Multi-rigid registration of magnetic navigation to a computed tomography volume
Devices, systems, methods, and computer-readable media for registering an electromagnetic registration of a luminal network to a 3D model of the luminal network include accessing a 3D model of a luminal network based on computed tomographic (CT) images of the luminal network, selecting a plurality of reference points within the 3D model of the luminal network, obtaining a plurality of survey points within the luminal network, dividing the 3D model of the luminal network and the luminal network into a plurality of regions, assigning a plurality of weights to the plurality of regions, determining an alignment of the plurality of reference points with the plurality of survey points based on the plurality of weights, and generating a registration based on the alignment, the registration enabling conversion of the plurality of survey points within the luminal network to points within the 3D model of the luminal network.
1. A system comprising:
one or more processors; and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of:
receiving, as input, a selection of a plurality of reference points within a 3D model of a luminal network to generate a reference airway tree within the 3D model of the luminal network;
dividing the 3D model of the luminal network and the reference airway tree into different regions of lungs;
assigning a weight to each region of the different regions of the lungs of the reference airway tree;
generating a survey airway tree based on the selection of the plurality of reference points of the reference airway tree;
dividing the survey airway tree into different regions of the lungs that are the same as the different regions of the lungs of the reference airway tree;
for each region of the different regions of the lungs of the survey airway tree, assigning a weight to each of a plurality of survey points located within that region;
determining, for each region of the respective different regions of the lungs of the reference airway tree and the survey airway tree, an alignment between the survey airway tree and the reference airway tree based on a weight assigned to that region of the reference airway tree and the weight assigned to each of the plurality of survey points located within that region of the survey airway tree; and
correcting a displacement between the survey airway tree and the reference airway tree based on the alignments.
2. The system according to claim 1 , wherein generating the survey airway tree includes generating the plurality of survey points based on the selection of the plurality of reference points of the reference airway tree.
3. The system according to claim 1 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
determining in which region of the different regions of the lungs of the survey airway tree each survey point of the plurality of survey points is generated; and
assigning the weight to each survey point of the plurality of survey points based on the region of the survey airway tree in which the survey point is determined to be generated.
4. The system according to claim 1 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
minimizing a divergence between the plurality of reference points and the plurality of survey points based on the weight assigned to each survey point of the plurality of survey points.
5. The system according to claim 1 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
overlaying the survey airway tree onto the 3D model of the luminal network.
6. A system comprising:
one or more processors; and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of:
dividing a 3D model of a patient's lungs into different lung regions;
assigning a weight to each of the different lung regions;
receiving, as input, a selection of a plurality of reference points within the 3D model of the patient's lungs;
generating a reference airway tree based on the selection of the plurality of reference points within the 3D model of the patient's lungs;
generating a survey airway tree;
dividing each of the reference airway tree and the survey airway tree into different lung regions that are the same as the different lung regions of the 3D model;
assigning a weight to each region of the different lung regions of the reference airway tree;
for each lung region of the different lung regions of the survey airway tree, assigning a weight to each of a plurality of survey points located within that lung region;
determining, for each lung region of the respective different lung regions of the reference airway tree and the survey airway tree, an alignment between the survey airway tree and the reference airway tree based on a weight assigned to that lung region of the reference airway tree and the weight assigned to each of the plurality of survey points located within that lung region of the survey airway tree; and
minimizing a divergence between the survey airway tree and the reference airway tree based on the alignments.
7. The system according to claim 6 , wherein generating the survey airway tree includes generating the plurality of survey points based on the selection of the plurality of reference points of the reference airway tree.
8. The system according to claim 6 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
determining in which of the different lung regions of the survey airway tree each survey point of the plurality of survey points is generated; and
assigning the weight to each survey point of the plurality of survey points based on the lung region of the survey airway tree in which the survey point is determined to be generated.
9. The system according to claim 6 , wherein minimizing a divergence between the survey airway tree and the reference airway tree includes minimizing a divergence between the plurality of reference points and the plurality of survey points based on the weight assigned to each survey point of the plurality of survey points.
10. The system according to claim 6 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
overlaying the survey airway tree onto the 3D model of the patient's lungs.
11. A system comprising:
one or more processors; and
one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of:
receiving, as input, a selection of a plurality of reference points within a 3D model of a patient's lungs to generate a reference airway tree within the 3D model of the patient's lungs;
dividing the 3D model of the patient's lungs and the reference airway tree into different lung regions;
assigning a weight to each lung region of the different lung regions of the reference airway tree;
generating a survey airway tree;
dividing the survey airway tree into different lung regions that are the same as the different lung regions of the reference airway tree;
for each lung region of the different lung regions of the survey airway tree, assigning a weight to each of a plurality of survey points located within that lung region;
determining, for each lung region of the respective different lung regions of the reference airway tree and the survey airway tree, an alignment between the survey airway tree and the reference airway tree based on a weight assigned to that lung region of the reference airway tree and the weight assigned to each of the plurality of survey points located within that lung region of the survey airway tree; and
registering the survey airway tree with the reference airway tree based on the alignments.
12. The system according to claim 11 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
overlaying the survey airway tree onto the 3D model of the patient's lungs.
13. The system according to claim 11 , wherein generating the survey airway tree includes generating the plurality of survey points based on the selection of the plurality of reference points of the reference airway tree.
14. The system according to claim 11 , wherein the one or more processor-readable storage media further store instructions which, when executed by the one or more processors, cause performance of:
determining in which of the different lung regions of the survey airway tree each survey point of the plurality of survey points is generated; and
assigning a weight to each survey point of the plurality of survey points based on the lung region of the survey airway tree in which the survey point is determined to be generated.