Method and apparatus for automatic alingment of volumetric images containing common subject matter

Claim 3

The method of claim 1 wherein the global vectors are derived according to steps comprising: a. utilizing the translation vectors to generate a single rotation vector maximally consistent with the mapping vectors and relating the first volume to the second volume; b. utilizing the mapping vectors to generate a single translation vector maximally consistent with the mapping vectors and relating the first volume to the second volume, the rotation and translation vectors encoding spatial displacement between the first and second volumes.

Claim 4

The method of claim 2 wherein the single rotation vector and the single translation vector are generated by a least-squares fit.

Claim 5

The method of claim 1 further comprising the step of preprocessing each set of frames to reduce high-frequency noise and to select for anatomical features of a predetermined size range.

Claim 6

The method of claim 4 wherein the preprocessing step comprises filtering with the Laplacian of a Gaussian.

Claim 9

The method of claim 6 wherein the subject matter comprises features each having a size, the target window being larger than the size of the smallest feature.

Claim 10

The method of claim 6 wherein the search block has 256 pixels and the target windows each have 2304 pixels.

Claim 11

The method of claim 6 wherein the global vectors are derived according to steps comprising: a. utilizing the translation vectors to generate a single rotation vector maximally consistent with the mapping vectors and relating the first volume to the second volume; b. utilizing the mapping vectors to generate a single translation vector maximally consistent with the mapping vectors and relating the first volume to the second volume, the rotation and translation vectors encoding spatial displacement between the first and second volumes.

Claim 12

The method of claim 6 further comprising the step of preprocessing each set of frames to reduce high-frequency noise and to select for anatomical features of a predetermined size range.

Claim 13

The method of claim 10 wherein the preprocessing step comprises filtering with the Laplacian of a Gaussian.

Claim 14

The method of claim 6 wherein the new search window is offset with respect to the previous search window so as to be adjacent thereto.

Claim 15

Apparatus for aligning first and second sets of digitized image frames, each set being representative of a volume and comprising a series of frames digitally encoding contiguous planar slices of the volume, the sets including common volumetric subject matter, said apparatus comprising: a. a first set of memory buffers for storing the first set of digitized frames; b. a second set of memory buffers for storing the second set of digitized frames; c. analysis means configured to: i. identify common volumetric subject matter by systematically comparing groups of pixels from a selected frame of the first frame set to groups of pixels of a plurality of frames of the second frame set; ii. define a field of three-directional translation vectors mapping each of a plurality of pixel groups of the first frame set to corresponding pixel groups of the second frame set with the smallest mapping error; iii. derive, from the translation vectors, a set of global vectors specifying translation and rotation between the volumes; and iv. align, based on the global vectors, the pixels of the first frame set with the pixels of the second frame set such that the volumes encoded by the frame sets are aligned.

Claim 16

Apparatus for aligning first and second sets of digitized image frames, each set being representative of a volume and comprising a series of frames digitally encoding contiguous planar slices of the volume, the sets including common volumetric subject matter, said apparatus comprising: a. a first set of memory buffers for storing the first set of digitized frames; b. a second set of memory buffers for storing the second set of digitized frames; c. analysis means configured to: i. identify common volumetric subject matter by systematically comparing groups of pixels from a selected frame of the first frame set to groups of pixels of a plurality of frames of the second frame set; ii. define a field of three-directional translation vectors mapping each of a plurality of pixel groups of the first frame set to corresponding pixel groups of the second frame set with the smallest mapping error; iii. derive, from the translation vectors, a set of global vectors specifying translation and rotation between the volumes; and iv. align, based on the global vectors, the pixels of the first frame set with the pixels of the second frame set such that the volumes encoded by the frame sets are aligned.

Claim 17

The apparatus of claim 13 wherein the analysis means is further configured to preprocess each set of frames to reduce high-frequency noise and to select for anatomical features of a predetermined size range.

Claim 18

Apparatus for aligning first and second sets of digitized image frames, each set being representative of a volume and comprising a series of frames digitally encoding contiguous planar slices of the volume, the sets including common volumetric subject matter, said apparatus comprising: a. a computer memory comprising a first set of memory buffers for storing the first set of digitized frames and a second set of memory buffers for storing the second set of digitized frames; b. analysis means configured to: i. define, in a first memory buffer of the first set, a search block comprising a plural number of pixels; ii. define, at identical locations in each of a plurality of memory buffers of the second set, a target window comprising a plural number of pixels at least as large as the number of pixels in the search block; iii. search for common volumetric subject matter by comparing the pixels of the search block with the pixels of each of the target windows; iv. derive an error factor representative of image differences therebetween; v. identify common volumetric subject matter by selecting the target-window pixels associated with the smallest error factor; vi. define and store, in the computer memory, a three-dimensional translation vector mapping the search block to the selected target-window pixels; vii. define, in the first frame of the first set, a new search block comprising a group of pixels offset with respect to the previous search block; viii. repeat (ii) through (vi); ix. complete the search for common volumetric subject matter by repeating (vii) and (viii) until all of the pixels of the first frame of the first set have been defined in a search block; xii. derive, from the translation vectors, a set of global vectors specifying translation and rotation between the common volumetric subject matter and store the global vectors in the computer memory; and xiii. based on the global vectors, align the first frame set with the second frame set.

Claim 19

Apparatus for aligning first and second sets of digitized image frames, each set being representative of a volume and comprising a series of frames digitally encoding contiguous planar slices of the volume, the sets including common volumetric subject matter, said apparatus comprising: a. a computer memory comprising a first set of memory buffers for storing the first set of digitized frames and a second set of memory buffers for storing the second set of digitized frames; b. analysis means configured to: i. define, in a first memory buffer of the first set, a search block comprising a plural number of pixels; ii. define, at identical locations in each of a plurality of memory buffers of the second set, a target window comprising a plural number of pixels at least as large as the number of pixels in the search block; iii. search for common volumetric subject matter by comparing the pixels of the search block with the pixels of each of the target windows; iv. derive an error factor representative of image differences therebetween; v. identify common volumetric subject matter by selecting the target-window pixels associated with the smallest error factor; vi. define and store, in the computer memory, a three-dimensional translation vector mapping the search block to the selected target-window pixels; vii. define, in the first frame of the first set, a new search block comprising a group of pixels offset with respect to the previous search block; viii. repeat (ii) through (vi); ix. complete the search for common volumetric subject matter by repeating (vii) and (viii) until all of the pixels of the first frame of the first set have been defined in a search block; xii. derive, from the translation vectors, a set of global vectors specifying translation and rotation between the common volumetric subject matter and store the global vectors in the computer memory; and xiii. based on the global vectors, align the first frame set with the second frame set.

Claim 20

The apparatus of claim 15 wherein the subject matter comprises features each having a size, the target window being larger than the size of the smallest feature.

Claim 21

The apparatus of claim 15 wherein the search block has 256 pixels and the target windows each have 2304 pixels.

Claim 22

The method of claim 6 wherein the new search window is offset with respect to the previous search window to overlap therewith.