Three-dimensional image registration method for spiral CT angiography
First Claim
Patent Images
1. A computer-implemented method for three-dimensional image registration in an imaging technique utilizing mask images, and respective data thereto, obtained before opacification and contrast images acquired after the injection of a contrast media bolus, said method comprising the steps of:
- resampling serial axial CT mask and contrast images into respective isotropic 3D volumes;
selecting 3D feature points in said mask volume;
establishing correspondences in said contrast volume;
processing resulting sparse 3D image flow vectors by an iterative random algorithm and computing motion parameters, translation and rotation, in a least squares optimized sense that are agreed upon by at least a preset percentage of pairs whereby patient motion is found;
after patient motion is found, transforming said mask volume accordingly and subtracting it from said contrast volume; and
rendering and displaying a resulting volume.
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Abstract
A three-dimensional image registration method also uses an algorithm and applies it to the solution of such problems in 3D CT DSA. The method can deal with incomplete or partial volumetric data in registration and correct patient global motion prior to subtraction even when it is coupled with local unconscious/nonrigid movements. Experimental results demonstrate the effectiveness of this algorithm on several clinical spiral CT data.
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Citations
24 Claims
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1. A computer-implemented method for three-dimensional image registration in an imaging technique utilizing mask images, and respective data thereto, obtained before opacification and contrast images acquired after the injection of a contrast media bolus, said method comprising the steps of:
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resampling serial axial CT mask and contrast images into respective isotropic 3D volumes; selecting 3D feature points in said mask volume; establishing correspondences in said contrast volume; processing resulting sparse 3D image flow vectors by an iterative random algorithm and computing motion parameters, translation and rotation, in a least squares optimized sense that are agreed upon by at least a preset percentage of pairs whereby patient motion is found; after patient motion is found, transforming said mask volume accordingly and subtracting it from said contrast volume; and rendering and displaying a resulting volume. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer-implemented method for three-dimensional image registration in an imaging technique utilizing mask images, and respective data related thereto, obtained before opacification and contrast images, and respective data related thereto, acquired after the injection of a contrast media bolus, said method comprising the steps of:
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resampling serial axial CT mask and contrast images into respective isotropic 3D volumes; selecting 3D feature points in said mask volume; establishing correspondences in said contrast volume; processing resulting sparse 3D image flow vectors by an iterative random algorithm as follows; (a) start with a desired maximum individual residual error ε and
desired size s;(b)select randomly a small number of points, Ni, from a set of points in said mask volume, V to form S and the corresponding points from a set of points in contrast volume, W to form S'"'"'; (c) compute a rotation matrix R and a translation vector t for a set S and a set S'"'"' using unit quaternions and if the maximum individual residual error is greater than ε
, repeat this step until such is no longer the case;(d) randomly pick a fixed number of new points from the remaining ones in V and W, and compute new transform parameters and, if the error constraint is again satisfied, append these points to S and S'"'"' and if not, repeat this step; and (e) repeat step (d) until the size of S and S'"'"' is greater than or equal to s, at which point terminate with V'"'"'←
S and W'"'"'←
S'"'"', or restart with step (b) if, after a predetermined number of times, T1, of repeating step (d), the size of S does not reach s, or restart with step (b) with a new ε
if for the given ε
, the desired size s is not obtained after a predetermined number of restarts, T2. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14, 15, 24)
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16. A computer-implemented method for three-dimensional image registration in an imaging technique utilizing mask images, and respective data related thereto, obtained before opacification and contrast images, and respective data related thereto, acquired after the injection of a contrast media bolus, said method comprising the steps of:
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resampling serial axial CT mask and contrast images into respective isotropic 3D volumes; selecting a set of 3D feature points in said mask volume; establishing correspondence with a set of points in said contrast volume; processing resulting sparse 3D image flow vectors by an iterative random algorithm as follows; (a) start with a desired maximum individual residual error ε and
desired size s;(b)select randomly a small number of points, Ni, from a set of points in said mask volume, V to form S and the corresponding points from a set of points in said contrast volume, W to form S'"'"'; (c) compute a rotation matrix R and a translation vector t for a set S and a set S'"'"' using unit quaternions, wherein a unit quaternion expresses a unit rotation, and if the maximum individual residual error is greater than ε
, repeat this step until such is no longer the case;(d) randomly pick a fixed number of new points from the remaining ones in V and W, and compute new transform parameters and, if the error constraint is again satisfied, append these points to S and S'"'"' and if not, repeat this step; and (e) repeat step (d) until the size of S and S'"'"' is greater than or equal to s, at which point terminate with V'"'"'←
S and W'"'"'←
S'"'"', or restart with step (b) if, after a predetermined number of times, T1, of repeating step (d), the size of S does not reach s, or restart with step (b) with a new ε
if for the given ε
, the desired size s is not obtained after a predetermined number of restarts, T2. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23)
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Specification