CN103218788B - A kind of measuring method of liver magnetic resonance R2* parameter - Google Patents
A kind of measuring method of liver magnetic resonance R2* parameter Download PDFInfo
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Abstract
A measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, comprising: (1) obtains magnetic resonance liver image, draws full liver area-of-interest; (2) the magnetic resonance liver image after denoising is obtained; Obtain each pixel grey scale in the full liver area-of-interest of magnetic resonance liver image after denoising again, the gray scale of each pixel and echo time are fitted in the first moment model formula (I) of Single-Index Model under non-central Chi noise effect, obtain full liver R2* and scheme; (3) the R2* value of full liver area-of-interest is divided into two classes, corresponds respectively to liver parenchyma and blood vessel; Liver parenchyma of reentrying area-of-interest; (4) calculate gray average, the echo time of each echo liver parenchyma area-of-interest, be fitted in formula (I), obtain final liver parenchyma R2* value.Method of the present invention can improve the degree of accuracy of transverse relaxation rate <b>R2*</bGreatT. GreaT.GT parameter and reproducible.
Description
Technical field
The present invention relates to magnetic resonance transverse relaxation parameter
r2*field of measuring technique, is specifically related to a kind of liver magnetic resonance transverse relaxation rate
r2*the measuring method of parameter.
Background technology
Magnetic resonance transverse relaxation rate R2* value (i.e. the inverse of T2 T2*) determination techniques, as the means of a kind of noninvasively estimating histoorgan particularly iron content of human tissue organ, become the main imaging diagnosis method of current liver iron overload.In the research of liver iron, normally first measure the R2* value of liver, recycle existing calibration function and R2* is changed into iron content to carry out iron content assessment.
Up to now, for the problem of the R2* value of measurement liver, main have two class methods.
The first is based on the little area-of-interest (regionofinterest of multiple liver, ROI), calculate the average gray value in the little area-of-interest of every echo, again the gray-scale value obtained and corresponding echo time are fitted to a suitable curve model, thus calculate R2* value and using the R2* value of this value as full liver.And liver iron is not be uniformly distributed in whole liver parenchyma in reality, the position that little area-of-interest is chosen and varying in size, can there is certain difference in the R2* obtained and the actual conditions of liver.Therefore, this based on local little area-of-interest replace the measuring method of whole liver often to exist sampling error is large, the inaccurate defect of test result.
The second is the full liver region of interest domain measurement R2* value based on whole liver.This method, because liver comprises abundant blood vessel, and the blood iron-holder that blood vessel comprises is little, R2* value is less, if do not got rid of, liver iron R2* estimated value can be caused on the low side, so liver parenchyma must be extracted exactly from full liver area-of-interest, the accuracy of guarantee measurement result.
Researcher is had to adopt the adaptive fuzzy clustering method based on gray scale to extract liver parenchyma (PositanoV; SalaniB, PepeA, SantarelliMF; DeMarchiD; RamazzottiA, FavilliB, CracoliciE; MidiriM; CianciulliP, LombardiM, LandiniL.ImprovedT2*assessmentinliverironoverloadbymagne ticresonanceimaging.MagnResonImaging2009; 27 (2): 188-197), this method only carries out cluster to a width echo, therefore for different echo cluster segmentation, liver parenchyma may be caused to extract result different.Such as, Palmieri etc. point out that some focuses are as liver's hemangioma, often when the echo time is larger just occur with the obvious signal contrast of liver parenchyma, at this moment just can not get rid of focus, obtain R2* also inaccurate.Also have researcher to carry out matching to each pixel single exponential model in whole liver ROI and obtain T2* figure; by getting a T2* threshold value, T2* is divided into two classes; corresponding to liver parenchyma and blood vessel (DengJ; RigsbyCK; SchoenemanS, BoylanE.AsemiautomaticpostprocessingofliverR2*measuremen tforassessmentofliverironoverload.MagnResonImaging2012; 30 (6): 799-806.).This kind of method, because magnetic resonance image (MRI) is always noisy, especially in strong noise high Fe content situation, the T2* value that individual element adopts single index model of fit to calculate is inaccurate, cause liver parenchyma to be extracted inaccurate.And due to the impact of partial volume effect, liver parenchyma and non-hepatic parenchymal T2* are distributed in histogram may not have clear and definite boundary, be difficult to definite threshold exactly in this case.And the selection of threshold value is also subjective, the result that operator's difference calculates also can differ greatly, not only transverse relaxation rate
r2*inaccurate and operation poor repeatability.
Therefore, not enough for prior art, provide one accurately can measure liver magnetic resonance transverse relaxation rate
r2*the measuring method of parameter is very necessary to overcome prior art deficiency.
Summary of the invention
The invention provides a kind of liver magnetic resonance transverse relaxation rate
r2*the measuring method of parameter, the method effectively can reduce the impact of noise, magnetic field bump and partial volume effect factor, can improve transverse relaxation rate
r2*the degree of accuracy of parameter, and method provided by the invention is reproducible.
Above-mentioned purpose of the present invention is realized by following technological means.
A measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, in turn includes the following steps:
(1), obtain magnetic resonance liver image, and draw full liver area-of-interest on obtained magnetic resonance liver image;
(2), denoising calculate full liver R2* and scheme;
Magnetic resonance liver image after denoising is obtained to magnetic resonance liver image denoising;
Obtain each pixel grey scale in the full liver area-of-interest of magnetic resonance liver image after denoising again, the echo time that the gray scale of each pixel is corresponding with each pixel is fitted in the first moment modular form (I) of Single-Index Model under non-central Chi noise effect, obtains full liver R2* and scheme;
......（I）；
In formula (I)
represent and ask expectation,
represent the gray-scale value of observation signal,
represent the standard variance of noise,
represent the number of receiving coil,
represent two factorial, namely
,
represent hypergeometry stream function,
represent the muting actual signal gray-scale value when echo time is 0,
represent the echo time,
represent transverse relaxation rate; Due to muting image
0 in image background regions, therefore
(3), liver parenchyma region is extracted;
The R2* value of the full liver area-of-interest adopting FCM Algorithms step (2) to be obtained is divided into two classes, corresponds respectively to liver parenchyma and blood vessel; Liver parenchyma of reentrying area-of-interest;
(4), liver parenchyma R2* value is calculated;
Calculate the gray average of each echo liver parenchyma area-of-interest, echo time, obtained hepatic parenchymal gray average and corresponding echo time are fitted in formula (I), obtain final liver parenchyma R2* value as liver magnetic resonance transverse relaxation rate R2* parameter.
Above-mentioned steps (1) specifically adopts many echo gradient echo sequence to obtain magnetic resonance liver image.
Above-mentioned steps (2) specifically adopts non-local mean filtering method to the magnetic resonance liver image denoising obtained.
Adopt in non local filtering method in above-mentioned steps (2), adopt following parameter: search box size is
, field window size is
, filtering parameter is 0.4 times of noise criteria variance.
Above-mentioned steps (3) also comprises carries out morphological operation to liver parenchyma area-of-interest, specifically utilizes structural unit to corrode liver parenchyma to obtain final liver parenchyma area-of-interest.
The measuring method of liver magnetic resonance transverse relaxation rate R2* parameter of the present invention, the method effectively can reduce the impact of noise, magnetic field bump and partial volume effect factor, can improve transverse relaxation rate
r2*the degree of accuracy of parameter, and method provided by the invention is reproducible.
Accompanying drawing explanation
The present invention is further illustrated to utilize accompanying drawing, but the content in accompanying drawing does not form any limitation of the invention.
Fig. 1 is the schematic flow sheet of the inventive method;
Fig. 2 is three the little area-of-interest schematic diagram drawn in many area-of-interests mROI method of contrast;
Fig. 3 is the full liver area-of-interest schematic diagram drawn in the inventive method;
Fig. 4 is for the inventive method is to the schematic diagram of the liver parenchyma area-of-interest (black represents blood vessel) that liver area-of-interest auto Segmentation complete in figure (3) obtains;
Fig. 5 is R2* value scatter diagram and the Blant-Atlman figure of method of the present invention and mROI method two kinds of methods;
Fig. 6 is the Blant-Altman figure of the interior repeatability of method of the present invention and mROI method two kinds of method observers;
Fig. 7 is the Blant-Altman figure of repeatability between method of the present invention and mROI method two kinds of method observers.
Embodiment
The invention will be further described with the following Examples.
embodiment 1.
A measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, in turn includes the following steps:
(1), adopt many echo gradient echo sequence to obtain magnetic resonance liver image, and draw full liver area-of-interest on obtained magnetic resonance liver image.Draw full liver area-of-interest by manual drawing, also automatically can be drawn by programmed control, also first automatically can be drawn by program and be undertaken finely tuning to improve precision by manual drawing again.
(2), adopt non-local mean filtering method to the magnetic resonance liver image denoising obtained and calculate full liver R2* and scheme;
Non-local mean filtering method is specifically adopted to obtain the magnetic resonance liver image after denoising to magnetic resonance liver image denoising; Obtain each pixel grey scale in the full liver area-of-interest of magnetic resonance liver image after denoising again, the echo time that the gray scale of each pixel is corresponding with each pixel is fitted in the first moment modular form (I) of Single-Index Model under non-central Chi noise effect, obtains full liver R2* and scheme;
In formula (I)
represent and ask expectation,
represent the gray-scale value of observation signal,
represent the standard variance of noise,
represent the number of receiving coil,
represent two factorial, namely
,
represent hypergeometry stream function,
represent the muting actual signal gray-scale value when echo time is 0,
represent the echo time,
represent transverse relaxation rate; Due to muting image
0 in image background regions, therefore
(3), liver parenchyma region is extracted;
The R2* value of the full liver area-of-interest adopting FCM Algorithms step (2) to be obtained is divided into two classes, corresponds respectively to liver parenchyma and blood vessel; Liver parenchyma of reentrying area-of-interest.
(4), liver parenchyma R2* value is calculated;
Calculate the gray average of each echo liver parenchyma area-of-interest, echo time, obtained hepatic parenchymal gray average and corresponding echo time are fitted in formula (I), using obtained liver parenchyma R2* value as liver magnetic resonance transverse relaxation rate R2* parameter.
Research shows, when liver deposition of iron is serious, noise is topmost influence factor, the present invention using the first moment of Single-Index Model under non-central Chi noise effect (formula (I)) as model of fit, can portray the impact of noise on R2* die-away curve more accurately, experiment proves that model of carrying can estimate R2* value more accurately.
First method of the present invention carries out pre-filtering to image, adopt noise correction first moment model of fit, reduce the impact of noise on R2*, and the fuzzy clustering algorithm extracting liver parenchyma employing is based on R2*, but not based on gradation of image, making to classify no longer affects by the unevenness in magnetic field, make use of the impact that operation operator reduces partial volume effect in addition, improve the accuracy that R2* measures, and greatly improve the repeatability of operation.
embodiment 2.
A measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, in turn includes the following steps.
(1), adopt many echo gradient echo sequence to obtain magnetic resonance liver image, and draw full liver area-of-interest on obtained magnetic resonance liver image.
Obtain magnetic resonance liver image by many echo gradient echo sequence method, there is the features such as applicability is strong, processing ease, with low cost, picking rate is fast.
It should be noted that, the method obtaining magnetic resonance liver image is not limited only to the many echo gradient echo sequence mode in the present embodiment, also can by single echo gather repeatedly etc. method.
(2), adopt non-local mean filtering method to the magnetic resonance liver image denoising obtained, concrete, adopt following parameter in non local filtering method: search box size is
, field window size is
, filtering parameter is 0.4 times of noise variance.
Calculate full liver R2* again to scheme, specifically: obtain each pixel grey scale in the full liver area-of-interest of magnetic resonance liver image after denoising, the echo time that the gray scale of each pixel is corresponding with each pixel is fitted in the first moment modular form (I) of Single-Index Model under non-central Chi noise effect, obtains full liver R2* and scheme;
In formula (I)
represent and ask expectation,
represent the gray-scale value of observation signal,
represent the standard variance of noise,
represent the number of receiving coil,
represent two factorial, namely
,
represent hypergeometry stream function,
represent the muting actual signal gray-scale value when echo time is 0,
represent the echo time,
represent transverse relaxation rate; Due to muting image
0 in image background regions, therefore
It should be noted that, the parameter adopted in non local filtering method is not limited only to above-mentioned numerical value, and user can be arranged according to specific needs flexibly, but best with this numerical result.
(3), liver parenchyma region is extracted;
The R2* value of the full liver adopting FCM Algorithms step (2) to be obtained is divided into two classes, corresponds respectively to liver parenchyma and blood vessel; Liver parenchyma of reentrying area-of-interest.FCM Algorithms is this area public office general knowledge, does not repeat them here.
Step (3) also comprises carries out morphological operation to liver parenchyma area-of-interest, specifically utilizes structural unit to corrode liver parenchyma to obtain final liver parenchyma area-of-interest.Owing to being positioned at the impact of pixel by partial volume effect at blood vessel and liver parenchyma edge, therefore morphological operation is carried out to liver parenchyma area-of-interest, utilize structural unit to corrode liver parenchyma, reduce the pixel by partial volume effect, obtain final liver parenchyma area-of-interest.
(4), liver parenchyma R2* value is calculated;
Calculate the gray average of each echo liver parenchyma area-of-interest, echo time, obtained hepatic parenchymal gray average and corresponding echo time are fitted in formula (I), obtain final liver parenchyma R2* value as liver magnetic resonance transverse relaxation rate R2* parameter.
Research shows, when liver deposition of iron is serious, noise is topmost influence factor, the present invention using the first moment of Single-Index Model under non-central Chi noise effect (formula (I)) as model of fit, can portray the impact of noise on R2* die-away curve more accurately, experiment proves that model of carrying can estimate R2* value more accurately.
First method of the present invention carries out pre-filtering to image, adopt noise correction first moment model of fit, reduce the impact of noise on R2*, and the fuzzy clustering algorithm extracting liver parenchyma employing is based on R2*, but not based on gradation of image, making to classify no longer affects by the unevenness in magnetic field, make use of the impact that operation operator reduces partial volume effect in addition, improve the accuracy that R2* measures, and greatly improve the repeatability of operation.
embodiment 3.
A measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, is measuring object with human liver, specifically comprises the steps.
Step 1, obtain 12 echo liver magnetic resonance images, its imaging parameters is set to: the echo time chooses 0.93,2.27,3.61,4.95,6.29,7.63,8.97,10.4,11.8,13.2,14.6 and 16ms respectively, repetition time is 200ms, thickness is 10mm, matrix size is 64 × 128, and flip angle is 20
o.
Step 2, on the liver magnetic resonance image of an echo wherein, gets the region of interest ROI of the suitable size in black background region (as 40 pixels), utilize formula as follows (
), calculate background noise standard variance.
Step 3, goes out full liver area-of-interest along liver image edge manual drawing, as shown in Figure 3.It should be noted that, the method for drawing full liver area-of-interest is not limited only to manual drawing, and other modes also can be adopted to draw, and automatically draws or drawn by other equipment as programmed control.
Step 4, by non-local mean denoising method, the liver magnetic resonance image after denoising is obtained to liver magnetic resonance image denoising, the optimum configurations that non-local mean denoising method adopts is: search window radius is 5, and field window radius is 1, and decay factor is 0.4 times of noise criteria variance.
Step 5, carries out matching by the first moment model of fit formula (I) under noise effect to each pixel after denoising in the full liver area-of-interest of step 4 and corresponding echo time and obtains full liver R2* and scheme.
In formula (I)
represent and ask expectation,
represent the gray-scale value of observation signal,
represent the standard variance of noise,
represent the number of receiving coil,
represent two factorial, namely
,
represent hypergeometry stream function,
represent the muting actual signal gray-scale value when echo time is 0,
represent the echo time,
represent transverse relaxation rate.
Step 6, is automatically divided into two classes to the full liver R2* value that step 5 obtains with FCM Algorithms: liver parenchyma and non-liver parenchyma (as blood vessel) part, thus obtains liver parenchyma area-of-interest.
Step 7, adopt radius that is smooth, plate-like be 1 structural unit etching operation is carried out to the liver parenchyma area-of-interest that step 6 obtains, remove by the liver parenchyma pixel of partial volume effect, improve the accuracy that liver parenchyma is extracted further.
Step 8, grey scale pixel value in liver parenchyma region of interest ROI in each echo is carried out Homogenization Treatments, by the first moment model of fit formula (I) under noise effect, matching is carried out to 12 gray averages and echo time again, calculate final R2* value as liver magnetic resonance transverse relaxation rate R2* parameter.
Research shows, when liver deposition of iron is serious, noise is topmost influence factor, the present invention using the first moment of Single-Index Model under non-central Chi noise effect (formula (I)) as model of fit, can portray the impact of noise on R2* die-away curve more accurately, experiment proves that model of carrying can estimate R2* value more accurately.
First method of the present invention carries out pre-filtering process to image, adopt noise correction first moment model of fit, reduce the impact of noise on R2*, and the fuzzy clustering algorithm extracting liver parenchyma employing is based on R2*, but not based on gradation of image, making to classify no longer affects by the unevenness in magnetic field.In addition the method also uses the impact that operation operator reduces partial volume effect, improves the accuracy that R2* measures, and greatly improves the repeatability of operation.
Method of the present invention is as follows hereinafter referred to as the methods experiment comparative result of SAPE method and the multiple little area-of-interest (multipleROIs, mROI) of existing employing.
For giving the liver parenchyma area-of-interest of mROI method extraction as a reference in Fig. 2, Fig. 3 is the full liver region of interest ROI that the first step of the present invention is extracted, Fig. 4 is that in the liver parenchyma region of interest ROI white wire of SAPE method of the present invention extraction, as can be seen from Figure 4 blood vessel is excluded entirely.
The mROI method that Fig. 5 gives method of the present invention and reference measures the comparison of 108 routine human liver R2* results, the result of these two kinds of methods has obvious correlativity (r=0.9960, P<0.001), and coefficient of variation CoV(coefficientofvariation) be 5.25%.
Fig. 6 gives same analyst under mROI two kinds of methods of method of the present invention and reference the consistance Blant-Altman figure (in observer, repeatability is analyzed) analyzing twice 108 routine human liver's data gained R2* values.Fig. 6 (a), (b) are the Blant-Altman figure of the inventive method SAPE and mROI method respectively, their coefficient of variation is 0.83%(r=0.9999 respectively, P<0.001), 3.63%(r=0.9980, P<0.001).
Under Fig. 7 gives method of the present invention and mROI two kinds of methods, different analyst schemes (between observer, repeatability is analyzed) the consistance Blant-Altman of 108 routine human liver's data processing gained R2* values respectively.Fig. 7 (a), (b) are the consistance of different analyst's gained R2* value under the inventive method SAPE and mROI method respectively, their coefficient of variation is 1.39%(r=0.9997 respectively, P<0.001), 6.28%(r=0.9940, P<0.001).
From above result table, the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter of the present invention can the R2* numerical value of Measurement accuracy liver, and substantially increase the repeatability that R2* measures.
It should be noted that, the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter of the present invention is not only applicable to the measurement of human liver's magnetic resonance transverse relaxation rate R2* parameter, is applicable to the measurement of other animal's liver magnetic resonance transverse relaxations rate R2* parameter yet.
Finally should be noted that; above embodiment is only in order to illustrate technical scheme of the present invention but not limiting the scope of the invention; although be explained in detail the present invention with reference to preferred embodiment; those of ordinary skill in the art is to be understood that; can modify to technical scheme of the present invention or equivalent replacement, and not depart from essence and the scope of technical solution of the present invention.
Claims (5)
1. a measuring method for liver magnetic resonance transverse relaxation rate R2* parameter, is characterized in that: in turn include the following steps:
(1), obtain magnetic resonance liver image, and draw full liver area-of-interest on obtained magnetic resonance liver image;
(2), denoising calculate full liver R2* and scheme;
Magnetic resonance liver image after denoising is obtained to magnetic resonance liver image denoising;
Obtain each pixel grey scale in the full liver area-of-interest of magnetic resonance liver image after denoising again, the echo time that the gray scale of each pixel is corresponding with each pixel is fitted in the first moment modular form (I) of Single-Index Model under non-central Chi noise effect, obtains full liver R2* and scheme;
（I）；
In formula (I)
represent and ask expectation,
represent the gray-scale value of observation signal,
represent the standard variance of noise,
represent the number of receiving coil,
represent two factorial, namely
,
represent hypergeometry stream function,
represent the muting actual signal gray-scale value when echo time is 0,
represent the echo time,
represent transverse relaxation rate; Due to muting image
0 in image background regions, therefore
(
);
(3), liver parenchyma region is extracted;
The R2* value of the full liver area-of-interest adopting FCM Algorithms step (2) to be obtained is divided into two classes, corresponds respectively to liver parenchyma and blood vessel; Liver parenchyma of reentrying area-of-interest;
(4), liver parenchyma R2* value is calculated;
Calculate the gray average of each echo liver parenchyma area-of-interest, echo time, obtained hepatic parenchymal gray average and corresponding echo time are fitted in formula (I), using obtained liver parenchyma R2* value as liver magnetic resonance transverse relaxation rate R2* parameter.
2. the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter according to claim 1, is characterized in that: described step (1) specifically adopts many echo gradient echo sequence to obtain magnetic resonance liver image.
3. the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter according to claim 1, is characterized in that: described step (2) specifically adopts non-local mean filtering method to the magnetic resonance liver image denoising obtained.
4. the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter according to claim 1, is characterized in that: adopt in non local filtering method in described step (2), adopt following parameter: search box size is 5
5, neighborhood window size is 1
1, filtering parameter is 0.4 times of noise criteria variance.
5. the measuring method of liver magnetic resonance transverse relaxation rate R2* parameter according to claim 1, it is characterized in that: described step (3) also comprises carries out morphological operation to liver parenchyma area-of-interest, specifically utilize structural unit to corrode liver parenchyma to obtain final liver parenchyma area-of-interest.
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| CN103714521B (en) * | 2013-12-30 | 2016-08-17 | 南方医科大学 | Liver R2* figure measuring method based on inquiry table |
| CA3012161C (en) | 2016-01-22 | 2022-05-31 | Synaptive Medical (Barbados) Inc. | Systems and methods for magnetic field-dependent relaxometry using magnetic resonance imaging |
| CN105608681B (en) * | 2016-02-14 | 2018-12-21 | 电子科技大学 | A kind of liver magnetic resonance R2*Parameter drawing drawing method |
| US20190328310A1 (en) * | 2016-11-07 | 2019-10-31 | Oxford University Innovation Limited | Correction method for magnetic resonance t1-mapping of visceral organs in the presence of elevated iron and elevated fat levels, and in the presence of off-resonance frequencies |
| CN110082696B (en) * | 2019-04-30 | 2021-06-08 | 上海东软医疗科技有限公司 | Imaging method and device of multi-echo sequence |
| CN113240078B (en) * | 2021-04-26 | 2024-03-19 | 南方医科大学 | Magnetic resonance R2 based on deep learning network * Parameter quantization method, medium and device |
| CN113674248B (en) * | 2021-08-23 | 2022-08-12 | 广州市番禺区中心医院(广州市番禺区人民医院、广州市番禺区心血管疾病研究所) | Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment |
| CN114186584B (en) * | 2021-12-06 | 2022-08-30 | 无锡鸣石峻致医疗科技有限公司 | Method and equipment for denoising magnetic resonance signal based on extended exponential model |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102116856A (en) * | 2010-12-30 | 2011-07-06 | 中国科学院深圳先进技术研究院 | Transverse relaxation time measuring method and system |
| WO2013036607A2 (en) * | 2011-09-06 | 2013-03-14 | University Of Florida Research Foundation, Inc. | Systems and methods for detecting the presence of anomalous material within tissue |
-
2013
- 2013-04-24 CN CN201310144276.2A patent/CN103218788B/en not_active Expired - Fee Related
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| CN102116856A (en) * | 2010-12-30 | 2011-07-06 | 中国科学院深圳先进技术研究院 | Transverse relaxation time measuring method and system |
| WO2013036607A2 (en) * | 2011-09-06 | 2013-03-14 | University Of Florida Research Foundation, Inc. | Systems and methods for detecting the presence of anomalous material within tissue |
Non-Patent Citations (1)
| Title |
|---|
| Improved MRI R2* Relaxometry of Iron-Loaded Liver with Noise Correction;Yanqiu Feng等;《Magnetic Resonance in Medicine 》;20130128;第70卷(第6期);1765–1774 * |
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