Adaptive navigation technique for navigating a catheter through a body channel or cavity
Abstract
A method for using an assembled three-dimensional image to construct a three-dimensional model for determining a path through a lumen network to a target. The three-dimensional model is automatically registered to an actual location of a probe by tracking and recording the positions of the probe and continually adjusting the registration between the model and a display of the probe position. The registration algorithm becomes dynamic (elastic) as the probe approaches smaller lumens in the periphery of the network where movement has a bigger impact on the registration between the model and the probe display.
Claims
exact text as granted — not AI-modified1 - 14 . (canceled)
15 . A method of generating an intra-lumen pathway to a target inside the body, comprising:
imaging a patient to obtain a plurality of scans; creating a 3D image volume from the scans comprising a plurality of voxels; selecting a target in the 3D image volume; detecting an anatomical feature related to the network of lumens within the 3D image volume; segmenting only voxels that represent space inside the lumens of the network; generating a computerized three-dimensional model of the lumen network using the segmented voxels; marking a pathway to the target on the three-dimensional model of the lumen network marking an exit point of the pathway on the three-dimensional model of the lumen network; and directly connecting the exit point and the target with a single straight line.
16 . The method of claim 15 wherein detecting an anatomical feature related to the network comprises detecting a trachea.
17 . The method of claim 16 wherein detecting the trachea includes searching for a tubular object in the lumen network having a density of air in the upper region of the network.
18 . The method of claim 15 wherein detecting an anatomical feature related to the network includes detecting an aorta.
19 . The method of claim 15 wherein segmenting only voxels that represent space inside the lumens of the network includes marking voxels that represent a substance contained within the lumens of the network.
20 . The method of claim 19 wherein segmenting only voxels that represent a substance inside the lumens of the network further includes avoiding bubbles caused by imaging noise and artifacts.
21 . The method of claim 15 wherein segmenting only voxels that represent space inside the lumens of the network includes:
a) defining a threshold value;
b) defining a seed point at a center point inside of the anatomical feature related to the network;
c) marking all related voxels according to the threshold value beginning with the seed point;
d) recording a whole number of marked voxels;
e) increasing the threshold value;
f) repeating steps c) and d), thereby beginning a next iteration;
g) comparing the number of marked voxels to the number determined in a previous iteration;
h) setting a limit for the increase determined at g) over which the increase is attributed to leakage and the increased threshold value at e) is reset to that from the previous iteration, thereby establishing a selected threshold;
i) segmenting the marked voxels using the selected threshold;
j) adding the segmented voxels to the seed point, thereby growing a pathway and resetting the seed point to a center of a distal end of the pathway; and
k) repeating steps c) through j) until the pathway is complete.Join the waitlist — get patent alerts
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