Adaptive Navigation Technique For Navigating A Catheter Through A Body Channel Or Cavity

• US 20080118135A1
• Filed: 11/13/2007
• Published: 05/22/2008
• Est. Priority Date: 11/10/2006
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: superDimension, Ltd. (Medtronic Plc)
• Inventors: Markov, Igor, Vorobeychyk, Ivan, Cohen, Ran, Averbuch, Dorian, Weingarten, Oren, Joskowicz, Leo
• Granted Patent: US 9,129,359 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/252 indicating steps of a surgical procedure
• CPC Class Codes: A61B 2090/3762 using computed tomography systems [CT]
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/25 User interfaces for surgical systems
• CPC Class Codes: G06T 11/203 Drawing of straight lines or curves
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 2207/20156 Automatic seed setting
• CPC Class Codes: G06T 2207/30061 Lung
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/155 involving morphological operators
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes

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

1. 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 a anatomical feature related to the network;

segmenting 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.

2. The method of claim 1 wherein detecting an anatomical feature related to the network comprises detecting the trachea.

3. The method of claim 2 wherein detecting the trachea comprises searching for a tubular object in the lumen network having the density of air in the upper region of the network.

4. The method of claim 1 wherein detecting an anatomical feature related to the network comprises detecting the aorta.

5. The method of claim 1 wherein segmenting voxels that represent space inside the lumens of the network comprises marking voxels that represent a substance contained within the lumens of the network.

6. The method of claim 5 wherein segmenting voxels that represent a substance inside the lumens of the network further comprises avoiding bubbles caused by imaging noise and artifacts.

7. The method of claim 1 wherein segmenting voxels that represent space inside the lumens of the network comprises:

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 said threshold value beginning with said seed point;

d) recording a whole number of marked voxels;

e) increasing said 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 said seed point, thereby growing a pathway and resetting said seed point to a center of a distal end of the pathway;

k) repeating steps c) through j) until said pathway is complete.

8. A method of registering a computer model of a lumen network to an actual lumen network of a patient while navigating the lumen network with a probe, comprising:

collecting data pertaining to an actual location of a probe;

processing successive data points to establish a probe path;

iteratively registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe;

iteratively adjusting the location of the computer model such that said probe path lies within the path shape.

9. The method of claim 8 wherein collecting data pertaining to an actual location of a probe comprises receiving location data from a tip of said probe.

10. The method of claim 8 wherein processing successive data points to establish a probe path comprises cleaning.

11. The method of claim 8 wherein iteratively registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe comprises rigidly registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe.

12. The method of claim 8 wherein iteratively registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe comprises deformably registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe.

13. The method of claim 8 wherein iteratively registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe comprises:

rigidly registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe while a diameter of a lumen containing the probe is large relative to the probe;

deformably registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe while a diameter of a lumen containing the probe is not large relative to the probe.

14. The method of claim 8 wherein iteratively registering the probe path to a path shape on a computer model of a lumen network while tracking the location of the probe comprises:

obtaining a stream of probe locations;

decluttering and assigning weights to the probe locations;

selecting probe locations for projecting;

projecting the selected probe locations onto the computer model.