Method for determining contact position parameters of a joint connecting two bones

• US 9,852,268 B2
• Filed: 12/09/2011
• Issued: 12/26/2017
• Est. Priority Date: 12/09/2011
• Status: Active Grant

• Current Assignee: Smith & Nephew Incorporated (Smith & Nephew PLC), Smith & Nephew Orthopaedics Ag (Smith & Nephew PLC), Smith & Nephew Pte. Limited (Smith & Nephew PLC)
• Original Assignee: Brainlab AG
• Inventors: Gotte, Hubert
• Primary Examiner(s): Phan, Thai
• Application Number:
  US14/363,040
• Publication Number:
  US 20140303947A1
• Time in Patent Office: 2,209 Days
• Field of Search: 703 2, 703 5, 345473, 600587
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A data processing method for determining six parameters of a contact position of a joint which connects two bones, comprising the steps of acquiring a plurality of sample contact position datasets, each dataset comprising six parameters, acquiring a subset of n of the parameters of the contact position as an input parameter dataset, selecting at least two of the sample contact position datasets based on the input parameter dataset and determining the m=6−n remaining parameters of the contact position based on the at least two selected sample contact position datasets.

Claims

1. A data processing method performed in a computer having a memory for determining six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, the method comprising:

acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position;

acquiring a subset of n of the parameters of the contact position as an input parameter dataset;

selecting at least two of the sample contact position datasets based on the input parameter dataset; and

determining the m=6−

n remaining parameters of the contact position based on the at least two selected sample contact position datasets.

2. The method of claim 1, wherein the remaining parameters are determined by interpolation or extrapolation.

3. The method according to claim 2, wherein the interpolation is a spline interpolation or uses inverse distance weighting.

4. The method according to claim 1, wherein the selected sample contact position datasets correspond to sample contact positions which are, regarding the input parameters, the nearest neighbors of the contact position.

5. The method of claim 4, wherein a distance between the contact position and a sample contact position is calculated using a Minkowski distance function.

6. The method according to claim 1, wherein the sample contact position datasets are arranged in an n-dimensional array and each array entry comprises the m remaining parameters.

7. The method according to claim 1, wherein the sample contact positions are arranged at equidistant intervals.

8. The method according to claim 1, wherein a sample contact position dataset is void for an impossible joint contact position.

9. The method of claim 1, wherein a sample contact position dataset further comprises affiliate information which indicates that the sample contact position belongs to a contact profile of contact positions.

10. The method according to claim 1, wherein the step of determining the m=6−

n remaining parameters of the contact position is repeated for a sequence of input parameter datasets, thus resulting in a sequence of contact positions.

11. The method according to claim 1, wherein a sample position dataset is determined by virtually positioning three-dimensional images of the two bones such that they are in contact and using the relative position of the bones thus positioned as a sample contact position.

12. The method according to claim 1, wherein a sample position dataset is automatically determined by using collision detection of three-dimensional models of the two bones.

13. The method according to claim 1, wherein a sample position dataset is determined by measuring a real joint.

14. A computer program embodied on a non-transitory computer readable medium which, when running on a computer or when loaded onto a computer, causes the computer to determine six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, by performing steps comprising:

acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position;

acquiring a subset of n of the parameters of the contact position as an input parameter dataset;

selecting at least two of the sample contact position datasets based on the input parameter dataset; and

determining the m=6-n remaining parameters of the contact position based on the at least two selected sample contact position datasets.

15. A computer on which the computer program according to claim 14 is running or into the memory of which the computer program is loaded.