CN103549953A - Method for extracting microwave detection breast model based on medical magnetic resonance imaging - Google Patents
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Abstract
The invention belongs to the technical field of biomedical detection, and relates to a method for extracting a microwave detection breast model based on medical magnetic resonance imaging. The method includes the steps: acquiring a T1 weighted magnetic resonance image of a breast portion; enhancing a boundary; performing gray discrete processing; calculating the water content of a tissue corresponding to each pixel for a thoracic gland portion in the magnetic resonance image by the aid of an image gray value; comparing the water content of the tissue corresponding to each pixel with typical water content data of each tissue of a normal human body, determining tissue information of each pixel and defining the pixel as an islet if the tissue information of the pixel cannot be determined; giving the same gray value to the pixels with the determined tissue information and belonging to the same tissue, and normalizing the gray of the magnetic resonance image according to the tissue information; corroding small discrete islets; building the breast model. A breast structure can be really simulated by the method.
Description
Affiliated technical field
The invention belongs to biomedical detection technique field, relate to a kind of extracting method of microwave sounding model.
Background technology
Breast tumor is the highest malignancy disease of women's sickness rate, and mortality rate occupies first of women's mortality of malignant tumors.The diagnosis of early stage breast tumor all has decisive significance for the survival rate at a specified future date that improves mastotic treatment rate and patient undoubtedly.The detection method of at present conventional breast carcinoma of early stage comprises mammography, ultrasonograph technology, computed tomography, nmr imaging technique, thermal imaging detection etc., but all there is certain shortcoming in all multi-methods, as human body produced to radiation injury, image contrast is low, expense is more high.The principle of ultra broadband Electromagnetic Wave Detection breast carcinoma is that different biological tissues are different to electromagnetic absorption, reflection and transmissison characteristic, and the electromagnetic field producing when the pulse signal of antenna transmission is propagated in mammary gland tissue can reflect the abundant information of malignant tissue.Simultaneously ultra-wideband microwave signal has that radiant power is low, the target information amount of carrying large, provides grade location and the advantage such as testing cost is lower, can be as the conventional means of early stage breast cancer.Before carrying out Clinical detection, the method need to be carried out a large amount of simulation studies.What initial research modeling adopted conventionally is block or hemispheric breast model, and this model I is comparatively simple for this technology.In order to carry out the simulation study of closing to reality more, how mammary gland is carried out to modeling most important.
List of references of the present invention is as follows:
[1]Y.L Zhang,W.Y.Liu,et al.”Enhancement of Human Cardiac DT-MRI Data Using Locallly Adaptive Filtering”ICSP2010Proceedings
[2]L.Wang,B.Blatel,et al.“Fully Automatic Breast Segmentation in3D Breast MRI”,ISBI2012Proceedings
[3] an ancient sacrificial utensil woods, NMR (Nuclear Magnetic Resonance)-imaging Xue， Higher Education Publishing House 2002 years
[4]S.A Huettel,A.W.Song and G.McCarthy,Functional Magnetic Resonance Imaging,Sinauer Associates Inc.2003
[5]R.F.Reinoso,B.A.Telfer and M.Rowland,“Tissue Water Content in Rats Measured by Desiccation”,Journal of Pharmacological and Toxicological Methods,Vol.38,No.2,Oct.1997
[6]I.C.Kiricuta,Jr and V.Simplaceanu,“Tissue Water Content and Nuclear Magnetic Resonance in Normal and Tumor Tissues”Cancer Research,Vol.35,May.1975
Summary of the invention
The object of this invention is to provide a kind of method of extracting breast model based on NMR (Nuclear Magnetic Resonance)-imaging (MRI) image, this model has comprised the various organization in breast, comprising: fat, thymus, chest fluid, skin etc.Because ultra-wideband microwave detection system needs to carry out a large amount of strict tests before practical application, therefore, with respect to comparatively simple model, this model is pressed close to real breast more.
Technical scheme of the present invention is as follows:
A method that detects breast model based on medical nmr Extraction of Image microwave, comprises the following steps:
1) obtain the T1 Weighted Kernel magnetic resonance image (MRI) of breast portion, and magnetic field intensity information and imaging radiofrequency signal cycle used used when obtaining imaging.
2) nuclear magnetic resonance image is carried out to border enhancement process;
3) image through border enhancement process carries out gray scale discrete processes: first according to imaging shape, find the chest body of gland part in nuclear magnetic resonance image, determine the gray value of this part.
4) for the chest body of gland part in nuclear magnetic resonance image, utilize gradation of image value, calculate the water content of the corresponding tissue of each pixel:
Wherein, T
rthe radiofrequency signal cycle while being NMR (Nuclear Magnetic Resonance)-imaging, V
graythe gray value of this pixel in nuclear magnetic resonance image, V
thymusthe gray value of thymus in nuclear magnetic resonance image, M
0the intensity of external magnetic field while being NMR (Nuclear Magnetic Resonance)-imaging.
5) after having calculated the water content of the corresponding tissue of all pixels, the typical moisture content data of each tissue of the water content of the corresponding tissue of each pixel and normal human are compared, determine the organizational information of each pixel, if can not determine the organizational information of pixel, be defined as isolated island;
6) for determining the pixel of organizational information, belong to its same gray value of giving of same tissue, the gray scale of nuclear magnetic resonance image is normalized by organizational information;
7) for the discrete isolated island of fritter, carry out corrosion treatment;
8) through 7) image after step process is that gray scale is discrete, one to one, the nuclear magnetic resonance image that boundary information is clear and definite, by this image vector, and turns to face territory by each molded tissue block, sets up breast model for gray scale and organizational information.
As preferred implementation, step 2) in, based on Hessian, strengthening sef-adapting filter, the method for utilizing gray scale derivative to strengthen, strengthens the region of grey scale change, makes the border of each tissue become clear.
Utilize the method, the breast model extracting based on MRI image is simulate breast structure truly, the propagation of analogue signal in breast comparatively truly in ultra-wideband microwave detection simulation, provides strong technical support for ultra-wideband microwave breast tumor detects.
Accompanying drawing explanation
Fig. 1. the MRI picture before processing.
Fig. 2. the MRI picture strengthening through border.
Fig. 3. Fig. 1 and the contrast of Fig. 2 concrete details, left is the figure after strengthening, the right side is former figure.
Fig. 4. the MRI picture after gray scale is discrete.
Fig. 5. the MRI picture after isolated island is eliminated.
Fig. 6. after vector quantization, import the sectional drawing in simulation software.
Fig. 7. the conventional model in the past using.
The specific embodiment
The present invention mainly gray scale based on MRI image and morphological image feature thereof processes.Realization extracts the concrete shape of each tissue and the function of position in breast from MRI image, finally according to emulation demand, is converted into corresponding standard storage form.Thereby for follow-up Electromagnetic Simulation provides comparatively real model, simultaneously also for clinical actual measurement provides good simulation comparison and reference.Mainly be divided into following four steps:
1. border strengthens
In tradition MRI image, due to noise, the restriction of the reasons such as image resolution ratio is lower, differentiation for each organizational boundary in mammary gland is not clearly, although each is organized in gray value difference in MRI image, because border is not obvious, cannot carry out effective shape localization and division, as shown in fig. 1, this is the boundary of breast tissue skin, and not good enough definition has affected boundary alignment.For can be correctly and effectively distinguish various organization, first need border locate accurately and identify.At present, for the organizational boundary in organism, strengthen and have many methods, this programme to utilize Hessian enhancing sef-adapting filter to strengthen image boundary in the world, referring to document [1] and [2].This kind of method is mainly the gray scale directional derivative based on image, can, under less amount of calculation, obtain good image reinforced effects.In this programme after this step process, it is comparatively strong that the grey scale change at image boundary place becomes, so image boundary becomes clear, and be easy to identification, Fig. 2 has shown the image boundary after border strengthens, the details picture that before and after Fig. 3 has provided and processed, both borders change.
2. gray scale is discrete
After obtaining obvious border, can extract each and organize outside profile.But at organization internal due to noise, muscular movement, the problem of imaging diplopia etc., same tissue there will be different gray values, brings difficulty in subsequent simulation the tissue characteristics (comprising electrology characteristic, physical characteristic etc.) that defines each tissue according to gray scale.Therefore in second step, need to make a kind of tissue for a gray scale organizing gray scale to carry out discretization processing, just be convenient to the assign operation in subsequent simulation.By rational setting discrete threshold values, in conjunction with parts of images profile definite in the first step, can carry out the adjustable discretization of precision at each organization internal and process.
The concrete foundation of carrying out discretization according to gray scale is as follows:
First, clinical MRI provides information by water proton and carries out image-forming diagnose [3].Water characteristic in human body comprises following 3 points: Density Distribution, existence and motion conditions.In the imaging of MRI chest region, comparatively conventional T1 formation method has following empirical equation to characterize the linearity dependence of T1 time to tissue water content:
ρ＝0.65+0.126T
1 (1)
Wherein, ρ is the water content of corresponding tissue, T
1it is the MRI test T1 time of this tissue.
Again due in follow-up imaging process, the relation of T1 time and picture contrast be expressed from the next [4]:
Wherein, C
aB(Contrast between A and B) is the ratio of the MRI gradation of image value at aminoacyl site and B position.M
0Aand M
0Bthe size of external magnetic field while referring to respectively aminoacyl site and the imaging of B position, for routine MRI imaging, external magnetic field is approximately fixed value in same imaging process, therefore in follow-up formula, do not distinguish M
0Aand M
0B, think that it is same value.T
rbe the repetition time of MRI pulse, in same MRI picture, it is fixing that the pulse of employing is, therefore its repetition time is also the same.T
1Aand T
1Bit is the T1 time at aminoacyl site and B position.
Comprehensive (1) and (2) formula, the pass that we can derive the difference of tissue water density and MRI picture contrast is:
Wherein, ρ
aand ρ
bthe tissue water density at aminoacyl site and B position.
Secondly, due to less about the data of tissue water content, this patent adopt be mouse tissue water content table [5] as a reference, as seen from table, although lung, the viscera tissue water content such as heart are very approaching, but the skin (Skin) that chest MRI image is related, thymus (Thymus), the water content difference at the positions such as skeleton (Bone) and fat (Adipose) is larger, and all below 80%.Therefore, directly using-system water content is carried out the discretization of gray value.
Meanwhile, for water content and the T1 time of tumor, existing data is as listed in [6].According to this document, the water content of tumor tissues is generally greater than general tissue, has the tumor tissues water content of data all more than 80%, simultaneously because the water in tumor tissues exists mainly with irreducible water form, therefore that the T1 time can become is longer.In other words, for the tissue of pathological changes, its water content and T1 time are all higher than normal structure, and difference of them is larger.Therefore in follow-up study, utilize gray scale also can rationally distinguish tumor tissues.
Afterwards, with formula (3), ask the gray value of each tissue to need a gray value reference, could ask for gray scale actual value by grey-scale contrast.From the stability of tissue property, consider, we choose thymus part gray scale that gray-value variation is less as gray value reference.
Due to
Obtain thus usining thymus gray scale and ask as reference the formula of respectively organizing gray value:
Wherein, V
graythe gray value of tissue to be asked, V
skinbe the fatty tissue gray value in existing MRI image, ρ is the water content of tissue to be asked.
(4) thus, anti-release determines that by gray value the formula of tissue water content is as follows:
Because the gray value of actual tissue can cause a little error because of imaging noise and image error, in the correspondence of historical facts or anecdotes border, that tissue that the data that for the gray value calculating, getting provides in [5] approach the most carries out correspondence.
After having judged tissue, for the ease of follow-up image, process, the gray scale of same tissue is adjusted to identical value, like this, in figure, the gray value of each point can a unique corresponding relevant tissue.In subsequent simulation, according to this gray value, also can rationally give model relevant position rational electrology characteristic value.
Pay particular attention to, the gray value after adjustment is the gray value that calculates of typical moisture content of getting each tissue at present, and therefore under current this algorithm, the gray value after discrete is also corresponding with water content, and corresponding relation as shown in Equation (5).
The image of Fig. 4 for processing through this method, can see discretization of its gray scale, makes each concrete gray scale correspondence concrete tissue, as large-area light-colored part correspondence in figure fatty tissue of breast.
Committed step and the tissue for Fig. 4, processed are below divided foundation:
According to the gray value of Fig. 2 and image outline, can obtain V
thymusbe 60.Middle thoracic cavity part gray value is 19, M when this MRI figure tests again
0and T
rbe respectively 0.5Tesla, 1s.
Therefore calculate according to (5), this position water content is about 0.78, approaches thymus partially aqueous amount most, is thymus therefore define this part, subsequent treatment unification is adjusted into typical thymus gray value.
Parts of skin gray value is 82 left and right again, and ρ is in 0.58 left and right, the most approaching with skin as calculated.
Finally, according to above-mentioned steps, obtain the gray scale for this MRI---the organizational structure criteria for classifying.
| Tonal range is (by 8 gray scales | Corresponding tissue (English) | Organize typical moisture content (%) |
| Meter) | ||
| 255-100 | Fat (adipose) | 18.3 |
| 99-78 | Skin (skin) | 65.1 |
| 77-39 | Thymus (thymus) | 77.6 |
| 38-0 | Chest fluid (hydrothorax) | 97.3 |
3. isolated island is eliminated
After gray scale is discrete, due to the difference of threshold value, may there is isolated island in the image inside after discretization, as shown in Figure 4.The reason that these isolated islands produce mainly contains two kinds: the one, and because the signal at this place disturbs the tonal range that has departed from more by force conventional organization.The 2nd, the organization internal combination causing due to threshold value value deviation is incomplete.These two kinds of corresponding material objects of isolated island are organized in essence all has identical characteristic with surrounding tissue, therefore, need to eliminate these isolated islands.Isolated island is eliminated the algorithm that has had a lot of maturations.Directly adopt conventional caustic solution in computer graphics herein, the discrete isolated island of fritter is carried out to corrosion treatment.After corrosion, fritter isolated island disappears, and Fig. 5 has shown the associated picture after isolated island is eliminated.
4. standardization
In order to mate the demand of different simulation softwares, the image of processing through above-mentioned steps need to carry out corresponding processing.This programme provides the function of normal vector figure output.The model that has met different software with this public Graphic exchange standard form of vectogram imports demand.The vectogram that imports to concrete simulation software can be realized and give different electrology characteristic values to each piecemeal according to the difference of its piecemeal, thereby the model importing is accurately reliable from the angle of phantom.Fig. 6 has shown that dependent vector figure imports the result after simulation software, and in figure, the color lump of different colors represents the tissue of different electrology characteristics.With models such as original simple semicircles, compare (Fig. 7), this model importing based on MRI image is the shape of closing to reality mammary gland tissue more.
Claims (2)
1. based on medical nmr Extraction of Image microwave, detect a method for breast model, comprise the following steps:
1) obtain the T1 Weighted Kernel magnetic resonance image (MRI) of breast portion, and magnetic field intensity information and imaging radiofrequency signal cycle used used when obtaining imaging.
2) nuclear magnetic resonance image is carried out to border enhancement process;
3) image through border enhancement process carries out gray scale discrete processes: first according to imaging shape, find the chest body of gland part in nuclear magnetic resonance image, determine the gray value of this part.
4) for the chest body of gland part in nuclear magnetic resonance image, utilize gradation of image value, calculate the water content of the corresponding tissue of each pixel:
Wherein, T
rthe radiofrequency signal cycle while being NMR (Nuclear Magnetic Resonance)-imaging, V
graythe gray value of this pixel in nuclear magnetic resonance image, V
thymusthe gray value of thymus in nuclear magnetic resonance image, M
0the intensity of external magnetic field while being NMR (Nuclear Magnetic Resonance)-imaging.
5) after having calculated the water content of the corresponding tissue of all pixels, the typical moisture content data of each tissue of the water content of the corresponding tissue of each pixel and normal human are compared, determine the organizational information of each pixel, if can not determine the organizational information of pixel, be defined as isolated island;
6) for determining the pixel of organizational information, belong to its same gray value of giving of same tissue, the gray scale of nuclear magnetic resonance image is normalized by organizational information;
7) for the discrete isolated island of fritter, carry out corrosion treatment;
8) through 7) image after step process is that gray scale is discrete, one to one, the nuclear magnetic resonance image that boundary information is clear and definite, by this image vector, and turns to face territory by each molded tissue block, sets up breast model for gray scale and organizational information.
2. the method that detects breast model based on medical nmr Extraction of Image microwave according to claim 1, it is characterized in that, step 2) in, based on Hessian, strengthen sef-adapting filter, the method of utilizing gray scale derivative to strengthen, region to grey scale change strengthens, and makes the border of each tissue become clear.
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| CN115115770A (en) * | 2021-03-22 | 2022-09-27 | 天津大学 | Three-dimensional electromagnetic simulation breast model construction method based on MRI (magnetic resonance imaging) image |
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| CN114820605B (en) * | 2022-06-28 | 2022-09-20 | 广州永士达医疗科技有限责任公司 | Eustachian tube OCT image recognition processing method and device |
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