Multi-rigid registration of magnetic navigation to a computed tomography volume

• US 10,646,284 B2
• Filed: 11/20/2018
• Issued: 05/12/2020
• Est. Priority Date: 12/05/2017
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Weingarten, Oren P., Nepomniashchy, Alexander
• Primary Examiner(s): Fitzpatrick, Atiba O
• Application Number:
  US16/196,032
• Publication Number:
  US 20190167355A1
• Time in Patent Office: 539 Days
• Field of Search: None
• CPC Class Codes: A61B 2017/00809 Lung operations
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2034/2068 using pointers, e.g. pointers having reference marks for determining coordinates of body points
• CPC Class Codes: A61B 2034/2072 Reference field transducer attached to an instrument or patient
• CPC Class Codes: A61B 2090/367 creating a 3D dataset from 2D images using position information
• CPC Class Codes: A61B 2090/3762 using computed tomography systems [CT]
• CPC Class Codes: A61B 2090/3925 ultrasonic
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/5235 combining images from the same or different ionising radiation imaging techniques, e.g. PET and CT
• CPC Class Codes: A61B 90/37 Surgical systems with images on a monitor during operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

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.

Claims

1. A method of registering an electromagnetic registration of a luminal network to a 3D model of the luminal network, the method comprising:

accessing a 3D model of a luminal network, the 3D model 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 into different regions of a lung;

assigning a plurality of weights to the different regions of the lung;

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 locations within the luminal network to locations within the 3D model of the luminal network.

2. The method of claim 1, wherein the luminal network is an airway of a patient.

3. The method of claim 2, wherein the 3D model is a model of the airway of the patient.

4. The method of claim 1, further comprising:

determining which region of the different regions of the lung in which each of the plurality of survey points is obtained; and

assigning a corresponding weight to each of the plurality of survey points based on which region each of the plurality of survey points is obtained.

5. The method of claim 4, wherein determining an alignment of the plurality of reference points with the plurality of survey points comprises:

minimizing a divergence between the plurality of reference points and the plurality of survey points based on the corresponding weight assigned to each of the plurality of survey points.

6. The method of claim 1, further comprising:

for each particular region of the plurality of regions;

assigning a particular plurality of weights to the different regions of the lung, the particular plurality of weights favoring the particular region;

minimizing a divergence between the plurality of reference points and the plurality of survey points based on the particular plurality of weights, the minimized divergence corresponding to a particular alignment; and

generating a particular registration based on the particular alignment, the particular registration being associated with the particular region and enabling conversion of locations within the luminal network to locations within the 3D model of the luminal network.

7. The method of claim 1, wherein the different regions of the lung includes transition regions.

8. The method of claim 7, wherein the different regions of the lung includes a right lung region, a central region, and a left lung region;

and

wherein the transition regions include left-central region and right-central region.

9. A system for updating a 3D model of a luminal network, the system comprising:

a location sensor capable of being navigated within a luminal network inside a patient'"'"'s body;

an electromagnetic field generator configured to detect a location of the location sensor as it is navigated within the luminal network; and

a computing device including a processor and a memory storing instructions which, when executed by the processor, cause the computing device to;

access a 3D model of the luminal network based on computed tomographic (CT) images of the luminal network;

select a plurality of reference points within the 3D model of the luminal network;

obtain a plurality of survey points within the luminal network, the plurality of survey points being generated by the location sensor and the electromagnetic field generator;

divide the 3D model of the luminal network into different regions of the lung;

assign a plurality of weights to the different regions of the lung;

determine an alignment of the plurality of reference points with the plurality of survey points based on the plurality of weights; and

generate 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.

10. The system of claim 9, wherein the instructions, when executed by the processor, further cause the computing device to:

determine which region of the different regions of the lung in which each of the plurality of survey points is obtained based on detected locations of the location sensor; and

assign a corresponding weight to each of the plurality of survey points based on which region each of the plurality of survey points is obtained.

11. The system of claim 10, wherein the instructions, when executed by the processor, further cause the computing device to:

minimize a divergence between the plurality of reference points and the plurality of survey points based on the corresponding weight assigned to each of the plurality of survey points.

12. The system of claim 9, wherein the instructions, when executed by the processor, further cause the computing device to:

for each particular region of the different regions of the lung;

assign a particular plurality of weights to the different regions of the lung, the particular plurality of weights favoring the particular region;

minimize a divergence between the plurality of reference points and the plurality of survey points based on the particular plurality of weights, the minimized divergence corresponding to a particular alignment; and

generate a particular registration based on the particular alignment, the particular registration being associated with the particular region and enabling conversion of locations within the luminal network to locations within the 3D model of the luminal network.

13. The system of claim 12, wherein the different regions of the lung include transition regions.

14. The system of claim 13, wherein the different regions of the lung include a right lung region, a central region, and a left lung region;

and

wherein the transition regions include a left-central region and a right-central region.

15. The system of claim 13, wherein the instructions, when executed by the processor, further cause the computing device to:

determine that a location of the location sensor is within a transition region;

determine which regions of the different regions of the lung the location sensor is transitioning between; and

interpolate a location within the 3D model of the luminal network based on registrations associated with the regions of the different regions of the lung the location sensor is transitioning between.