Magnetic resonance imaging apparatus and image processing apparatus

1. A magnetic resonance imaging apparatus comprising:

a sequence controller that acquires k-space data corresponding to a predetermined quantity of encoding processes; and

an image generator that extracts a plurality of data sets arranged in a time series from the k-space data, selects a data set from among the extracted plurality of data sets so as to reduce an effect caused by a movement of a subject, and generates an image by using the selected data set.

2. The magnetic resonance imaging apparatus according to claim 1 , wherein the image generator extracts the plurality of data sets arranged in the time series, according to an order in which the k-space data is acquired.

3. The magnetic resonance imaging apparatus according to claim 2 , wherein the image generator extracts the plurality of data sets arranged in the time series, by gradually increasing a quantity of encoding processes for data included in each of the data sets, according to the order in which the k-space data is acquired.

4. The magnetic resonance imaging apparatus according to claim 1 , wherein the image generator calculates a function value between data sets and selects the data set from among the plurality of data sets on a basis of the calculated function values.

5. The magnetic resonance imaging apparatus according to claim 4 , wherein the image generator specifies, on the basis of the function values, a data set corresponding to a time at which the subject had a movement from among the plurality of data sets and selects such a data set that corresponds to a time earlier in the time series than the time corresponding to the specified data set.

6. The magnetic resonance imaging apparatus according to claim 5 , wherein the image generator selects such a data set that corresponds to a time earlier in the time series than the time corresponding to the specified data set and that has a largest quantity of encoding processes for data.

7. The magnetic resonance imaging apparatus according to claim 5 , wherein the image generator selects such a data set that corresponds to a time closer to a time when data at a center of a k-space is acquired than the time corresponding to the specified data set.

8. The magnetic resonance imaging apparatus according to claim 4 , wherein the image generator specifies, on a basis of the function values, a data set corresponding to a time at which the subject had a movement from among the plurality of data sets and selects such a data set that corresponds to a time later in the time series than a time corresponding to the specified data set.

9. The magnetic resonance imaging apparatus according to claim 8 , wherein the image generator selects such a data set that corresponds to a time later in the time series than the time corresponding to the specified data set and that has a largest quantity of encoding processes for data.

10. The magnetic resonance imaging apparatus according to claim 4 , wherein the image generator selects such a targeted data set for which a difference between the function value thereof and the function value of another data set having a smaller quantity of encoding processes than the targeted data set is equal to or smaller than a predetermined threshold value and which has a largest quantity of encoding processes for data.

11. The magnetic resonance imaging apparatus according to claim 4 , wherein the function value is an L1 norm of differences between the data sets.

12. The magnetic resonance imaging apparatus according to claim 1 , wherein the image generator selects a data set in such a range that is not affected by the movement while gradually accumulating data starting from a first point in time of a sampling process in a direction toward future, further selects a data set in such a range that is not affected by the movement while gradually adding data starting from a last point in time of the sampling process in a direction toward past, and generates the image by using one of the data sets.

13. The magnetic resonance imaging apparatus according to claim 1 , wherein, when acquiring the data corresponding to the predetermined quantity of encoding processes, the sequence controller acquires data in a center part of the k-space prior to data in a perimeter part of the k-space.

14. The magnetic resonance imaging apparatus according to claim 1 , wherein, when acquiring the data corresponding to the predetermined quantity of encoding processes, the sequence controller acquires data in a perimeter part of the k-space prior to data in a center part of the k-space.

15. The magnetic resonance imaging apparatus according to claim 1 , wherein the image generator causes a display to display a reconstructed image from a data set selected as a candidate from among the plurality of data sets and a reconstructed image from a data set that is not selected as a candidate, and further selects the data set by receiving a selection made by an operator.

16. An image processing apparatus comprising:

a storage that stores therein k-space data corresponding to a predetermined quantity of encoding processes acquired by a magnetic resonance imaging apparatus; and

an image generator that extracts a plurality of data sets arranged in a time series from the k-space data, selects a data set from among the extracted plurality of data sets so as to reduce an effect caused by a movement of a subject, and generates an image by using the selected data set.

17. A magnetic resonance imaging apparatus comprising:

a sequence controller that acquires k-space data corresponding to a predetermined quantity of encoding processes; and

an image generator that extracts a plurality of data sets arranged in a time series from the k-space data, selects a data set from among the extracted plurality of data sets on a basis of a movement of a subject, and generates an image by using the selected data set, wherein

the image generator extracts the plurality of data sets arranged in the time series, by gradually increasing a quantity of encoding processes for data included in each of the data sets.