※基础研究
食品科学
2006, Vol. 27, No. 10
197
Reconstruction of Magnetic Resonance Image T2 State Mapping
Diagram of Cheese and Bread Samples Using Matlab 6.5 Software
ZHANG Jin-sheng1，LIN Xiang-yang1,2，QI Jin-ning3，RUAN Rong-sheng1,*
(1.Key Laboratory of Food Science, Ministry of Education, Nanchang University, Nanchang
330047, China；
2.Institute of Bioengineering, Fuzhou University, Fuzhou
350002, China；3.Department of Biosystem and
Agriculture, Minnesota University, 1390 Eckles Avenue St.Paul, MN
55108, USA)
Abstracts：The images with different Tau values were gained by using a spin3D sequence under low-field nuclear magnetic
resonance (NMR) image experiment. Invoking the program designed by ourselves, the magnetic resonance imaging (MRI) T2
mapping diagrams of cheese and bread samples' are reconstructed by software Matlab 6.5. The T2 distribution of samples were
observed obviously from the T2 state mapping diagram. The results further suggests that using the programs designed by software
Matlab 6.5 to reconstruct the T2 mapping diagrams is feasible.
Key words：NMR/MRI；T 2；T 2 mapping；cheese；reconstruction
应用Matlab 6.5软件对奶酪和面包样品的核磁共振
成像进行T2 分布重建的研究
张锦胜 1 ，林向阳 1 , 2 ，齐锦宁 3 ，阮榕生 1 , *
(1.南昌大学 食品科学教育部重点实验室，江西 南昌
330047；2.福州大学生物工程研究所，
福建 福州
350002；3.美国明尼苏达大学生态系统与农业工程系，美国明尼苏达州，St.Paul市, 55108)
摘 要：本文论述了采用低场核磁共振成像技术(magnetic resonance imaging, MRI)中的 spin3D 成像序列，采用
不同 Tau 值对奶酪和面包样品进行成像实验。应用 Matlab 软件编程对图像进行数据处理，并对 T2 分布进行重建，最
后得到 T 2 分布状态图像。为核磁共振技术在食品中的应用打下良好的基础。
关键词：核磁共振及其成像；自旋自旋弛豫时间；T 2 分布；奶酪；T 2 分布状态重建图
中图分类号：O657.2
文献标识码：A
文章编号：1002-6630(2006)10-0197-05
Nuclear magnetic resonance(NMR) and magnetic reso-
such as protein denaturation[1] and enzyme activity[2] and etc;
nance imaging(MRI) techniques are commonly applied in
moisture is the determining factor in rheological behavior[3]
the medical field. And with the rapid development of MRI
and is extensively involved in chemical, physical change.
relative technology, the prices of MRI equipments have been
The research on how moisture changes in the food system is
decreased so much that it is possible to be applied in other
very important, but not easy. MRI is a non-destructive and
research fields such as food science, agriculture and etc.
versatile technique, providing data on the same sample un-
Since MRI is based on the principals of proton movements,
der different parameters. Because of this apparent advantages
it has obvious advantages to be applied on studying the
in non-destructive characters, more and more food scientists
moisture in complex food systems. It is well known that
have shown the interesting of the new technique's applica-
moisture is one of the important factors in food processing
tion in food science. MRI has been used to study the drying
affecting final product characteristics. Moisture is a key
and hydration of several biological and food systems[4～10];
component which strongly influences chemical changes,
Recent research has verified that the visualization of water
收稿日期：2006-08-17
*通讯作者
基金项目：江西省主要学科带头人培养计划项目(Z02605)
作者简介：张锦胜( 1 9 7 1 - ) ，助理研究员，博士研究生，研究方向为核磁共振及其在食品科学中的应用。
198
2006, Vol. 27, No. 10
食品科学
distribution by MRI has undoubtedly great potential in
※基础研究
Density low
Density high
optimizing these food processes[11,12]. The spin-spin relaxation time (T2) is one of the important parameters of food
samples which can help suppose the molecular status of
water in the complex food system. The T2 mapping diagram
Cheese
can even help to study the change of food quality during
(highdensity)
storage. So how to obtain a T2 mapping state diagram is
Bread
(highdensity)
worthy to be studied profoundly. This presentation is study
on the method of gaining a T2 mapping state diagram by the
Fig.1
The slice of 3D image of cheese and bread
program designed by ourselves in software Matlab 6.5. The
primary object of this research was to develop a T2 mapping
technique using MRI in order to gain an insight into the T2
distributional characteristics of samples. This will be a good
base for the profound research on the shelf life of complex
food system.
1
1.1
Slice number Middle slice #17
Materials and Methods
Materials
Fig.2
Slices of an image displayed using IDL 5.6 software
(The white part is cheese, the dark part is the bread because it
The cheese and white bread purchased in supermarket
contain less moisture)
are used as the experimental samples. RINMR equipment
fabricated by resonance instruments Ltd is used for MRI
in a txt file with the name of Txxxx.txt where xxxx indicates the
image experiments. The spin3D sequence is used for image
value of Tau which was used to the acquired the image. In
with different Tau values.
the same way, open other images and save the slice with the
1.2
same slice number as above using the similar file names.
Experimental steps and results
NMR and MRI measurements were performed using the
Copy all the files into a folder named“C:＼MATLAB6p5
RI NMR/MRI spectroscope equipped with temperature con-
＼work＼T2mappingSlices”
. In this folder, the text files store
trolling device and a large bore NMR/MRI system. At first,
the data for the slices in a series of images acquired at Tau
put the sample in the bore of the MRI instrument. Adjust the
values of 3000, 3500, 4000, 4500 and 5000, respectively.
position of the sample in the bore and acquire an image of
In order to remove the noise signal, a threshold value
the sample by optimizing the sequence parameters using
should be obtained by visually checking the 2D slice using
Imageset and Spin3D pulse sequences respectively. Under
the function, ThreshholdCheck (file number, directory) with
imageset pulse sequence, find the smallest value of Tau so
two parameters. The parameter“directory”is the folder
that the D3 value remains the same or change a little by
name saved as aforementioned, and the other parameter
adjusting the 1D profile into the center of the window when
“filename”is a number representing the order of files in
the Tau value is increased. After that, running spin3D to
the folder. Generally taking 4 or 5 for the slice of the largest
acquire a series of images for the sample at different values
Tau value. The signal distribution is showed in Fig.3, and
of Tau, which should increase from the smallest one at an
rotating the 2D slice to Fig.4 and then obtain the noise level
interval of 400 or 500 us. One of the 3D images of bread and
as approximate0.4.
cheese sample is shown in Fig.1. The color scale represent
After gaining the slice signals in 3D distribution images
the increment of the proton density. From here, we can see
then calculate T2 mapping. Invoking function, T2 mapping
the spatial distribution of sample protons.
(threshold, leveloff, directory) (in Fig.5), was written to calcu-
Using IDL 5.6 software to open the spin3D image
late T2 mapping. Parameter“threshold”is obtained as
acquired by the smallest Tau value, and the 2D slices will
above; A large number is assigned to leveloff such as 100000
be displayed on the lower right corner. Select one slice
to reduce the large T2 values and balance the small T2 values;
(mostly the middle slice such as one in the red frame as
and directory is the same as in function threshholdcheck().
shown in Fig.2). Write down the slice number, save the slice
On the command window, type“T2=T2 mapping(0.4,100000,
※基础研究
食品科学
10
15
8
10
6
× 104
20
5
199
4
2
0
40
30
20
10
Fig.3
10
0 0
20
0
40
40
30
30
20
20
10
2D slice displayed using Matlab software
30
40
10
0 0
T2 mapping calculated using parameters of threshold=0.4,
Fig.6
20
18
16
14
12
10
8
6
4
2
0
leveloff=10^6
10
× 104
8
6
4
2
0
40
0 40
Fig.4
2006, Vol. 27, No. 10
5
10
15
20
25
30
35
Rotate the 2D slice to obtain the noise level
30
20
20
10
Fig.7
30
40
10
0 0
T2 mapping calculated using parameters of threshold=1,
as approximate 0.4
leveloff=10^6
× 104
2
1
0
35
30
40
25
30
20
15
20
10
10
5
0 0
Fig.8
T2mapping calculated using parameters of threshold=1,
leveloff=15000
Fig.5
Program of function T2 mapping()
'c:＼MATLAB6p5＼work＼T2mapping Slices/*.txt');”
, and the
window in Fig.6 appears which shows T2 mapping. The large
2.1
relation:
S= A e
T2 values occur at four sides due to noise.
Change the threshold to 1 to raise the threshold in order
to remove noise further. On the command window, type
“T 2 = T 2 m a p p i n g ( 1 , 1 0 0 0 0 0 , ' c : ＼ M A T L A B 6 p 5 ＼ w o r k ＼
of threshold=1, leveloff=10^6. Decrease leveloff to 15000. On
the command window, type“T2=T2 mapping(1,15000,'c:
＼MATLAB6p5＼work＼T2mappingSlices/*.txt');”
, and T2 distribution state mapping is displayed in Fig.8. From here we
can see the T2 distribution clearly.
−
TE
T2
where S is arbitrary signal magnitude, A is constant, and
TE is that is represented by Tau in this manual. The formula
can be converted to:
ln(S)=ln(A)-Tau/T2
T2mappingSlices/*.txt');”
, and T2 mapping is displayed in
Fig.7. From here, T2 mapping is calculated using parameters
Time constant of spin-spin relaxation
The time constant of spin-spin relaxation, T2 has a
ln(S) and Tau have a linear relationship. T2 can be
calculated from the slope of the relationship.
The values of T2 are measured in experiments using a
spin-echo pulse sequence, or an improved one such as carr
purcell meiboom gill (CPMG) sequence.
2.2
T2 mapping
Each 3D image of a sample can be acquired by using a
2
Discussion
spin-echo pulse sequence. The values of the signal magni-
200
2006, Vol. 27, No. 10
食品科学
※基础研究
tude of the image are in a 3D matrix. Each element in the 3D
fileN=strcat(temp3,char(fileNames(i)));
matrix represents a corresponding spatial pixel in the sample.
s=textread(fileN,'%f');
A series of images for the sample can be acquired using a
m=(length(s))^0.5;
spin-echo sequence at different values of Tau parameter.
r=reshape(s,m,m);
The T2 value for each spatial pixel of the sample can be
for j=1:m
calculated using the linear regress formula aforementioned
for k=1:m
between the log signal magnitude at the signal and the Tau
array3D(j,k,i)=r(j,k); %j=row, k=column, i=page
values.Therefore, A 3D T2 mapping can be calculated for the
end
whole sample. A 2D T2 mapping can be also calculated for a
end
slice in the sample.
end
In terms of the above principles, we design the programs
cut3D=AV3DcutThreshhold(threshhold,array3D);
in Matlab 6.5 to remove the noise and process the data and
TT2=T2Map(cut3D,off,off_flag, Tau);
gain the T2 distribution state mapping figure as following:
[row,col]=size(TT2);
Import data and process (% illustration)
figureName=strcat(experimentName,'__',sampleName);
%for each element, if＞threshhold, set it to 0, otherwise
figure('name',figureName);
keep it
surf(TT2);
%off: level if signal is greater than off
axis([0,row,0,col,0,off]);
function outp=T2mapping(threshhold, off, off_flag,
%TT2=Tau;
sampleName, experimentName)
if nargin ～=5
error('threshhold, off_level, off_flag, sampleName,
experimentName');
av1DProfile=average2Dto1D(TT2,'column');
fi gure Name =st rcat (exp erim ent Name ,'__ ',
sampleName,'_av1Dprofile');
figure('name',figureName);
end
[row,col]=size(av1DProfile);
%get all file names in the directory, which are storaged
plot(av1DProfile);
in fileNames
folderName=strcat('c:＼MATLAB6p5＼work＼',
experimentName,'＼',sampleName,'＼*.txt');
axis([0,col,0,off]);
fileWr=strcat('c:＼MATLAB6p5＼work＼',experimentName,
'＼',sampleName,'_av1Dprofile.xls');
files=dir(folderName);
temp11=strtok(folderName,'*');
[p,q]=size(files);
fileWr=strcat(temp11,sampleName,'.xls');
if p＜1
error('wrong folder name, or empty data
file');
temp1D(1)=cellstr(strcat(sampleName,
'_T2map_av1Dprofile'));
avL=size(av1DProfile)+1;
end
for i=2:avL
fori=1:p
temp1D(i)=cellstr(num2str(av1DProfile(i-1)));
fileNames(i)=cellstr(files(i).name);
end
end
my_wk1write(fileWr,av1DProfile,0,1);
%withdraw Tau values from the filenames, which are
outp=av1DProfile;
storage in Tau
fori=1:p
temp1=strtok(char(fileNames(i)),'.');
return;
2.3 Summary for obtaining a T2 mapping for a sample
In this study, the bread and cheese binary matrix
temp2=regexprep(temp1,'T','+','preservecase');
samples were used to obtain the T2 mapping state diagrams
Tau(i)=str2num(temp2);
by the Matlab 5.6 software. Experimental results demonstrated
end
that using the programs designed by software Matlab 6.5 to
%input the slices data
reconstruct the T2 mapping diagrams is feasible. This study
temp3=strtok(folderName,'*');
provides information about the T2 distribution in the samples.
fori=1:p
It is no doubt that MRI technique can be applied to investi-
※基础研究
食品科学
3
201
water in foods[M]. Boston, MA. Martinus Nijhoff Publishers, 1985.
gate the water behavior and diffusion between two phases of
[3]
bread and cheese in the future.
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Lai L S, Kokini J L. The effect of extrusion operation conditions on the
on-line apparent viscosity of 98% amylopection and 70% amylase corn
starches during extrusion[J]. J Rheol, 1990, 34: 1245-1266.
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[4]
T2 is one of the important parameters in NMR and MRI
techniques. Especially some scientists found out that it is
Wood Sci. Technol, 1986, 20: 229-233.
[5]
possible to use the change of T2 during food storage to
predict the shelf life of food products. More and more researchers show the interests of this possibility. The primary
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[6]
Menon R S, MacKay A L, Flibotte S, et al. Quantitative separation of
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[7]
Olson J R, Chang S J, Wang P C. Nuclear magnetic resonance imaging:
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Jenner C F, Xia Y, Eccles C D, et al. Circulation of water within whear
grain revealed by nuclear magnetic resonance micro-imaging[J]. Nature,
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[8]
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[9]
measurement of transient moisture profiles and structural changes in corn
strongly depends on the understanding of format saved in
the MRI equipment, it will be a good base of study on the
shelf life of complex food system. Gaining the T2 distribution
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imaging[J]. Cereal Chem, 1992, 69: 600-606.
[10]
evaluation of the Fickian model[J]. Drying Technol, 1992, (10): 295332.
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[2]
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(3):60-62.
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