Method and apparatus for generating a precision sub-volume within three-dimensional image datasets
A method, apparatus and computer program for generating a sub-volume within a 3D dataset in a consistent, repeatable fashion. To accomplish this, geometric object(s) (e.g., 2D planes) are placed at precise anatomic landmarks with precise sizes and orientations. This serves to divide the 3D object into multiple parts (e.g., a first portion of the 3D volume has a first set of voxels and a second portion of the 3D volume has a second set of voxels). This process continues as multiple additional geometric objects are placed so that certain features of the 3D dataset can be extracted (i.e., shown with the best viewing settings). This process when used in conjunction with a radiologist's checklist enables efficient volume-by-volume viewing.
1. A method comprising:
using a 3D image
wherein said 3D image is obtained from a CT scan, a MRI scan, a PET scan, a SPECT scan or an ultrasound scan, and
wherein said 3D image comprises anatomic structures;
performing segmentation of said 3D image into said anatomic structures,
selecting a first anatomic landmark, a second anatomic landmark, a third anatomic landmark and a fourth anatomic landmark from said anatomic structures wherein said first anatomic landmark, said second anatomic landmark, said third anatomic landmark and said fourth anatomic landmark are different anatomic landmarks;
determining a first 3D coordinate corresponding to said first anatomic landmark, a second 3D coordinate corresponding to said second anatomic landmark, a third 3D coordinate corresponding to said third anatomic landmark and a fourth 3D coordinate corresponding to said fourth anatomic landmark wherein said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate are different coordinates; and
generating a digital geometric object within said 3D image
wherein a configuration of said digital geometric object is different from said anatomic structures' configurations,
wherein a boundary of said digital geometric object is determined by at least said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate, and
wherein the digital geometric object is used to define a boundary of a sub-volume within the 3D dataset.
2. The method of claim 1 further comprising wherein the digital geometric object consists of one of the group of: a curving surface; and, a 3D object.
3. The method of claim 1 further comprising wherein a first image processing technique is performed on the sub-volume and a second image processing technique is performed on portions of the 3D volume other than the sub-volume.
4. The method of claim 1 further comprising wherein the sub-volume is defined by at least one additional digital geometric object placed in proximity to at least one additional pre-selected anatomic landmark within the 3D dataset.
5. The method of claim 4 further comprising wherein the digital geometric object is connected to the at least one additional digital geometric object to further define the boundary of the sub-volume within the 3D dataset.
6. The method of claim 1 wherein the anatomic landmarks identified by artificial intelligence.
7. The method of claim 1 wherein the segmentation is performed within the sub-volume.
8. The method of claim 1 wherein filtering is performed within the sub-volume.
9. The method of claim 1 wherein the sub-volume is viewed with a 2D monitor or an extended reality display.
10. The method of claim 1 further comprising wherein automatic shape recognition technology is used to identify findings within the sub-volume.
11. The method of claim 1 further comprising wherein the sub-volume is generated for an item in a radiology checklist.
12. The method of claim 1 further comprising wherein the sub-volume is viewed with a prioritized volume rendering imaging technique.
13. The method of claim 1 further comprising wherein the sub-volume is viewed in conjunction with voxel manipulation.
14. The method of claim 1 further comprising wherein the anatomic landmark is named and labeled by an AI algorithm and subsequently displayed to a user.
15. The method of claim 1 further comprising wherein an anatomic feature within the sub-volume is segmented wherein a first portion of the anatomic feature is displayed with a first imaging processing technique and a second portion of the anatomic feature is displayed with a second image processing technique.
16. The method of claim 1 further comprising wherein eye tracking of a user is performed as the user looks at the sub-volume.
17. The method of claim 1 further comprising wherein a modified segmented structure is performed within the sub-volume.
18. The method of claim 1 further comprising wherein analysis of the sub-volume is performed.
19. A non-transitory computer readable medium having computer readable code thereon for image processing, the medium comprising instructions for:
using a 3D image
wherein said 3D image is obtained from a CT scan, a MRI scan, a PET scan, a SPECT scan or an ultrasound scan, and
wherein said 3D image comprises anatomic structures;
performing segmentation of said 3D image into said anatomic structures,
selecting a first anatomic landmark, a second anatomic landmark, a third anatomic landmark and a fourth anatomic landmark from said anatomic structures wherein said first anatomic landmark, said second anatomic landmark, said third anatomic landmark and said fourth anatomic landmark are different anatomic landmarks;
determining a first 3D coordinate corresponding to said first anatomic landmark, a second 3D coordinate corresponding to said second anatomic landmark, a third 3D coordinate corresponding to said third anatomic landmark and a fourth 3D coordinate corresponding to said fourth anatomic landmark wherein said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate are different coordinates; and
generating a digital geometric object within said 3D image
wherein a configuration of said digital geometric object is different from said anatomic structures' configurations,
wherein a boundary of said digital geometric object is determined by at least said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate, and
wherein the digital geometric object is used to define a boundary of a sub-volume within the 3D dataset.
20. A computer system comprising:
a memory; and
a processor;
wherein the memory is encoded with an application providing image processing, that when performed on the processor, provides a process for processing information, the process causing the computer system to perform the operations of:
using a 3D image
wherein said 3D image is obtained from a CT scan, a MRI scan, a PET scan, a SPECT scan or an ultrasound scan, and
wherein said 3D image comprises anatomic structures;
performing segmentation of said 3D image into said anatomic structures,
selecting a first anatomic landmark, a second anatomic landmark, a third anatomic landmark and a fourth anatomic landmark from said anatomic structures wherein said first anatomic landmark, said second anatomic landmark, said third anatomic landmark and said fourth anatomic landmark are different anatomic landmarks;
determining a first 3D coordinate corresponding to said first anatomic landmark, a second 3D coordinate corresponding to said second anatomic landmark, a third 3D coordinate corresponding to said third anatomic landmark and a fourth 3D coordinate corresponding to said fourth anatomic landmark wherein said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate are different coordinates; and
generating a digital geometric object within said 3D image
wherein a configuration of said digital geometric object is different from said anatomic structures' configurations,
wherein a boundary of said digital geometric object is determined by at least said first 3D coordinate, said second 3D coordinate, said third 3D coordinate and said fourth 3D coordinate, and
wherein the digital geometric object is used to define a boundary of a sub-volume within the 3D dataset.