Gaming state object tracking
US-2024420539-A1 · Dec 19, 2024 · US
US9138165B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9138165-B2 |
| Application number | US-201313773984-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 22, 2013 |
| Priority date | Feb 22, 2012 |
| Publication date | Sep 22, 2015 |
| Grant date | Sep 22, 2015 |
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A surgical instrument navigation system is provided that visually simulates a virtual volumetric scene of a body cavity of a patient from a point of view of a surgical instrument residing in the cavity of the patient, wherein the surgical instrument, as provided, may be a steerable surgical catheter with a biopsy device and/or a surgical catheter with a side-exiting medical instrument, among others. Additionally, systems, methods and devices are provided for forming a respiratory-gated point cloud of a patient's respiratory system and for placing a localization element in an organ of a patient.
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What is claimed is: 1. A method of modifying a segmented image dataset for a region of a respiratory system to match the corresponding anatomy of a patient's respiratory system, the method comprising: (i) forming a respiratory-gated point cloud of data by moving a catheter having a localization element through a plurality of locations in the patient's respiratory system, wherein the respiratory-gated point cloud of data demarcates the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system at one or more discrete phases within a respiration cycle of the patient, (ii) density filtering the respiratory-gated point cloud to reduce the number of duplicate data points in the respiratory-gated point cloud, (iii) classifying data points of the density filtered respiratory-gated point cloud into the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system, and (iv) modifying the segmented image dataset to correspond to the classified data points in the density filtered respiratory-gated point cloud. 2. The method of claim 1 wherein the discrete phases are expiration, inspiration and discrete phases there-between. 3. The method of claim 1 wherein the segmented image dataset is from a first discrete phase of the patient's respiration cycle and the respiratory-gated point cloud is from a second and different discrete phase of the patient's respiration cycle. 4. The method of claim 1 wherein the segmented image dataset is a skeletonized segmented image dataset depicting a centerline of the patient's respiratory system. 5. A method of simulating the movement of a patient's respiratory system in the patient's respiration cycle during respiration comprising: (i) forming a respiratory-gated point cloud of data by moving a catheter having a localization element through a plurality of locations in the patient's respiratory system, wherein the respiratory-gated point cloud of data demarcates the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system at one or more discrete phases within a respiration cycle of the patient, (ii) density filtering the respiratory-gated point cloud to reduce the number of duplicate data points in the respiratory-gated point cloud, (iii) classifying data points of the density filtered respiratory-gated point cloud into the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system, (iv) creating a cine loop comprising a plurality of modified segmented image datasets through multiple modifications of the segmented image dataset to correspond to a plurality of classified data points in the respiratory-gated point cloud over the respiration cycle, and (v) displaying the cine loop comprising the plurality of modified segmented image datasets over the patient's respiration cycle. 6. The method of simulation of claim 5 wherein displaying the cine loop comprising the plurality of modified segmented image datasets over the patient's respiration cycle is synchronized with the patient's respiration cycle. 7. A method of preparing a segmented image dataset to match the anatomy of a patient's respiratory system, the method comprising: (i) forming a respiratory-gated point cloud of data by moving a catheter having a localization element through a plurality of locations in the patient's respiratory system, wherein the respiratory-gated point cloud of data demarcates the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system at one or more discrete phases within a respiration cycle of the patient, (ii) density filtering the respiratory-gated point cloud to reduce the number of duplicate data points in the respiratory-gated point cloud, (iii) classifying data points of the density filtered respiratory-gated point cloud into the trachea, the right main bronchus, and the left main bronchus of the patient's respiratory system, (iv) registering the classified respiratory-gated point cloud to the segmented image dataset, (v) comparing the classified respiratory-gated point cloud to a segmented image data set to determine the weighting of points comprised by the respiratory-gated point cloud, (vi) distinguishing regions of greater weighting from regions of lesser weighting, and (vii) modifying the registered segmented image dataset to correspond to the classified data points the respiratory-gated point cloud. 8. The method of claim 7 wherein registering the respiratory-gated point cloud to the segmented image data set comprises: registering the respiratory-gated point cloud representing at least one branch of the patient's respiratory system to corresponding anatomical points of reference in the registered segmented image data set representing the branch(es) of the patient's respiratory system. 9. The method of claim 7 wherein the respiratory-gated point cloud is registered to a plurality of branches of the patient's respiratory system, wherein the plurality of branches comprise the trachea, the right main bronchus, and the left main bronchus. 10. The method of claim 7 wherein the discrete phases are expiration, inspiration and discrete phases there-between. 11. The method of claim 7 wherein the segmented image dataset is from a first discrete phase of the patient's respiration cycle and the respiratory-gated point cloud is from a second and different discrete phase of the patient's respiration cycle. 12. A non-transitory processor-readable medium storing code representing instructions to cause a processor to perform a process, the code comprising code to carry out one or more elements of the method of claim 1 . 13. A non-transitory processor-readable medium storing code representing instructions to cause a processor to perform a process, the code comprising code to carry out one or more elements of the method of claim 5 . 14. A non-transitory processor-readable medium storing code representing instructions to cause a processor to perform a process, the code comprising code to carry out one or more elements of the method of claim 7 . 15. The method of claim 7 further comprising, after the step of distinguishing regions of greater weighting from regions of lesser weighting, increasing the data set comprised by the respiratory-gated point cloud for regions of lesser weighting.
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