System and method for image registration in medical imaging system
The present disclosure relates to a system and method for image registration and image subtraction. The technique includes perform acquiring data related to the image processing, performing a pre-processing of the images, performing an image registration, performing an image subtraction, performing a post-processing of the images and managing storage of the data.
1. A system of image processing, comprising:
a storage storing a set of instructions; and
at least one processor in communication with the storage, wherein when executing the instructions, the at least one processor is configured to cause the system to:
acquire a reference image of an object and a floating image of the object;
perform a coarse registration on the floating image and the reference image to obtain an intermediate image;
perform a fine registration on the intermediate image and the reference image to obtain an auxiliary image, the fine registration comprising aligning a region of interest in the intermediate image with a reference region of interest in the reference image;
perform a super-fine registration on the auxiliary image and the reference image to obtain a target image, the super-fine registration comprising aligning a characteristic in the auxiliary image with a reference characteristic in the reference image.
2. The system of claim 1 , wherein the coarse registration includes rigid spatial transformation based on an optimization of either mutual information or a mean squared error.
3. The system of claim 1 , wherein the fine registration includes free-form deformation designating offsets of points in the region of interest in the intermediate image, and the fine registration is determined based on an optimization of either mutual information or a mean squared error on the points in the region of interest in the intermediate image.
4. The system of claim 1 , wherein the characteristic in the auxiliary image includes at least one feature point in the auxiliary image or a structure in the auxiliary image, the reference characteristic in the reference image includes at least one reference feature point in the reference image or a reference structure in the reference image.
5. The system of claim 4 , wherein the at least one reference feature point in the reference image is a point with the highest gray level.
6. The system of claim 5 , wherein the reference image is X-ray image, and the point with the highest gray level is a point designating a positioning of a rib.
7. The system of claim 4 , wherein the reference image is CT image, and the reference structure in the reference image is a rib or a vessel within a lung area in the CT image.
8. The system of claim 4 , wherein the at least one processor is configured to cause the system further to identify a rib area in the reference image.
9. The system of claim 1 , wherein the reference image and the floating image are taken at different times.
10. A method comprising:
acquiring a reference image of an object and a floating image of the object;
performing a coarse registration on the floating image and the reference image to obtain an intermediate image;
performing a fine registration on the intermediate image and the reference image to obtain an auxiliary image, the fine registration comprising aligning a region of interest in the intermediate image with a reference region of interest in the reference image;
performing a super-fine registration on the auxiliary image and the reference image to obtain a target image, the super-fine registration comprising aligning a characteristic in the auxiliary image with a reference characteristic in the reference image.
11. The method of claim 10 , wherein the coarse registration includes rigid spatial transformation based on an optimization of either mutual information or a mean squared error.
12. The method of claim 10 , wherein the fine registration includes free-form deformation designating offsets of points in the region of interest in the intermediate image, and the fine registration is determined based on an optimization of either mutual information or a mean squared error on the points in the region of interest in the intermediate image.
13. The method of claim 10 , wherein the characteristic in the auxiliary image includes at least one feature point in the auxiliary image or a structure in the auxiliary image, the reference characteristic in the reference image includes at least one reference feature point in the reference image or a reference structure in the reference image.
14. The method of claim 13 , wherein the at least one reference feature point in the reference image is a point with the highest gray level.
15. The system of claim 14 , wherein the reference image is X-ray image, and the point with the highest gray level is a point designating a positioning of a rib.
16. The method of claim 13 , wherein the reference image is CT image, and the reference structure in the reference image is a rib or a vessel within a lung area in the CT image.
17. The method of claim 13 , further comprising identifying a rib area in the reference image.
18. The method of claim 10 , wherein the reference image and the floating image are taken at different times.
19. A non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations comprising:
acquiring a reference image of an object and a floating image of the object;
performing a coarse registration on the floating image and the reference image to obtain an intermediate image;
performing a fine registration on the intermediate image and the reference image to obtain an auxiliary image, the fine registration comprising aligning a region of interest in the intermediate image with a reference region of interest in the reference image;
performing a super-fine registration on the auxiliary image and the reference image to obtain a target image, the super-fine registration comprising aligning a characteristic in the auxiliary image with a reference characteristic in the reference image.