Creating a vascular tree model
A method for vascular modeling is disclosed. The method, in some embodiments, comprises receiving a plurality of 2-D angiographic images of a portion of a vasculature of a subject, and processing the images to automatically detect 2-D features, for example, paths along vascular extents, which are projected into 3-D to determine homologous features among blood vessels. In some embodiments, projection and/or image registration is iteratively altered to improve feature position matching. Based on 3-D vascular extents and their registration to 2-D images, additional features such as vascular width are optionally determined and added to the model.
1. A method for construction of a vascular tree model comprising:
receiving, by image processing circuitry, a plurality of 2-D angiographic images showing blood vessel segments of a portion of a vasculature of a subject, wherein the plurality of the 2-D angiographic images are obtained during at least two separate phases of a cyclic physiological motion;
extracting, by the image processing circuitry, from each of the plurality of 2-D angiographic images, an image feature set comprising 2-D feature positions of the blood vessel segments, wherein the blood vessel segment positions deviate with the two separate phases of the cyclic physiological motion;
adjusting, by the image processing circuitry, correction parameters for back-projecting the 2-D feature positions into a common 3-D coordinate system to reduce back-projection fit errors among the plurality of 2-D angiographic images, at least some of the errors being caused by the cyclic physiological motion; and
associating, by the image processing circuitry, image features of the image feature sets to one another based on their adjusted back-projection from the planes of the 2-D angiographic images to common blood vessel segment regions in the common 3-D coordinate system to create a vascular tree model.
2. The method of claim 1 , wherein the image feature set includes a centerline data set including 2-D centerline positions ordered along the blood vessel segments.
3. The method of claim 2 , wherein adjusting the correction parameters includes registration of the 2-D feature positions in a 3-D space according to projection parameters that are configured to bring the 2-D centerline positions into closer correspondence among their 3-D back-projections.
4. The method of claim 2 , further comprising estimating a metric of radial vascular width based on values of at least one of the plurality of 2-D angiographic images along lines perpendicular to the ordered 2-D centerline positions.
5. The method of claim 1 , further comprising providing, by the image processing circuitry, information for the association of the image features of the image feature sets to one another before a review of the 2-D angiographic images by a human operator.
6. The method of claim 1 , further comprising defining a surface corresponding to a shape of the heart of the subject, and using the surface as a constraint for at least one of adjusting the correction parameters or extracting the image feature set.
7. The method of claim 1 , wherein the plurality of 2-D images are received after injection of a contrast agent to the vasculature of the subject, the method further comprising:
determining temporal information of a movement of the contrast agent through the vasculature; and
constraining the feature positions based on the temporal information.
8. The method of claim 1 , wherein one of the at least two separate phases includes an end of a diastole phase of the cyclic physiological motion.
9. The method of claim 1 , wherein the plurality of 2-D angiographic images shows coronary arteries of the subject.
10. The method of claim 1 , wherein at least some of the back-projection fit errors are caused by breathing or movements of the subject.
11. The method of claim 1 , wherein the correction parameters include information indicative of at least one of translation or rotation of the common 3-D coordinate system for the plurality of 2-D angiographic images.
12. The method of claim 1 , further comprising determining the correction parameters for the plurality of 2-D angiographic images based on the corresponding image features.
13. The method of claim 1 , further comprising:
identifying, by the image processing circuitry, 2-D image portions representing blood vessel segment regions for which a physical characteristic is to be calculated, based on analyzing projections of the blood vessel segment regions from the common 3-D coordinate system to planes of the 2-D angiographic images associated with the image features;
selecting, by image processing circuitry, a portion of at least one of the plurality of 2-D angiographic images, the portion comprising a representation of the associated image features identified by the inspecting; and
calculating a physical characteristic of at least one of the blood vessel segments, based on the selected image portion.
14. A system for vascular assessment comprising a computer communicatively coupled to a memory storing instructions, which when executed by the computer, cause the computer to:
receive a plurality of 2-D angiographic images of blood vessel segments in a portion of vasculature of a subject from an angiographic imaging device, wherein the plurality of the 2-D angiographic images are recorded during at least two separate phases of a cyclic physiological motion;
extract, from each of the plurality of 2-D angiographic images, an image feature set comprising 2-D feature positions of the blood vessel segments, wherein the blood vessel segment positions deviate with the two separate phases of the cyclic physiological motion;
adjust parameters that back-project the 2-D feature positions into a common 3-D coordinate system to improve a quality of back-projection fit among the plurality of 2-D angiographic images; and
associate image features of the image feature sets to one another based on their adjusted back-projection from the planes of the 2-D angiographic images to common blood vessel segment regions in the common 3-D coordinate system.
15. The system of claim 14 , wherein the memory includes additional instructions, which when executed, cause the computer to send a synchronization signal to the angiographic imaging device for synchronizing the recording of the plurality of the 2-D images to the separate phases of the cyclic physiological motion.
16. The system of claim 14 , wherein the memory includes additional instructions, which when executed, cause the computer to:
select a portion of at least one of the plurality of 2-D angiographic images, the portion comprising a representation of the associated image features, wherein the selection is based on an analysis of projections from the common 3-D coordinate system of blood vessel segment regions associated with the image features to the 2-D angiographic images; and
calculate a physical characteristic of at least one of the blood vessel segments, based on the selected image portion.
17. The system of claim 16 , wherein the image feature set comprises a centerline data set including 2-D centerline positions ordered along the blood vessel segments, and
wherein the memory includes additional instructions, which when executed, cause the computer to use the 2-D centerline positions as the 2-D feature positions.
18. The system of claim 17 , wherein the memory includes additional instructions, which when executed, cause the computer to adjust the parameters based on registration of the 2-D feature positions in 3-D space according to projection parameters that bring the 2-D centerline positions into closer correspondence among their 3-D back-projections.
19. The system of claim 18 , wherein the memory includes additional instructions, which when executed, cause the computer to determine, for the representation of the associated image features, radial vascular width measurements based on values of at least one of the plurality of 2-D angiographic images along lines perpendicular to the ordered 2-D centerline positions.
20. The system of claim 14 , wherein the parameters define 2-D image transformations of a first image of the plurality of 2-D angiographic images to more closely match projections of the 2-D feature positions projected from a 3-D feature position model derived from a second image of the plurality of 2-D angiographic images.
21. The system of claim 14 , wherein the portion of the vasculature includes a tree of coronary arteries to at least a third branch point from a main coronary artery.