This is an exciting and useful problem. Your question is very general and is complex to provide a satisfactory answer. Maybe you should elaborate a bit more on your problem.
There are several methods to obtain maps of T1 and T2. But more than a tool of Matlab , you need to design and select your experiment. I recommend taking into account, among other things:
1 - Pulse Sequence . The equations describing the variation of the intensity of a pixel is different in each case .
Spin Echo ( SE)
a) Calculation of T1: TR change with a fixed TE .
b ) Calculation of T2: TE change with a fixed TR .
IR pulse sequence :
a) Calculation of T1: IT change and fixed TR and TE .
Gradient Echo (GRE) . Change the FA and hold fixed TR and TE .
2 - Select the calculation method : generally using optimization methods ( Levenberg-Marquardt ) .
Anyway , your question has various answers depending on many things. I have some Matlab functions for T1 and T2 map calculation using the DICOM images. I can give you is the if you need them.
If you want more help you can contact my mail: evelio.gonzalez @ cigb.edu.cu
I am enclosing an article that can guide you solve your problem .
This is an exciting and useful problem. Your question is very general and is complex to provide a satisfactory answer. Maybe you should elaborate a bit more on your problem.
There are several methods to obtain maps of T1 and T2. But more than a tool of Matlab , you need to design and select your experiment. I recommend taking into account, among other things:
1 - Pulse Sequence . The equations describing the variation of the intensity of a pixel is different in each case .
Spin Echo ( SE)
a) Calculation of T1: TR change with a fixed TE .
b ) Calculation of T2: TE change with a fixed TR .
IR pulse sequence :
a) Calculation of T1: IT change and fixed TR and TE .
Gradient Echo (GRE) . Change the FA and hold fixed TR and TE .
2 - Select the calculation method : generally using optimization methods ( Levenberg-Marquardt ) .
Anyway , your question has various answers depending on many things. I have some Matlab functions for T1 and T2 map calculation using the DICOM images. I can give you is the if you need them.
If you want more help you can contact my mail: evelio.gonzalez @ cigb.edu.cu
I am enclosing an article that can guide you solve your problem .
I agree with Dr. Gonzalez that the most important considerations are in the data acquisition. However, I don't think that the variable flip angle technique is ideal for a T1 measurement because of its dependence on obtaining a uniform B1 field across the sample, and because of its relatively limited dynamic range. The VFA technique's main advantage is speed. However, if you want to use VFA, take a few acquisitions with a different TR. That way you can estimate the variation in B1.
Inversion recovery techniques, particularly Look-Locker techniques, have good dynamic range and, if the inversion is accomplished with an adiabatic inversion, are insensitive to variations in B1. See the following reference: 1. Gelman N, Ewing JR, Gorell JM, Spickler EM, Solomon EG. Interregional variation of longitudinal relaxation rates in human brain at 3.0 T: relation to estimated iron and water contents. Magn Reson Med. 2001;45(1):71-9. PubMed PMID: 11146488.
Analysis of T1 data is fairly straightforward. I like Levenberg-Marquardt for its stability and speed. Remember that one has to estimate or fix a number of variables - T1, M0, theta, and background magnitude. The background magnitude is tricky because the noise in MRI magnitude images is Rician. One of the things you find as you go along is that estimating background may be the most difficult part of the calculation. However, most approaches simply ignore the problem and produce biased estimates.
As for T2 - again, the main problem is acquiring reliable data, mainly because of B1 inhomogeneities. Use CPMG pulse sequences to ameliorate the problems with inexact 180 degree refocusing pulses. Curve fitting is relatively straightforward, since only M0, T2, and background have to be estimated - you can do that with a log transform of the data after background correction followed by a linear regression. Again, background estimate and Rician noise will bias the answer.
As for MR fingerprinting - not recommended for people asking about the basics of estimating T1 and T2. It seems to me that, because of the way that the data gets acquired, there's a very strong dependency on knowing exactly what the B1 field is at every point in the sample. One has to know that in order to back-calculate the trajectory of the magnetization in k-space, so that the T1 and T2 values can be estimated from a look-up table.
Hello Prof. James. Could you send me a copy of his work "Interregional variation of longitudinal relaxation rates in human brain at 3.0 T: relation to iron and water contents Estimated Magn Reson Med 2001; 45 (1):.. 71-9 PubMed PMID: 11146488.. "