Patent US7194117B2 successfully refreshed from Google Patents.
US7194117B2
Expired / Lapsed
US
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System and method for performing a three-dimensional virtual examination of objects, such as internal organs
Assignee: Research Foundation of the State University of New York
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Filing: 2001-02-05
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Granted: 2007-03-20
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Expires: 2021-02-05
Abstract
Abstract Methods for generating a three-dimensional visualization image of an object, such as an internal organ, using volume visualization techniques are provided. The techniques include a multi-scan imaging method; a multi-resolution imaging method; and a method for generating a skeleton of a complex three dimension object. The applications include virtual cystoscopy, virtual laryngoscopy, virtual angiography, among others.
Inventors
- 👤 Arie E. Kaufman
- 👤 Zhengrong Liang
- 👤 Mark R. Wax
- 👤 Ming Wan
- 👤 Dongqing Chen
- 👤 Bin Li
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 22:36
CPC Classifications
A; A61; A61B; A61B5/00; A61B5/05; A61B5/055; A61B6/00; A61B6/02; A61B6/03; A61B6/032; G; G06; G06T; G06T15/00; G06T15/08; G06T19/00; G06T7/00; G06T7/10; G06T7/11; G09; G09B; G09B23/00; G09B23/28; A61B5/72; A61B5/7235; A61B5/7253; A61B5/726; A61B8/00; A61B8/48; A61B8/483; G06T2207/00; G06T2207/10; G06T2207/10072; G06T2207/30; G06T2207/30004; G06T2207/30028; G06T2207/30084; G06T2207/30172; G06T2210/00; G06T2210/41; G06T2219/00; G06T2219/028; G06T2219/20; G06T2219/2004
Claims Analysis
Total Claims: 22
Claim 1
Independent Claim
131 words
A method of performing computed assisted diagnosis of a region of interest, comprising: acquiring imaging scan data including at least a portion of the region of interest; converting the imaging scan data to a volume representation including a plurality of voxels, at least a portion of the voxels representing a surface of the region of interest; analyzing a first portion of voxels representing the surface to determine a context surface texture feature of the region of interest; analyzing a second portion of voxels representing the surface to identify a local surface texture feature; comparing the local surface texture feature to the context surface texture feature and identifying the local surface texture as indicative of an abnormality if the local surface texture is at least sufficiently different from the context texture feature.
Claim 2
Independent Claim
131 words
A method of performing computed assisted diagnosis of a region of interest, comprising: acquiring imaging scan data including at least a portion of the region of interest; converting the imaging scan data to a volume representation including a plurality of voxels, at least a portion of the voxels representing a surface of the region of interest; analyzing a first portion of voxels representing the surface to determine a context surface texture feature of the region of interest; analyzing a second portion of voxels representing the surface to identify a local surface texture feature; comparing the local surface texture feature to the context surface texture feature and identifying the local surface texture as indicative of an abnormality if the local surface texture is at least sufficiently different from the context texture feature.
Claim 3
Dependent Claim
37 words
The method of performing computed assisted diagnosis according to claim 1 , wherein the local surface texture feature is included in a probability density function characterizing a correlation between two voxels of the second portion of voxels.
Claim 4
Dependent Claim
19 words
The method of performing computed assisted diagnosis according to claim 2 , wherein the two voxels are adjacent voxels.
Claim 5
Dependent Claim
32 words
The method of performing computer assisted diagnosis according to claim 2 , wherein intensity values of said second portion of voxels are used to generate an estimate of the probability density function.
Claim 6
Dependent Claim
58 words
The method of performing computer assisted diagnosis according to claim 4 , wherein a plurality of voxel intensity values are used to generate a cumulating distribution function of the region of interest and a local cumulating distribution function, and wherein the local cumulating distribution function is compared against the context cumulating distribution function to identify regions of abnormality.
Claim 7
Dependent Claim
36 words
The method of performing computer assisted diagnosis according to claim 5 , wherein a distance is determined between said local cumulating distribution function and said context cumulating distribution function, the distance providing a measure of abnormality.
Claim 8
Dependent Claim
50 words
The method of performing computer assisted diagnosis according to claim 6 , wherein the distance is used to assign intensity values to the voxels representing a surface of the region of interest and wherein said method further comprises displaying said voxels such that variations in intensity represent regions of abnormality.
Claim 9
Dependent Claim
26 words
The method of performing computer assisted diagnosis according to claim 7 , wherein the region of interest includes the colon and wherein the abnormality includes polyps.
Claim 10
Dependent Claim
28 words
The method of performing computer assisted diagnosis according to claim 1 , wherein the region of interest includes the aorta and wherein the abnormality includes abdominal aortic aneurysms.
Claim 11
Independent Claim
156 words
A method of performing computed assisted diagnosis of a region of interest, comprising: acquiring imaging scan data including at least a portion of the region of interest; converting the imaging scan data to a volume representation including a plurality of voxels, at least a portion of the voxels representing a surface of the region of interest; analyzing a first portion of voxels representing the surface to determine a context surface texture feature of the region of interest; analyzing a second portion of voxels representing the surface to identify a local surface texture feature; comparing the local surface texture feature to the context surface texture feature and identifying regions as indicative of an abnormality if the local surface texture of the region is at least sufficiently different from the context surface texture feature; and analyzing said identified regions where the local surface texture is indicative of an abnormality for a geometric feature further indicative of an abnormality.
Claim 12
Independent Claim
156 words
A method of performing computed assisted diagnosis of a region of interest, comprising: acquiring imaging scan data including at least a portion of the region of interest; converting the imaging scan data to a volume representation including a plurality of voxels, at least a portion of the voxels representing a surface of the region of interest; analyzing a first portion of voxels representing the surface to determine a context surface texture feature of the region of interest; analyzing a second portion of voxels representing the surface to identify a local surface texture feature; comparing the local surface texture feature to the context surface texture feature and identifying regions as indicative of an abnormality if the local surface texture of the region is at least sufficiently different from the context surface texture feature; and analyzing said identified regions where the local surface texture is indicative of an abnormality for a geometric feature further indicative of an abnormality.
Claim 13
Dependent Claim
37 words
The method of performing computed assisted diagnosis according to claim 10 , wherein the local surface texture feature is included in a probability density function characterizing a correlation between two voxels of the second portion of voxels.
Claim 14
Dependent Claim
19 words
The method of performing computed assisted diagnosis according to claim 11 , wherein the two voxels are adjacent voxels.
Claim 15
Dependent Claim
31 words
The method of performing computer assisted diagnosis according to claim 12 , wherein intensities of said second portion of voxels are used to generate an estimate of the probability density function.
Claim 16
Dependent Claim
57 words
The method of performing computer assisted diagnosis according to claim 13 , wherein a plurality of voxel intensities are used to generate a cumulating distribution function of the region of interest and a local cumulating distribution function, and wherein the local cumulating distribution function is compared against the context cumulating distribution function to identify regions of abnormality.
Claim 17
Dependent Claim
36 words
The method of performing computer assisted diagnosis according to claim 14 , wherein a distance is determined between said local cumulating distribution function and said context cumulating distribution function, the distance providing a measure of abnormality.
Claim 18
Dependent Claim
50 words
The method of performing computer assisted diagnosis according to claim 15 , wherein the distance is used to assign intensity values to the voxels representing a surface of the region of interest and wherein said method further comprises displaying said voxels such that variations in intensity represent regions of abnormality.
Claim 19
Dependent Claim
26 words
The method of performing computer assisted diagnosis according to claim 16 , wherein the region of interest includes the colon and wherein the abnormality includes polyps.
Claim 20
Dependent Claim
28 words
The method of performing computer assisted diagnosis according to claim 10 , wherein the region of interest includes the aorta and wherein the abnormality includes abdominal aortic aneurysms.
Claim 21
Dependent Claim
43 words
The method of performing computer assisted diagnosis according to claim 10 , wherein the surface is represented as a second differentiable surface where each surface volume unit has an associate Gauss curvature and wherein said Gauss curvatures combine to form said geometric features.
Claim 22
Dependent Claim
41 words
The method of performing computer assisted diagnosis according to claim 10 , wherein a plurality of predetermined geometrical feature templates are defined and wherein the geometric features of said surface are compared to said templates to determine a geometric feature classification.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2010-03-19 | 2010-09-18 | 2011-03-20 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2014-03-19 | 2014-09-18 | 2015-03-20 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2018-03-19 | 2018-09-18 | 2019-03-20 | $7700.00 | Window Closed / Lapsed |