Magnetic resonance imaging apparatus and magnetic resonance image processing method
Disclosed are a method for processing a magnetic resonance (MR) image of a dynamic object and an MRI apparatus. The method includes receiving, from the dynamic object, a plurality of MR signals that correspond to a plurality of time sections and a plurality of slices, generating a plurality of MR images by using the plurality of MR signals, performing segmentation of each of the plurality of MR images into a plurality of regions, determining whether a segmentation error occurs in each of the plurality of MR images, and arranging the plurality of MR images to correspond to the respective time sections and the respective slices to display a matrix image, based on a result of the determining.
1. A method of processing a magnetic resonance (MR) image of a dynamic object, the method comprising:
receiving, from the dynamic object, a plurality of MR signals corresponding to a plurality of time sections and to a plurality of slices;
generating a plurality of MR images, based on the plurality of MR signals;
performing a segmentation of each of the plurality of MR images into a plurality of regions;
determining whether a segmentation error of the segmentation occurs in each of the plurality of MR images, by calculating, for each of the plurality of MR images, a segmentation error probability, based on a difference between a size of the dynamic object in a respective one of the plurality of MR images and a size of the dynamic object in a respective previous one of the plurality of the MR images; and
displaying a matrix image comprising the plurality of MR images that is arranged to respectively correspond to the plurality of time sections and the plurality of slices, a color and a transparency of each of the plurality of MR images being variably displayed to indicate a result of the determining of whether the segmentation error occurs in a respective one of the plurality of MR images.
2. The method of claim 1 , wherein the determining comprises calculating, for each of the plurality of MR images, the segmentation error probability with respect to the performed segmentation.
3. The method of claim 2 , wherein the displaying comprises displaying the matrix image, based on the calculated segmentation error probability for each of the plurality of MR images.
4. The method of claim 3 , wherein the determining comprises:
determining that the segmentation error occurs in a first MR image for which the calculated segmentation error probability is greater than or equal to a predetermined reference value, among the plurality of MR images; and
determining that the segmentation error does not occur in a second MR image for which the calculated segmentation error probability is less than the predetermined reference value, among the plurality of MR images, and
wherein the displaying further comprises displaying the first MR image, based on the determining that the segmentation error occurs in the first MR image.
5. The method of claim 3 , wherein the displaying comprises any one or any combination of changing a color of the matrix image, based on the calculated segmentation error probability for each of the plurality of MR images, changing a contrast of the matrix image, based on the calculated segmentation error probability for each of the plurality of MR images, and adding a predetermined mark to the matrix image.
6. The method of claim 1 , further comprising determining whether to correct the matrix image, based on a result of the determining of whether the segmentation error occurs.
7. The method of claim 6 , further comprising correcting the matrix image, based on a result of the determining of whether to correct the matrix image.
8. The method of claim 7 , wherein the determining comprises determining that the segmentation error does not occur in a first MR image among the plurality of MR images, and
the correcting comprises correcting the matrix image with reference to the first MR image in which the segmentation error is determined to not occur.
9. The method of claim 7 , wherein the correcting further comprises correcting the matrix image, based on the segmentation error probability of each of the plurality of MR images.
10. The method of claim 1 , wherein the displaying comprises correcting and displaying the matrix image, based on a result of the determining.
11. A non-transitory computer-readable storage medium storing a program for executing the method of claim 1 .
12. A magnetic resonance imaging (MRI) apparatus for imaging a dynamic object, the MRI apparatus comprising:
an image processor configured to:
receive, from the dynamic object, a plurality of MR signals corresponding to a plurality of time sections and to a plurality of slices;
generate a plurality of MR images, based on the plurality of MR signals;
segment each of the plurality of MR images into a plurality of regions; and
determine whether a segmentation error of the segmenting occurs in each of the plurality of MR images, by calculating, for each of the plurality of MR images, a segmentation error probability, based on a difference between a size of the dynamic object in a respective one of the plurality of MR images and a size of the dynamic object in a respective previous one of the plurality of the MR images; and
a display,
wherein the image processor is further configured to control the display to display a matrix image comprising the plurality of MR images that is arranged to respectively correspond to the plurality of time sections and the plurality of slices, a color and a transparency of each of the plurality of MR images being variably displayed to indicate a result of the determining of whether the segmentation error occurs in a respective one of the plurality of MR images.
13. The MRI apparatus of claim 12 , wherein the image processor is further configured to calculate the segmentation error probability with respect to the segmenting.
14. The MRI apparatus of claim 13 , wherein the display is further configured to display the matrix image, based on the calculated segmentation error probability for each of the plurality of MR images.
15. The MRI apparatus of claim 13 , wherein the image processor is further configured to:
determine that the segmentation error occurs in a first MR image for which the calculated segmentation error probability is greater than or equal to a predetermined reference value, among the plurality of MR images;
determine that the segmentation error does not occur in a second MR image for which the calculated segmentation error probability is less than the predetermined reference value, among the plurality of MR images; and
control the display to display the first MR image, based on the determining that the segmentation error occurs in the first MR image.
16. The MRI apparatus of claim 12 , wherein the image processor comprises a corrector configured to:
determine whether to correct the matrix image, based on a result of the determining of whether the segmentation error occurs; and
correct the matrix image, based on a result of the determining of whether to correct the matrix image.
17. The MRI apparatus of claim 16 , wherein the image processor is further configured to determine that the segmentation error does not occur in a first MR image among the plurality of MR images, and
the corrector is further configured to correct the matrix image with reference to the first MR image in which the segmentation error is determined to not occur.
18. The MRI apparatus of claim 17 , wherein the corrector is further configured to correct the matrix image, based on a segmentation error probability of each of the plurality of MR images.
19. The MRI apparatus of claim 12 , wherein the display is further configured to correct and display the matrix image, based on a result of the determining.