A machine learning method for determining a value for a magnetic resonance imaging (MRI) parameter, said value enabling a characterization of a biological tissue, the method comprising: - determining reference values for said MRI parameter from a group of objects, wherein a first MRI technique is used by an MRI system for determining for each object said reference value from a first set of data; - creating a learning dataset by associating for each object of the group of objects a second set of data and the reference value previously determined from the first set of data, wherein the second set of data is acquired by the MRI system according to a second MRI technique for determining values of the MRI parameter and is configured for enabling a determination of said MRI parameter; - using a machine learning algorithm, in particular implemented by the MRI system, trained on the learning dataset for determining a value of said MRI parameter, wherein the second set of data obtained for each of the objects is used as input in the machine learning algorithm and its associated reference value is used as output target for said machine learning algorithm; - determining a relationship between the second set of data and a value of the MRI parameter obtained for each object by training the machine learning algorithm on the learning dataset; - using said relationship for determining from another data set a value for the MRI parameter of a new object, wherein said another dataset has been obtained by the MRI system by means of the second MRI technique, wherein said MRI parameter is a T2 relaxation time, the method being characterized in that the first MRI technique comprises a single-echo spin-echo (SE) sequence. - determining reference values for said MRI parameter from a group of objects, wherein a first MRI technique is used by an MRI system for determining for each object said reference value from a first set of data; - creating a learning dataset by associating for each object of the group of objects a second set of data and the reference value previously determined from the first set of data, wherein the second set of data is acquired by the MRI system according to a second MRI technique for determining values of the MRI parameter and is configured for enabling a determination of said MRI parameter; - using a machine learning algorithm, in particular implemented by the MRI system, trained on the learning dataset for determining a value of said MRI parameter, wherein the second set of data obtained for each of the objects is used as input in the machine learning algorithm and its associated reference value is used as output target for said machine learning algorithm; - determining a relationship between the second set of data and a value of the MRI parameter obtained for each object by training the machine learning algorithm on the learning dataset; - using said relationship for determining from another data set a value for the MRI parameter of a new object, wherein said another dataset has been obtained by the MRI system by means of the second MRI technique, wherein said MRI parameter is a T2 relaxation time, the method being characterized in that the first MRI technique comprises a single-echo spin-echo (SE) sequence. <EOS>