Methods of reducing motion artifacts for optical coherence tomography angiography
A method for reducing motion artifacts in optical coherence tomography (OCT) angiography images is disclosed. The method is applied to the intensity or complex OCT data prior to applying the motion contrast analysis and involves determining sub-pixel level shifts between at least two B-scans repeated approximately at the same location and applying the sub-pixel level shifts to the B-scans to be able to correct for motion and accurately determine motion contrast signal. A preferred embodiment includes the use of 2D cross correlations to register a series of B-scans in both the axial (z-) and lateral (x-) dimensions and a convolution approach to achieve sub-pixel level frame registration.
1. A method to reduce the effects of motion in functional optical coherence tomography (OCT) imaging of a sample, said method comprising:
collecting a cluster of OCT B-scans of the sample with an OCT system, said cluster containing at least two B-scans, wherein at least two B-scans have an overlap of greater than 80%;
calculating displacements in two dimensions between the B-scans in the cluster;
registering the B-scans in the cluster using the calculated displacements;
analyzing the registered cluster to obtain functional information of the sample; and
storing or displaying the functional information.
2. A method as recited in claim 1 , in which the sample is a human eye.
3. A method as recited in claim 1 , in which the analyzing step includes applying an optical microangiography (OMAG) technique to the registered cluster.
4. A method as recited in claim 1 , in which the registering step is carried out in the depth structure domain.
5. A method as recited in claim 1 , in which the displacements are calculated on intensity B-scan data.
6. A method as recited in claim 1 , in which the displacements are calculated on complex B-scan data.
7. A method as recited in claim 1 , in which the calculating step is performed by taking cross-correlations between sub-regions of the B-scans in the cluster.
8. A method as recited in claim 1 , in which the registering step involves creating delta functions from the displacements and convolving the delta functions to the B-scans to be registered.
9. A method as recited in claim 1 , in which upsampling is used in the calculating step to improve the accuracy of the calculated displacements.
10. A non-transitory computer-readable medium storing a program which upon execution by a computer causes the computer to execute each step of an analysis method of an optical coherence tomography system said method comprising:
calculating displacements in two dimensions between a plurality of B-scans in a cluster of B-scans collected with an optical coherence tomography system and wherein at least two B-scans have an overlap of greater than 80%;
registering the B-scans in the cluster using the calculated displacements;
analyzing the registered cluster to obtain functional information of the sample; and
storing or displaying the functional information.
11. A non-transitory computer-readable medium as recited in claim 10 , in which the sample is a human eye.
12. A non-transitory computer-readable medium as recited in claim 10 in which the analyzing step includes applying an optical microangiography (OMAG) technique to the registered cluster.
13. A non-transitory computer-readable medium as recited in claim 10 , in which the registering step is carried out in the depth structure domain.
14. A non-transitory computer-readable medium as recited in claim 10 , in which the displacements are calculated on intensity B-scan data.
15. A non-transitory computer-readable medium as recited in claim 10 , in which the displacements are calculated on complex B-scan data.
16. A non-transitory computer-readable medium as recited in claim 10 , in which the calculating step is performed by taking cross-correlations between sub-regions of the B-scans in the cluster.
17. A non-transitory computer-readable medium as recited in claim 10 , in which the registering step involves creating delta functions from the displacements and convolving the delta functions to the B-scans to be registered.
18. A non-transitory computer-readable medium as recited in claim 10 , in which upsampling is used in the calculating step to improve the accuracy of the calculated displacements.