Aligning data sets based on identified fiducial markers
Inventors
YOHE, Michael Lee • HARDWICK, Andrew Craig • RUSSELL, Kyle Jordan • CANTOR, Chanler Megan Crowe • ETHEREDGE, Charles Thomas
Assignees
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Publication Number
US-11600009-B2
Publication Date
2023-03-07
Expiration Date
Abstract
Techniques are disclosed for aligning fiducial markers that commonly exist in each of multiple different N-dimensional (N-D) data sets. Notably, the N-D data sets are at least three-dimensional (3D) data sets. A first set and a second set of N-D data are accessed. A set of one or more fiducial markers that commonly exist in both those sets are identified. Based on the fiducial markers, one or more transformations are performed to align the two sets. Performing this alignment process results in at least a selected number of the common fiducial markers that exist in the two sets being within a threshold alignment relative to one another.
Core Innovation
Not explicitly described in patent.
Not explicitly described in patent.
Claims Coverage
The independent claims (clm-00001, clm-00011, and clm-00019) cover aligning fiducial markers that commonly exist in multiple N-dimensional, at least 3D, data sets by identifying common fiducial markers and applying transformations so that at least a selected number of common fiducial markers are within a threshold alignment relative to corresponding markers in the other data set.
Aligning common fiducial markers across N-dimensional data sets with threshold alignment
Access a first set of N-D data; access a second set of N-D data; identify a set of one or more fiducial markers that commonly exist in both the first set of N-D data and the second set of N-D data; and based on the identified set of one or more fiducial markers, perform one or more transformations to the first set of N-D data and/or the second set of N-D data to align the first set of N-D data with the second set of N-D data, wherein the aligning results in at least a selected number of the common fiducial markers that exist in the second set of N-D data being within a threshold alignment relative to the corresponding common fiducial markers that exist in the first set of N-D data.
Computer system aligning common fiducial markers in multiple 3D data sets with threshold alignment
A computer system with one or more processors and one or more computer-readable hardware storage devices configured to access a first set of 3D data; access a second set of 3D data; identify a set of one or more fiducial markers that commonly exist in both the first set of 3D data and the second set of 3D data; and based on the identified set of one or more fiducial markers, perform one or more transformations to the first set of 3D data and/or the second set of 3D data to align the first set of 3D data with the second set of 3D data, wherein the aligning results in at least a selected number of the common fiducial markers that exist in the second set of 3D data being within a threshold alignment relative to the corresponding common fiducial markers that exist in the first set of 3D data.
Computer system aligning 3D data sets by common fiducials and threshold alignment and identifying differences
A computer system with one or more processors and one or more computer-readable hardware storage devices configured to access a first set of 3D data; access a second set of 3D data; identify a set of one or more fiducial markers that commonly exist in both the first set of 3D data and the second set of 3D data; based on the identified set of one or more fiducial markers, perform one or more transformations to the first set of 3D data and/or the second set of 3D data to align the first set of 3D data with the second set of 3D data, wherein the aligning results in at least a selected number of the common fiducial markers that exist in the second set of 3D data being within a threshold alignment relative to the corresponding common fiducial markers that exist in the first set of 3D data; and subsequent to aligning the first set of 3D data with the second set of 3D data, identify one or more differences that exist between the first set of 3D data and the second set of 3D data.
Across the independent claims, alignment is achieved by identifying fiducial markers common to both data sets and applying transformations so that a selected number of those common fiducial markers meet a threshold alignment criterion; in clm-00019 and associated dependent claims, the aligned results are further used to identify one or more differences between the data sets.
Stated Advantages
Documented Applications
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