Volumetric image data processing
View Patent ↗A method, apparatus, computer readable medium storing computer readable instructions are disclosed for processing volumetric image data. According to the method, 3-dimensional data points are collected. A plurality of 2-dimensional image maps is obtained from the 3-dimensional data points. At least one of the plurality of 2D image maps is extracted to form at least one image frame. A frame gallery is created from the at least one image frame.
1. A method for processing volumetric image data comprising:
obtaining a plurality of 2-dimensional image maps from 3-dimensional data points;
extracting at least one of the plurality of 2-dimensional image maps to form a plurality of image frames; and
creating a frame gallery from the plurality of image frames including a radically different frame that is radically different from preceding and following frames based on a value of importance,
wherein the value of importance includes a Gaussian weighted sum of the preceding frame and the radically different frame and the following frame and the radically different frame.
2. The method of claim 1 , wherein the 3-dimensional data points are generated from a spherical surface.
3. The method of claim 1 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.
4. The method of claim 1 , wherein the radically different frame is radically different from the preceding and following frames based on the value of importance being greater than a predetermined threshold.
5. An apparatus for processing volumetric image data comprising:
an obtaining unit that obtains a plurality of 2-dimensional image maps from 3-dimensional data points;
an extracting unit that extracts at least one of the plurality of 2-dimensional image maps to form a plurality of image frames; and
a creating unit that creates a frame gallery from the plurality of image frames including a radically different frame that is radically different from preceding and following frames based on a value of importance,
wherein the value of importance includes a Gaussian weighted sum of the preceding frame and the radically different frame and the following frame and the radically different frame.
6. The apparatus of claim 5 , wherein the 3-dimensional data points are generated from a spherical surface.
7. The apparatus of claim 5 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.
8. The apparatus of claim 5 , wherein the radically different frame is radically different from the preceding and following frames based on the value of importance being greater than a predetermined threshold.
9. A method for processing volumetric image data, comprising:
obtaining a plurality of 2-dimensional image maps from 3-dimensional data points;
constructing a volumetric image data based on the plurality of 2-dimensional image maps and temporal data associated with each of the plurality of 2-dimensional image maps;
applying a critical point graph to the volumetric image data; and
creating a frame gallery from a plurality of image frames including at least one of a radically different frame or a representative frame,
wherein a radically different frame is determined by:
calculating a difference sum between two image frames by the sum of the square of difference between all corresponding pixels of the two image frames; and
computing a value of importance for each image frame based on the calculated difference sum, the radically different frame being determined based on the computed value of importance for each image frame; and
wherein a representative frame is determined by:
calculating a difference sum between two image frames by the sum of the square of difference between all corresponding pixels of the two image frames;
computing a value of importance for each image frame based on the calculated difference sum; and
dividing the volumetric image data into bins based on the computed value of importance for each image frame, one frame from each of the bins being extracted as the representative frame.
10. The method of claim 9 , wherein the applying a critical point graph comprises:
computing a gradient field of the volumetric image data and critical points based on eigenvalues and eigenvectors of a Jacobian matrix; and
generating the critical point graph based on the computed critical points and streamlines in between.
11. The method of claim 9 , wherein the 3-dimensional data points are generated from a spherical surface.
12. The method of claim 9 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.
13. A method for processing volumetric image data comprising:
obtaining a plurality of 2-dimensional image maps from 3-dimensional data points;
extracting at least one of the plurality of 2-dimensional image maps to form a plurality of image frames; and
creating a frame gallery from the plurality of image frames including a representative frame that represents a certain amount of importance relative to preceding and following frames,
wherein the value of importance includes a Gaussian weighted sum of the preceding frame and the representative frame and the following frame and the representative frame.
14. The method of claim 13 , wherein the 3-dimensional data points are generated from a spherical surface.
15. The method of claim 13 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.
16. An apparatus for processing volumetric image data comprising:
an obtaining unit that obtains a plurality of 2-dimensional image maps from 3-dimensional data points;
an extracting unit that extracts at least one of the plurality of 2-dimensional image maps to form a plurality of image frames; and
a creating unit that creates a frame gallery from the plurality of image frames including a representative frame that represents a certain amount of importance relative to preceding and following frames,
wherein the amount of importance includes a Gaussian weighted sum of the preceding frame and the representative frame and the following frame and the representative frame.
17. The apparatus of claim 16 , wherein the 3-dimensional data points are generated from a spherical surface.
18. The apparatus of claim 16 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.
19. A method for processing volumetric image data, comprising:
obtaining a plurality of 2-dimensional image maps from 3-dimensional data points;
constructing a volumetric image data based on the plurality of 2-dimensional image maps and temporal data associated with each of the plurality of 2-dimensional image maps;
applying a critical point graph to the volumetric image data; and
creating a frame gallery from a plurality of image frames including a representative frame that represents a certain amount of importance relative to preceding and following frames,
wherein the amount of importance includes a Gaussian weighted sum of the preceding frame and the representative frame and the following frame and the representative frame.
20. The method of claim 19 , wherein the 3-dimensional data points are generated from a spherical surface.
21. The method of claim 19 , wherein the 3-dimensional data points are generated from event-related potential (ERP) data.