System and method for image segmentation in generating computer models of a joint to undergo arthroplasty
View Patent ↗Systems and methods for image segmentation in generating computer models of a joint to undergo arthroplasty are disclosed. Some embodiments may include a method of partitioning an image of a bone into a plurality of regions, where the method may include obtaining a plurality of volumetric image slices of the bone, generating a plurality of spline curves associated with the bone, verifying that at least one of the plurality of spline curves follow a surface of the bone, and creating a 3D mesh representation based upon the at least one of the plurality of spline curve.
1. A method of mapping a representation of a model bone into an image scan of a target bone:
registering a generated portion of the representation into the image scan of the target bone using a translational transformation;
registering the generated portion of the representation into the image scan of the target bone using a similarity transformation;
registering a boundary portion of the representation into the image scan of the target bone using an affine transformation; and
registering the boundary portion of the representation into the image scan of the target bone using a spline transformation.
2. The method of claim 1 , further comprising the act of adjusting one or more parameters of the translational transformation such that the translational transformation minimizes misalignment of the representation of the model bone and the image scan of the target bone.
3. The method of claim 1 , wherein the similarity transform includes seven factors that are varied to optimize match between the representation and the target bone.
4. The method of claim 1 , wherein the spline transformation is a 3D B-spline transformation.
5. The method of claim 1 , wherein the translational transform occurs without rotating, scaling, or deforming the representation.
6. The method of claim 1 , wherein the representation is rotated, scaled, or deformed during the similarity transform.
7. The method of claim 1 , wherein in the event the bone is a tibia, the method further comprises the act of using at least one additional registration operation between the affine and spline transformations.
8. The method of claim 7 , wherein the at least one additional registration operation uses transforms represented with one or more quadratic functions.
9. The method of claim 1 , wherein the model bone is varus.
10. The method of claim 1 , wherein the model bone is valgus.
11. The method of claim 1 , wherein the target bone includes a knee joint and the acts of registering are performed such that a tibia does not penetrate a femur.
12. The method of claim 1 , further comprising the act of introducing a penalty into the mapping in the event that the mapping causes the tibia to penetrate the femur.
13. The method of claim 1 , wherein a step gradient descent optimizer is used during the similarity transform, affine transform, and spline transforms.
14. The method of claim 1 , wherein the translational transform includes using an exhaustive optimizer.
15. The method of claim 1 , further comprising the act of correcting for variations between the representation of the model bone and the image scan of the target bone by supplying each voxel of the image scan with the distance to the nearest boundary voxel.
16. The method of claim 1 , wherein the similarity transform utilizes, for a center position, a center of a bounding box that encloses the target bone registered during translation registration.