Detecting and representing anatomical features of an anatomical structure

Patent metadata

Field	Value
Publication number	US-12067678-B2
Application number	US-202017617869-A
Country	US
Kind code	B2
Filing date	Jun 9, 2020
Priority date	Jun 11, 2019
Publication date	Aug 20, 2024
Grant date	Aug 20, 2024

Abstract

An exemplary processing system accesses a three-dimensional (3D) model of an anatomical structure of a patient and applies a detection process to the 3D model to detect a single-layer anatomical feature in the anatomical structure. The detection process includes generating, from the 3D model, a probability map of candidate points for the single-layer anatomical feature, and generating, based on the probability map of candidate points, a single-layer mesh representing the single-layer anatomical feature.

First claim

What is claimed is:

1. A system comprising:
a memory storing instructions; and
a processor communicatively coupled to the memory and configured to execute the instructions to:
access a three-dimensional (3D) model of an anatomical structure; and
apply a detection process to the 3D model to detect a single-layer anatomical feature in the anatomical structure, the detection process comprising:
determining, from the 3D model, a set of candidate points for the single-layer anatomical feature;
applying a signed distance transform on the set of candidate points to generate a signed distance map, wherein the signed distance map includes vectors that pass through the set of candidate points, the vectors orthogonal to the single-layer anatomical feature and representing distances of the candidate points from the single-layer anatomical feature; and
generating a single-layer mesh representing the single-layer anatomical feature by connecting zero-crossing points in the signed distance map.

2. The system of claim 1 , wherein the generating the single-layer mesh representing the single-layer anatomical feature comprises:
generating an initial single-layer mesh; and
generating a refined single-layer mesh based on the initial single-layer mesh.

3. The system of claim 2 , wherein the generating the refined single-layer mesh comprises refining the initial single-layer mesh based on a property of the anatomical feature.

4. The system of claim 2 , wherein the generating the refined single-layer mesh comprises at least one of:
smoothing the initial single-layer mesh;
filling holes in the initial single-layer mesh; or
clipping, based on the 3D model of the anatomical structure, the initial single-layer mesh.

5. The system of claim 1 , wherein the single-layer anatomical feature comprises a fissure of the anatomical structure.

6. The system of claim 1 , wherein the processor is further configured to execute the instructions to apply an additional detection process, different from the detection process, to the 3D model to detect a non-single-layer anatomical feature in the anatomical structure.

7. The system of claim 6 , wherein the additional detection process comprises a segmentation process to detect the non-single-layer anatomical feature.

8. The system of claim 6 , wherein the non-single-layer anatomical feature comprises one or more blood vessels.

9. The system of claim 6 , wherein the non-single-layer anatomical feature comprises one or more airways.

10. The system of claim 1 , wherein the processor is further configured to execute the instructions to provide a visual representation of the anatomical structure based on the 3D model and the detected single-layer anatomical feature in the anatomical structure.

11. The system of claim 1 , wherein the detection process further comprises applying Hessian matrices to determine normal information for the set of candidate points.

12. A method comprising:
accessing, by a processor, a three-dimensional (3D) model of an anatomical structure; and
applying, by the processor, a detection process to the 3D model to detect a single-layer anatomical feature in the anatomical structure, the detection process comprising:
determining, from the 3D model, a set of candidate points for the single-layer anatomical feature;
applying a signed distance transform on the set of candidate points to generate a signed distance map, wherein the signed distance map includes vectors that pass through the set of candidate points, the vectors orthogonal to the single-layer anatomical feature and representing distances of the candidate points from the single-layer anatomical feature; and
generating a single-layer mesh representing the single-layer anatomical feature by connecting zero-crossing points in the signed distance map.

13. The method of claim 12 , wherein the generating the single-layer mesh representing the single-layer anatomical feature comprises:
generating an initial single-layer mesh; and
generating a refined single-layer mesh based on the initial single-layer mesh.

14. The method of claim 13 , wherein the generating the refined single-layer mesh comprises refining the initial single-layer mesh based on a property of the anatomical feature.

15. The method of claim 13 , wherein the generating the refined single-layer mesh comprises at least one of:
smoothing the initial single-layer mesh;
filling holes in the initial single-layer mesh; or
clipping, based on the 3D model of the anatomical structure, the initial single-layer mesh.

16. The method of claim 12 , wherein the single-layer anatomical feature comprises a fissure of the anatomical structure.

17. The method of claim 12 , further comprising applying an additional detection process, different from the detection process, to the 3D model to detect a non-single-layer anatomical feature in the anatomical structure.

18. The method of claim 12 , further comprising providing a visual representation of the anatomical structure based on the 3D model and the detected single-layer anatomical feature in the anatomical structure.

19. The method of claim 12 , wherein the detection process further comprises applying Hessian matrices to determine normal information for the set of candidate points.

20. A non-transitory computer-readable medium storing instructions executable by a processor to:
access a three-dimensional (3D) model of an anatomical structure; and
apply a detection process to the 3D model to detect a single-layer anatomical feature in the anatomical structure, the detection process comprising:
determining, from the 3D model, a set of candidate points for the single-layer anatomical feature;
applying a signed distance transform on the set of candidate points to generate a signed distance map, wherein the signed distance map includes vectors that pass through the set of candidate points, the vectors orthogonal to the single-layer anatomical feature and representing distances of the candidate points from the single-layer anatomical feature; and
generating a single-layer mesh representing the single-layer anatomical feature by connecting zero-crossing points in the signed distance map.

Assignees

• Intuitive Surgical Operations

Inventors

• Zhang Hui
• Li Junning
• Wang Bai
• Zhao Tao

Classifications

• G06T2210/41

  Medical · CPC title

• G06T2207/30101

  Blood vessel; Artery; Vein; Vascular · CPC title

• G06T2207/30064

  Lung nodule · CPC title

• G06T7/0012 Primary

  Biomedical image inspection · CPC title

• A61B2034/107

  Visualisation of planned trajectories or target regions · CPC title