if the updating times are smaller than a set threshold value, based on the projection image set of the updated initial reconstruction image in the set projection angle range, performing initial image reconstruction again, determining independent areas for the initial reconstruction image after the initial image reconstruction again, and assigning values to pixel parameters in each independent area to update the initial reconstruction image until the updating times reach the set threshold value, so as to obtain a final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
Here, the independent area refers to a connected island-shaped area determined based on the boundary area, that is, an area corresponding to the closed area defined by the boundary area except for the boundary area. In practical applications, a watershed algorithm or a boundary algorithm may be used to identify boundary regions and non-boundary regions, so as to determine the independent regions. For example, the boundary region of the image of fig. 2(b) is found as shown in fig. 2(c), the non-boundary region is shown in fig. 2(d), and fig. 2(e) shows an extracted independent region of fig. 2 (d). In other possible embodiments, other algorithms may be used.
Because an independent area can be regarded as the same component, the gray value difference of the pixel points in the independent area is not large, and the actual value is close to the peak value of the gray value distribution histogram. Based on this, in an embodiment, the assigning the pixel parameters in each independent area includes:
acquiring the peak value of the gray value distribution histogram of each independent area;
and replacing the gray value of the pixel point in each independent area with the corresponding peak value.
In practical application, the peak value of the gray value distribution histogram of each independent area can be automatically obtained and given to the area, namely, the gray value of a pixel point in the area is changed into a corresponding peak value, so that the initial reconstructed image is updated.
For the updated initial reconstructed image of each two-dimensional slice, a projection image set of the updated initial reconstructed image of each two-dimensional slice within a set projection angle range is also required to be obtained (refer to the implementation process in step 101), initial image reconstruction is performed again based on the projection image set of the updated initial reconstructed image within the set projection angle range (refer to the implementation process in step 102), an independent area is determined for the initial reconstructed image after initial image reconstruction is performed again, and pixel parameters in each independent area are assigned to update the initial reconstructed image until the number of updating times reaches the set threshold, so that a final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be measured is obtained.
In practical application, the value of the update times can be set according to practical experience. FIG. 2(g) is the output after 10 updates; the final reconstruction result (i.e., the final reconstructed image) is an output result after 30 updates as shown in fig. 2 (h). FIG. 2(i) shows the difference between the reconstruction results of FIG. 2(h) and the original FIG. 2(a), which can be seen to be very small, thus verifying the reliability of the image reconstruction method (also known as weight-based DART, abbreviated as W-DART) in the reconstruction of analog data in the embodiments of the present invention.
In this way, in the process of updating the initial reconstructed image, the gray values of the pixel points in each independent region are automatically assigned, so that the input of prior knowledge is reduced, the reconstruction error is reduced in an iterative mode (namely, the set number of initial reconstructed images are updated), and the accuracy of the final reconstructed image corresponding to each two-dimensional slice layer can be effectively improved.
And 104, determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
Here, the determining the volume fraction of the target region of the three-dimensional object to be measured based on the final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be measured includes:
and determining the volume fraction of the target area based on the ratio of the sum of the pixel points of the target area of the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected to the total number of the pixel points of the three-dimensional object to be detected. Here, the target area refers to a component of interest to the user.
In an embodiment, the method further comprises:
reconstructing based on the projection image set of each two-dimensional slice layer to obtain a three-dimensional model;
determining a first volume fraction of the target region based on the three-dimensional model;
acquiring a projection image set of each two-dimensional slice of the three-dimensional model in the set projection angle range, and determining a final reconstruction image corresponding to each two-dimensional slice of the three-dimensional model to obtain a second volume fraction of the target area;
and correcting the volume fraction based on the first volume fraction and the second volume fraction to obtain a corrected volume fraction.
In practical application, three-dimensional modeling is carried out on the projection image set of each two-dimensional slice layer based on a Filtering Back Projection (FBP) method, and the three-dimensional model is obtained. In other possible embodiments, other three-dimensional modeling algorithms may be selected.
For the three-dimensional model obtained by the three-dimensional modeling, the first integral number F1 of the target region can be calculated using the three-dimensional model.
The embodiment of the invention can also obtain the projection images of each two-dimensional slice layer in the three-dimensional model under different projection angles according to the method shown in the step 101 to obtain the projection image set of each two-dimensional slice layer, and obtain the initial reconstruction image corresponding to each two-dimensional slice layer according to the method shown in the step 102; obtaining a final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional model according to the method shown in the step 103; a second volume fraction F2 of the target region, i.e. the volume fraction corresponding to the target region of the three-dimensional model, is then determined according to the method shown in step 104.
Correcting the volume fraction based on the first volume fraction and the second volume fraction, specifically according to the following formula:
where F0 represents the volume fraction of the target region in step 104, and F is the volume fraction of the target region after correction.
Because of the limitation of projection angle, projection quantity and the like, the resolution ratio after three-dimensional reconstruction is actually lower than that of a two-dimensional projection image obtained by shooting, therefore, the error exists between the result after three-dimensional reconstruction and the real situation, on the basis, in order to improve the accuracy of the final volume fraction, the embodiment of the invention firstly obtains a model which is closer to the real situation through a three-dimensional model reconstruction method (the three-dimensional model has modeling error), because the volume fraction of a target area in the three-dimensional model is easier to obtain, the reconstruction error of the three-dimensional model during image reconstruction can be obtained by adopting the image reconstruction method of the embodiment of the invention for the three-dimensional model, even if the three-dimensional model has modeling error, the correlation between the reconstruction error of the obtained image reconstruction and the modeling error is smaller, therefore, the method of the embodiment of the invention can obtain the volume fraction result by real projection and subtract the reconstruction error of the image, the error of the obtained volume fraction can be reduced, and the accuracy of the finally obtained volume fraction is improved. FIG. 5 is a graphical representation of the volume fraction of precipitated phases in a 7N01 aluminum alloy calculated using the method of an embodiment of the present invention.
In an embodiment, the method further comprises:
and carrying out component distinguishing on the three-dimensional object to be detected based on the gray values of the pixel points in the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected.
In actual application, the components can be distinguished by using the gray value range corresponding to the components. As shown in fig. 3, compared with the original images 3(a) and 3(c), it can be seen that the reconstruction algorithm of the embodiment of the present invention can reconstruct good shape information (fig. 3(b)) and can also generate two peaks with different gray values (fig. 3(d)), and it can be seen that the method of the embodiment of the present invention can accurately reconstruct the shape of the image and the reliability of component separation, that is, the number of types of particles in the system can be obtained by the number of peaks in the histogram; meanwhile, the effect of more accurate volume fraction can be calculated.
In practical application, the same component corresponds to a gray value range, so that on one hand, the number of component types can be identified by using a gray histogram (several peaks exist in an observed gray histogram), and on the other hand, if the components in the three-dimensional object are known, the components can be segmented according to the peak value range of the gray histogram by combining the prior knowledge of an experimenter, so that the volume fraction of each component can be obtained.
In order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a volume fraction obtaining apparatus based on three-dimensional reconstruction, as shown in fig. 6, including: a projection image acquisition module 601, an image reconstruction module 602, an image update module 603, and a volume fraction determination module 604. Wherein the content of the first and second substances,
the projection image acquisition module 601 is configured to acquire a projection image set of each two-dimensional slice of the three-dimensional object to be detected within a set projection angle range, where the projection image set includes projection images corresponding to different projection angles within the set projection angle range;
an image reconstruction module 602, configured to perform initial image reconstruction based on the projection image set corresponding to each two-dimensional slice layer to obtain an initial reconstruction image corresponding to each two-dimensional slice layer;
an image updating module 603, configured to perform image updating on the initial reconstructed image until the number of updating times reaches a set threshold, so as to obtain a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be measured;
a volume fraction determining module 604, configured to determine a volume fraction of a target region of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be detected.
In an embodiment, the image update module 603 is specifically configured to:
determining an independent region in the initial reconstructed image based on a boundary region in the initial reconstructed image;
assigning the pixel parameters in each independent area, and updating the initial reconstructed image based on the assigned image parameters;
and if the updating times are smaller than a set threshold value, based on the projection image set of the updated initial reconstruction image in the set projection angle range, performing initial image reconstruction again, determining independent areas for the initial reconstruction image after the initial image reconstruction again, and assigning values to pixel parameters in each independent area to update the initial reconstruction image until the updating times reach the set threshold value, so as to obtain a final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
In an embodiment, the image update module 603 is specifically configured to:
acquiring the peak value of the gray value distribution histogram of each independent area;
and replacing the gray value of the pixel point in each independent area with the corresponding peak value.
In one embodiment, the volume fraction determination module 604 is specifically configured to:
and determining the volume fraction of the target area based on the ratio of the sum of the pixel points of the target area of the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected to the total number of the pixel points of the three-dimensional object to be detected.
In one embodiment, the apparatus further comprises: a correction module 605, the correction module 605 specifically configured to:
reconstructing based on the projection image set of each two-dimensional slice layer to obtain a three-dimensional model;
determining a first volume fraction of the target region based on the three-dimensional model;
acquiring a projection image set of each two-dimensional slice of the three-dimensional model in the set projection angle range, and determining a final reconstruction image corresponding to each two-dimensional slice of the three-dimensional model to obtain a second volume fraction of the target area;
and correcting the volume fraction based on the first volume fraction and the second volume fraction to obtain a corrected volume fraction.
In one embodiment, the apparatus further comprises: a component distinguishing module 606, wherein the component distinguishing module 606 is specifically configured to:
and carrying out component distinguishing on the three-dimensional object to be detected based on the gray values of the pixel points in the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected.
In one embodiment, the correction module 605 performs three-dimensional modeling on the projection image set of each two-dimensional slice based on a Filtered Back Projection (FBP) method to obtain the three-dimensional model.
In actual applications, the projection image acquisition module 601, the image reconstruction module 602, the image update module 603, the volume fraction determination module 604, the correction module 605, and the composition discrimination module 606 may be implemented by a processor in a volume fraction acquisition apparatus based on three-dimensional reconstruction. Of course, the processor needs to run a computer program in memory to implement its functions.
It should be noted that: in the volume fraction acquiring device based on three-dimensional reconstruction provided in the above embodiment, when volume fraction acquiring based on three-dimensional reconstruction is performed, only the division of the above program modules is taken as an example, and in practical applications, the above processing may be allocated to different program modules according to needs, that is, the internal structure of the device may be divided into different program modules to complete all or part of the above-described processing. In addition, the volume fraction acquiring device based on three-dimensional reconstruction and the volume fraction acquiring method based on three-dimensional reconstruction provided by the above embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.
Based on the hardware implementation of the program module, and in order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a volume fraction obtaining device based on three-dimensional reconstruction. Fig. 7 shows only an exemplary structure of the apparatus and not the entire structure, and a part of or the entire structure shown in fig. 7 may be implemented as necessary.
As shown in fig. 7, an apparatus 700 provided by an embodiment of the present invention includes: at least one processor 701, memory 702, user interface 703, and at least one network interface 704. The various components in the volume fraction acquisition device 700 based on three-dimensional reconstruction are coupled together by a bus system 705. It will be appreciated that the bus system 705 is used to enable communications among the components. The bus system 705 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various busses are labeled in figure 7 as the bus system 705.
The user interface 703 may include, among other things, a display, a keyboard, a mouse, a trackball, a click wheel, a key, a button, a touch pad, or a touch screen.
The memory 702 in the embodiment of the present invention is used to store various types of data to support the operation of the volume fraction acquiring apparatus based on three-dimensional reconstruction. Examples of such data include: any computer program for operating on a volume fraction acquisition device based on a three-dimensional reconstruction.
The volume fraction obtaining method based on three-dimensional reconstruction disclosed by the embodiment of the invention can be applied to the processor 701 or realized by the processor 701. The processor 701 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the volume fraction obtaining method based on three-dimensional reconstruction may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 701. The Processor 701 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 701 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software module may be located in a storage medium located in the memory 702, and the processor 701 reads information in the memory 702, and completes the steps of the volume fraction obtaining method based on three-dimensional reconstruction provided by the embodiment of the present invention in combination with hardware thereof.
In an exemplary embodiment, the volume fraction obtaining Device based on three-dimensional reconstruction may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable logic devices (P L D, Programmable L ic devices), Complex Programmable logic devices (CP L D, Complex Programmable L ic devices), FPGAs, general purpose processors, controllers, Micro Controllers (MCUs), microprocessors (microprocessors), or other electronic components, for performing the aforementioned methods.
The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic Random Access Memory (FRAM), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Dynamic Random Access Memory (DRAM), which may be of the type described by a Dynamic Random Access bus (SDRAM), or a Dynamic Random Access Memory (SDRAM), which may be of the type described by a Dynamic Random Access bus (SDRAM), or a Dynamic Random Access Memory (RAM), which may be of the type described by a Dynamic Random Access bus, or a Dynamic Random Access bus (SDRAM), or a Dynamic Random Access Memory (SDRAM), which may be of the type described by a Dynamic Random Access bus (SDRAM), or a Dynamic Access Memory (SDRAM), which may be of the type described by a Dynamic Access bus Access RAM, but is suitable for example, or a Dynamic Access RAM (SDRAM, or a Dynamic Access RAM).
In an exemplary embodiment, the embodiment of the present invention further provides a storage medium, specifically a computer storage medium, which may be a computer readable storage medium, for example, a memory 702 storing a computer program, which is executable by a processor 701 of a volume fraction acquiring apparatus based on three-dimensional reconstruction, so as to complete the steps described in the method of the embodiment of the present invention. The computer readable storage medium may be a ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM, among others.
It should be noted that: "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
In addition, the technical solutions described in the embodiments of the present invention may be arbitrarily combined without conflict.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A volume fraction obtaining method based on three-dimensional reconstruction is characterized by comprising the following steps:
acquiring a projection image set of each two-dimensional slice layer of a three-dimensional object to be detected in a set projection angle range, wherein the projection image set comprises projection images corresponding to different projection angles in the set projection angle range;
performing initial image reconstruction based on the projection image set corresponding to each two-dimensional slice layer to obtain an initial reconstruction image corresponding to each two-dimensional slice layer;
updating the image of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected;
and determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
2. The method according to claim 1, wherein the image updating the initial reconstructed image until the number of updating times reaches a set threshold value to obtain a final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be measured includes:
determining an independent region in the initial reconstructed image based on a boundary region in the initial reconstructed image;
assigning the pixel parameters in each independent area, and updating the initial reconstructed image based on the assigned image parameters;
and if the updating times are smaller than a set threshold value, based on the projection image set of the updated initial reconstruction image in the set projection angle range, performing initial image reconstruction again, determining independent areas for the initial reconstruction image after the initial image reconstruction again, and assigning values to pixel parameters in each independent area to update the initial reconstruction image until the updating times reach the set threshold value, so as to obtain a final reconstruction image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
3. The method of claim 2, wherein assigning pixel parameters in each independent area comprises:
acquiring the peak value of the gray value distribution histogram of each independent area;
and replacing the gray value of the pixel point in each independent area with the corresponding peak value.
4. The method of claim 1, wherein determining the volume fraction of the target region of the three-dimensional object to be measured based on the final reconstructed image corresponding to each two-dimensional slice of the three-dimensional object to be measured comprises:
and determining the volume fraction of the target area based on the ratio of the sum of the pixel points of the target area of the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected to the total number of the pixel points of the three-dimensional object to be detected.
5. The method of claim 1, further comprising:
reconstructing based on the projection image set of each two-dimensional slice layer to obtain a three-dimensional model;
determining a first volume fraction of the target region based on the three-dimensional model;
acquiring a projection image set of each two-dimensional slice of the three-dimensional model in the set projection angle range, and determining a final reconstruction image corresponding to each two-dimensional slice of the three-dimensional model to obtain a second volume fraction of the target area;
and correcting the volume fraction based on the first volume fraction and the second volume fraction to obtain a corrected volume fraction.
6. The method of claim 1, further comprising:
and carrying out component distinguishing on the three-dimensional object to be detected based on the gray values of the pixel points in the final reconstructed image of each two-dimensional slice layer of the three-dimensional object to be detected.
7. The method of claim 5, wherein reconstructing the set of projection images based on the two-dimensional slices to obtain a three-dimensional model comprises:
and carrying out three-dimensional modeling on the Projection image set of each two-dimensional slice layer based on a Filtered Back Projection (FBP) method to obtain the three-dimensional model.
8. A volume fraction acquisition apparatus based on three-dimensional reconstruction, comprising:
the projection image acquisition module is used for acquiring a projection image set of each two-dimensional slice layer of the three-dimensional object to be detected in a set projection angle range, wherein the projection image set comprises projection images corresponding to different projection angles in the set projection angle range;
the image reconstruction module is used for performing initial image reconstruction based on the projection image sets corresponding to the two-dimensional slice layers to obtain initial reconstruction images corresponding to the two-dimensional slice layers;
the image updating module is used for updating the images of the initial reconstructed image until the updating times reach a set threshold value, and obtaining a final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected;
and the volume fraction determining module is used for determining the volume fraction of the target area of the three-dimensional object to be detected based on the final reconstructed image corresponding to each two-dimensional slice layer of the three-dimensional object to be detected.
9. A volume fraction acquisition apparatus based on three-dimensional reconstruction, characterized by comprising: a processor and a memory for storing a computer program capable of running on the processor, wherein,
the processor, when executing the computer program, is adapted to perform the steps of the method of any of claims 1 to 7.
10. A storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the steps of the method of any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113052960A (en) * | 2021-03-25 | 2021-06-29 | 湖南大学 | Discrete algebra three-dimensional reconstruction method and system suitable for multi-component system and readable storage medium |
| CN113538372A (en) * | 2021-07-14 | 2021-10-22 | 重庆大学 | Three-dimensional target detection method and device, computer equipment and storage medium |
| CN117392316A (en) * | 2023-10-13 | 2024-01-12 | 清华大学 | Three-dimensional reconstruction method and device based on series of under-focus images |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113052960A (en) * | 2021-03-25 | 2021-06-29 | 湖南大学 | Discrete algebra three-dimensional reconstruction method and system suitable for multi-component system and readable storage medium |
| CN113538372A (en) * | 2021-07-14 | 2021-10-22 | 重庆大学 | Three-dimensional target detection method and device, computer equipment and storage medium |
| CN113538372B (en) * | 2021-07-14 | 2022-11-15 | 重庆大学 | Three-dimensional target detection method and device, computer equipment and storage medium |
| CN117392316A (en) * | 2023-10-13 | 2024-01-12 | 清华大学 | Three-dimensional reconstruction method and device based on series of under-focus images |
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