Validation scheme for composing magnetic resonance images (MRI)
View Patent ↗Method and apparatus for determining the quality of alignment of a pair of volumes of data of medical images is disclosed. The method for validating the alignment includes selecting one or more points in the first volume and one or more points in the second volume, determining the average distance between the one or more points in the first volume and the one or more points in the second volume, determining a distortion category based on the average distance, determining an average noise level in the first and second volumes, and assigning a Q value indicative of the quality of the alignment based on the distortion category.
1. A method for validating an alignment of a first and second volume of data obtained during a medical imaging procedure, comprising the steps of:
selecting one or more points in the first volume and one or more points in the second volume;
determining an average Euclidean distance between the one or more points in the first volume and the one or more points in the second volume;
determining a distorted alignment category that provides a quantitative measure of alignment based on the average Euclidean distance; and
assigning a Q value indicative of a quality of the alignment based on the distorted alignment category, the steps being carried out by a processor for medical imaging, wherein the distorted alignment category is based on the average Euclidean distance as follows: if the average Euclidean distance is between 12 and 16, the distorted alignment category is Severe; if the average Euclidean distance is between 8 and 12, the distorted alignment category is Medium; if the average Euclidean distance is between 4 and 8, the distorted alignment category is moderate; if the average Euclidean distance is between 0 and 4, the distorted alignment category is Minimal.
2. The method as claimed in claim 1 , wherein there is a plurality of points selected in the first volume.
3. The method as claimed in claim 2 , wherein there is a plurality of points selected in the second volume.
4. The method as claimed in claim 1 , wherein a single point is selected in the first volume and a single point is selected in the second volume, and the average Euclidean distance is the Euclidean distance between the single point in the first volume and the single point in the second volume.
5. The method as claimed in claim 1 , further comprising determining a noise level from a background region in the first volume and assigning a Q value indicative of the quality of the alignment based on the distorted alignment category and on the noise level.
6. The method as claimed in claim 5 , wherein the Q value is determined in accordance with the following table:
Distortion
Noise
Q
Severe
Severe
48
Severe
Medium
52
Severe
Moderate
56
Severe
Minimal
60
Medium
Severe
60
Medium
Medium
64
Medium
Moderate
68
Medium
Minimal
72
Moderate
Severe
72
Moderate
Medium
76
Moderate
Moderate
80
Moderate
Minimal
84
Minimal
Severe
84
Minimal
Medium
88
Minimal
Moderate
92
Minimal
Minimal
96.
7. The method as claimed in claim 1 , further comprising:
determining a noise level from a background region in the first volume;
determining a noise level from a background region in the second volume;
determining an average of the noise level from the background region in the first volume and the noise level from the background region in the second volume; and
assigning a Q value indicative of the quality of the alignment based on the distorted alignment category and on the average noise level.
8. The method as claimed in claim 7 , further comprising determining a Q value for a plurality of pairs of volumes.
9. A system for validating an alignment of a first and second volume of data obtained during a medical imaging procedure, comprising:
an imaging device;
a processor for selecting one or more points in the first volume and one or more points in the second volume;
a processor for determining an average Euclidean distance between the one or more points in the first volume and the one or more points in the second volume;
a processor for determining a distorted alignment category that provides a quantitative measure of alignment based on the average Euclidean distance; and
a processor for assigning a Q value indicative of a quality of the alignment based on the distorted alignment category, wherein the distorted alignment category is based on the average Euclidean distance as follows: if the average Euclidean distance is between 12 and 16, the distorted alignment category is Severe; if the average Euclidean distance is between 8 and 12, the distorted alignment category is Medium; if the average Euclidean distance is between 4 and 8, the distorted alignment category is Moderate; if the average Euclidean distance is between 0 and 4, the distorted alignment category is Minimal.
10. The system as claimed in claim 9 , wherein there is a plurality of points selected in the first volume.
11. The system as claimed in claim 10 , wherein there is a plurality of points selected in the second volume.
12. The system as claimed in claim 9 , wherein a single point is selected in the first volume and a single point is selected in the second volume, and the average Euclidean distance is the Euclidean distance between the single point in the first volume and the single point in the second volume.
13. The system as claimed in claim 9 , further comprising means for determining a noise level from a background region in the first volume and assigning a Q value indicative of the quality of the alignment based on the distorted alignment category and on the noise level.
14. The system as claimed in claim 13 , wherein the Q value is determined in accordance with the following table:
Distortion
Noise
Q
Severe
Severe
48
Severe
Medium
52
Severe
Moderate
56
Severe
Minimal
60
Medium
Severe
60
Medium
Medium
64
Medium
Moderate
68
Medium
Minimal
72
Moderate
Severe
72
Moderate
Medium
76
Moderate
Moderate
80
Moderate
Minimal
84
Minimal
Severe
84
Minimal
Medium
88
Minimal
Moderate
92
Minimal
Minimal
96.
15. The system as claimed in claim 9 , further comprising:
means for determining a noise level from a background region in the first volume;
means for determining a noise level from a background region in the second volume;
means for determining an average of the noise level from the background region in the first volume and the noise level from the background region in the second volume; and
means for assigning a Q value indicative of the quality of the alignment based on the distorted alignment category and on the average noise level.
16. The system as claimed in claim 15 , further comprising determining a Q value for a plurality of pairs of volumes.
17. A method for validating an alignment of a first and second volume of data obtained during a medical imaging procedure, comprising the steps of:
selecting one or more points in the first volume and one or more points in the second volume;
determining an average distance between the one or more points in the first volume and the one or more points in the second volume;
determining a distortion category based on the average distance;
determining a noise level from a background region in the first volume and assigning a Q value indicative of a quality of the alignment based on the distortion category and on the noise level, the steps being carried out by a processor for medical imaging, and wherein
the distortion category is based on the average distance as follows: if the average distance is between 12 and 16, the distorted alignment category is Severe; if the average distance is between 8 and 12, the distortion category is Medium; if the average distance is between 4 and 8, the distortion category is Moderate; if the average distance is between 0 and 4, the distortion category is Minimal, wherein the noise level is categorized as Severe, Medium, Moderate or Minimal, and the Q value is determined in accordance with the following table:
Distortion
Noise
Q
Severe
Severe
48
Severe
Medium
52
Severe
Moderate
56
Severe
Minimal
60
Medium
Severe
60
Medium
Medium
64
Medium
Moderate
68
Medium
Minimal
72
Moderate
Severe
72
Moderate
Medium
76
Moderate
Moderate
80
Moderate
Minimal
84
Minimal
Severe
84
Minimal
Medium
88
Minimal
Moderate
92
Minimal
Minimal
96.
18. A system for validating an alignment of a first and second volume of data obtained during a medical imaging procedure, comprising:
a processor for selecting one or more points in the first volume and one or more points in the second volume;
a processor for determining an average distance between the one or more points in the first volume and the one or more points in the second volume;
a processor for determining a distortion category based on the average distance;
a processor for determining a noise level from a background region in the first volume and assigning a Q value indicative of a quality of the alignment based on the distortion category and on the noise level, and wherein
the distortion category is based on the average distance as follows: if the average distance is between 12 and 16, the distorted alignment category is Severe; if the average distance is between 8 and 12, the distortion category is Medium; if the average distance is between 4 and 8, the distortion category is Moderate; if the average distance is between 0 and 4, the distortion category is Minimal, wherein the noise level is categorized as Severe, Medium, Moderate or Minimal, and the Q value is determined in accordance with the following table:
Distortion
Noise
Q
Severe
Severe
48
Severe
Medium
52
Severe
Moderate
56
Severe
Minimal
60
Medium
Severe
60
Medium
Medium
64
Medium
Moderate
68
Medium
Minimal
72
Moderate
Severe
72
Moderate
Medium
76
Moderate
Moderate
80
Moderate
Minimal
84
Minimal
Severe
84
Minimal
Medium
88
Minimal
Moderate
92
Minimal
Minimal
96.