US 12,249,062 B2
Techniques for segmentation of lymph nodes, lung lesions and other solid or part-solid objects
Yongqiang Tan, Forest Hills, NY (US); Binsheng Zhao, Forest Hills, NY (US); and Lawrence H. Schwartz, New York, NY (US)
Assigned to The Trustees of Columbia University in the City of New York, New York, NY (US)
Filed by The Trustees of Columbia University in the City of New York, New York, NY (US)
Filed on Jun. 3, 2019, as Appl. No. 16/430,175.
Application 16/430,175 is a continuation of application No. 14/394,098, granted, now 10,354,377, previously published as PCT/US2013/036258, filed on Apr. 11, 2013.
Claims priority of provisional application 61/622,989, filed on Apr. 11, 2012.
Claims priority of provisional application 61/622,998, filed on Apr. 11, 2012.
Prior Publication US 2019/0355117 A1, Nov. 21, 2019
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/12 (2017.01); A61B 5/00 (2006.01); G06T 7/00 (2017.01); G06T 7/10 (2017.01); G06T 7/13 (2017.01); G06T 7/136 (2017.01); G06T 7/149 (2017.01); G06T 7/155 (2017.01); G06T 7/62 (2017.01); G06T 7/66 (2017.01); G06T 7/70 (2017.01); G06T 7/77 (2017.01); G06T 11/00 (2006.01); G06T 15/06 (2011.01); G06V 10/22 (2022.01); G06V 10/24 (2022.01); G06V 10/26 (2022.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/75 (2022.01); G06V 20/69 (2022.01); A61B 8/08 (2006.01); G06F 18/20 (2023.01); G06T 5/40 (2006.01); G06T 5/70 (2024.01); G06T 7/143 (2017.01); G06V 10/50 (2022.01); G06V 10/764 (2022.01); G06V 10/84 (2022.01)
CPC G06T 7/0012 (2013.01) [A61B 5/4887 (2013.01); G06T 7/10 (2017.01); G06T 7/12 (2017.01); G06T 7/136 (2017.01); G06T 7/149 (2017.01); G06T 7/155 (2017.01); G06T 7/62 (2017.01); G06T 7/66 (2017.01); G06T 7/70 (2017.01); G06T 7/77 (2017.01); G06T 11/008 (2013.01); G06T 15/06 (2013.01); G06V 10/22 (2022.01); G06V 10/225 (2022.01); G06V 10/245 (2022.01); G06V 10/26 (2022.01); G06V 10/267 (2022.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/755 (2022.01); G06V 20/695 (2022.01); A61B 5/004 (2013.01); A61B 5/4222 (2013.01); A61B 5/4244 (2013.01); A61B 5/4842 (2013.01); A61B 5/489 (2013.01); A61B 8/08 (2013.01); A61B 8/0808 (2013.01); A61B 8/0833 (2013.01); A61B 8/085 (2013.01); A61B 2576/02 (2013.01); A61B 2576/026 (2013.01); G06F 18/295 (2023.01); G06T 5/40 (2013.01); G06T 5/70 (2024.01); G06T 7/13 (2017.01); G06T 7/143 (2017.01); G06T 2200/04 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/10072 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10136 (2013.01); G06T 2207/20008 (2013.01); G06T 2207/20012 (2013.01); G06T 2207/20036 (2013.01); G06T 2207/20041 (2013.01); G06T 2207/20112 (2013.01); G06T 2207/20116 (2013.01); G06T 2207/20152 (2013.01); G06T 2207/20161 (2013.01); G06T 2207/20168 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30008 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30032 (2013.01); G06T 2207/30056 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30064 (2013.01); G06T 2207/30084 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30101 (2013.01); G06T 2207/30208 (2013.01); G06T 2210/41 (2013.01); G06V 10/50 (2022.01); G06V 10/764 (2022.01); G06V 10/85 (2022.01); G06V 20/698 (2022.01); G06V 2201/03 (2022.01); G06V 2201/031 (2022.01); G06V 2201/032 (2022.01)] 12 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining, on a processor, image data that indicates amplitude values at each of a plurality of voxels for a particular measurement modality;
determining, on a processor, an outer edge of a contiguous subset of voxels based on voxels that have an amplitude in a first amplitude range associated with a target object in image data of the particular measurement modality;
determining, on a processor, a center voxel, wherein a center distance from the center voxel to a closest voxel of the outer edge is greater than a distance from any neighbor of the center voxel to a corresponding closest voxel of the outer edge;
generating new image data by causing, on a processor, a location and size of the target object to be marked in the image data based on the center voxel and the center distance further comprising
determining, on a processor, a gradient value at a voxel; and
determining, on a processor, a reduced gradient equal to a product of the gradient with a fraction f that decreases with decreasing distance of the voxel from the center voxel,
wherein the new image data is based at least in part on the reduced gradient; and
presenting on a display device output image data based at least in part on the new image data with the location and size of the target object marked.
 
7. A method comprising:
obtaining, on a processor, image data that indicates amplitude values at each of a plurality of voxels for a particular measurement modality;
determining, on a processor, an outer edge of a contiguous subset of voxels based on voxels that have an amplitude in a first amplitude range associated with a target object in image data of the particular measurement modality;
determining, on a processor, a center voxel, wherein a center distance from the center voxel to a closest voxel of the outer edge is greater than a distance from any neighbor of the center voxel to a corresponding closest voxel of the outer edge;
determining, on a processor, a location and size of the target object in the image data based on the center voxel and the center distance further comprising determining, on a processor, a refined boundary by moving an initial boundary based on active contouring using as the initial boundary at least one of a marker as the center voxel and the center distance or a watershed boundary; and
presenting on a display device output image data based at least in part on the location and size of the target object or the refined boundary,
wherein:
the active contouring of the initial boundary further comprises determining a change in boundary position based, at least in part, on a potential well term independently weighted by a parameter α,
the potential well term comprises a product of a gradient of an edge indicator function g and a gradient of a level set function ϕ,
the active contouring of the initial boundary further comprises determining a change in boundary position based, at least in part, on a volume preserving mean curvature term of an equation comprising the volume preserving mean curvature term and the potential well term and wherein the volume preserving mean curvature term is independently weighted by an independent parameter β such that the potential well term is not weighted by the independent parameter β; and
the volume preserving mean curvature term comprises a product of a magnitude of the gradient of the level set function ϕ and a difference between a local mean curvature κ and a mean curvature for the initial boundary κmean.
 
8. A method comprising:
obtaining, on a processor, image data that indicates amplitude values at each of a plurality of voxels for a particular measurement modality;
determining, on a processor, an outer edge of a contiguous subset of voxels based on voxels that have an amplitude in a first amplitude range associated with a target object in image data of the particular measurement modality;
determining, on a processor, a center voxel, wherein a center distance from the center voxel to a closest voxel of the outer edge is greater than a distance from any neighbor of the center voxel to a corresponding closest voxel of the outer edge;
determining, on a processor, a location and size of the target object in the image data based on the center voxel and the center distance further comprising determining, on a processor, a refined boundary by moving an initial boundary based on active contouring using as the initial boundary at least one of a marker as the center voxel and the center distance or a watershed boundary; and
presenting on a display device output image data based at least in part on the location and size of the target object or the refined boundary,
wherein performing active contouring of the initial boundary comprises using an evolution equation that includes a first term that indicates deviations in amplitude for all voxels inside the boundary from a statistical metric of amplitude of all voxels inside the boundary and a second term that indicates deviations in amplitude for local voxels outside the boundary from a statistical metric of amplitude of the local voxels outside the boundary, wherein the local voxels outside the boundary exclude a larger number of voxels outside the initial boundary.