System and method for tracking a global shape of an object in motion
First Claim
1. A computer implemented method for tracking a deformable global shape of an object in motion in a sequence of digital medical images, the method performed by the computer comprising the steps of:
- providing a probabilistic subspace shape model for the deformable global shape derived from a set of training shapes;
defining one or more control points along the deformable global shape;
tracking each of the one or more control points as the object is in motion;
estimating uncertainty of a location of a control point in motion;
exploiting the uncertainty to constrain the deformable global shape using a point dependent covariance matrix to employ the subspace shape constraint model using a non-orthogonal projection;
fusing the subspace constraint model and the uncertainty to determine a current location of the object by correcting outlier control points according to the probabilistic subspace shape model; and
remedying error accumulation during tracking of the one or more control points by using a multi-template adaptive matching framework.
3 Assignments
0 Petitions
Accused Products
Abstract
A system and method for tracking a global shape of an object in motion is disclosed. One or more control points along an initial contour of the global shape are defined. Each of the one or more control points is tracked as the object is in motion. Uncertainty of a location of a control point in motion is represented using a number of techniques. The uncertainty to constrain the global shape is exploited using a prior shape model. In an alternative embodiment, multiple appearance models are built for each control point and the motion vectors produced by each model are combined in order to track the shape of the object. The movement of the shape of the object can be visually tracked using a display and color vectors.
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Citations
56 Claims
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1. A computer implemented method for tracking a deformable global shape of an object in motion in a sequence of digital medical images, the method performed by the computer comprising the steps of:
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providing a probabilistic subspace shape model for the deformable global shape derived from a set of training shapes; defining one or more control points along the deformable global shape; tracking each of the one or more control points as the object is in motion; estimating uncertainty of a location of a control point in motion; exploiting the uncertainty to constrain the deformable global shape using a point dependent covariance matrix to employ the subspace shape constraint model using a non-orthogonal projection; fusing the subspace constraint model and the uncertainty to determine a current location of the object by correcting outlier control points according to the probabilistic subspace shape model; and remedying error accumulation during tracking of the one or more control points by using a multi-template adaptive matching framework. - View Dependent Claims (2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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6. The method of 1 wherein the subspace shape constraint model is a Gaussian model.
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22. A program storage device readable by a computer, tangibly embodying a program of instructions executable by the computer to perform the method steps for tracking a global shape of an object in motion in a sequence of digital medical images, method comprising:
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providing a probabilistic subspace shape model for the deformable global shape derived from a set training shapes; defining one or more control points along an initial contour of the deformable global shape; tracking each of the one or more control points as the object is in motion; estimating uncertainty of a location of a control point in motion; exploiting the uncertainty to constrain the deformable global shape using a point dependent covariance matrix to employ the subspace shape constraint model using a non-orthogonal projection; fusing the subspace constraint model and the uncertainty to determine a current location of the object by correcting outlier control points according to the probabilistic subspace shape model; and remedying error accumulation during tracking of the one or more control points by using a multi-template adaptive matching framework. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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43. A computer implemented method for tracking a deformable global shape of an object in motion in a sequence of digital medical images, the method performed by the computer comprising the steps of:
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providing a probabilistic subspace shape model for the deformable global shape derived from a set of training shapes; defining one or more control points along the deformable global shape; tracking each of the one or more control points as the object is in motion; estimating uncertainty of a location of a control point in motion, wherein estimating uncertainty includes measuring anisotropic uncertainty; building multiple appearance models for each control point, the multiple appearance models being based on uncertainty of a location of one or more of the control points; using robust information fusion to compute an estimate of the location and uncertainty of each control point; and combining the appearance models, the uncertainty, and the probabilistic subspace shape model to determine a current location of the object wherein the tracked deformable global shape resides inside the shape model subspace and is a most plausible shape according to uncertainties in global motion estimation local point measurements, and the deformable shape model. - View Dependent Claims (44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56)
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Specification