Apparatus and method for object pose estimation in a medical image
Apparatus and method for object pose estimation are disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive a plurality of sets of echo data, wherein the plurality of sets of echo data is configured for generation of a plurality of echo depth maps, segment the plurality of echo depth maps, determine a depth datum related to pixels of an object of interest as a function of the plurality of segmented echo depth maps, generate a three dimensional (3D) point cloud related to the object of interest as a function of the depth datum and generate a pose datum of the object of interest as a function of the 3D point cloud.
1. An apparatus for object pose estimation in a medical image, the apparatus comprising:
one or more ultrasound imaging systems located on a surface of a subject;
an object of interest configured to be placed within the subject;
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:
receive a plurality of sets of echo data from the one or more ultrasound imaging systems, wherein the plurality of sets of echo data is configured for generation of a plurality of echo depth maps;
segment the plurality of echo depth maps;
determine a depth datum related to pixels of the object of interest as a function of the plurality of segmented echo depth maps;
generate a three dimensional (3D) point cloud related to the object of interest as a function of the depth datum; and
generate a pose datum of the object of interest as a function of the 3D point cloud, wherein generating the pose datum comprises:
training a pose estimation model using pose estimation training data, wherein the pose estimation training data comprises exemplary 3D point clouds correlated to exemplary pose datums; and
generating the pose datum using the trained pose estimation model.
2. The apparatus of claim 1 , wherein receiving the plurality of sets of echo data comprises receiving the plurality of sets of echo data from a plurality of echo transducers, wherein each of the plurality of echo transducers is located at a different angle.
3. The apparatus of claim 1 , wherein the plurality of sets of echo data is related to a cadaveric organ with a catheter inserted into it.
4. The apparatus of claim 1 , wherein segmenting the plurality of echo depth maps comprises:
extracting object features of the object of interest from the plurality of echo depth maps; and
segmenting the plurality of echo depth maps as a function of the object features.
5. The apparatus of claim 1 , wherein determining the depth datum comprises:
training a depth model using depth training data, wherein the depth training data comprises exemplary segmented echo depth maps correlated to exemplary depth datums; and
determining the depth datum using the trained depth model.
6. The apparatus of claim 1 , wherein the pose estimation model comprises a regression model and the pose estimation training data comprises synthetic 3D point clouds generated from a computer aided design (CAD) model of the object of interest.
7. The apparatus of claim 1 , wherein:
the pose datum comprises a 6D pose datum; and
generating the pose datum comprises generating the 6D pose datum related to a second object of interest relative to the object of interest as a function of a rigidity constraint between the object and the second object of interest.
8. The apparatus of claim 7 , further comprising:
a catheter, wherein the catheter comprises:
the object of interest comprising a distinct shape; and
an electrode comprising the second object of interest.
9. The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to:
generate a 3D model as a function of the 3D point cloud;
generate a user interface including the 3D model; and
display the user interface including the 3D model on a display device.
10. The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to generate an anatomical datum as a function of the pose datum, wherein the anatomical datum comprises a dimension datum of the object of interest.
11. The apparatus of claim 1 , wherein the pose datum comprises a five degree (5D) pose datum.
12. A method for object pose estimation in a medical image, the method comprising:
placing, one or more ultrasound imaging systems on a surface of a subject;
positioning an object of interest configured to be within the subject;
receiving, using at least a processor and from the one or more ultrasound imaging systems, a plurality of sets of echo data, wherein the plurality of sets of echo data is configured for generation of a plurality of echo depth maps;
segmenting, using the at least a processor, the plurality of echo depth maps;
determining, using the at least a processor, a depth datum related to pixels of the object of interest as a function of the plurality of segmented echo depth maps;
generating, using the at least a processor, a three dimensional (3D) point cloud related to the object of interest as a function of the depth datum; and
generating, using the at least a processor, a pose datum of the object of interest as a function of the 3D point cloud, wherein generating the pose datum comprises:
training a pose estimation model using pose estimation training data, wherein the pose estimation training data comprises exemplary 3D point clouds correlated to exemplary pose datums; and
generating the pose datum using the trained pose estimation model.
13. The method of claim 12 , wherein receiving the plurality of sets of echo data comprises receiving the plurality of sets of echo data from a plurality of echo transducers, wherein each of the plurality of echo transducers is located at a different angle.
14. The method of claim 12 , wherein the plurality of sets of echo data is related to a cadaveric organ with an inserting device of a catheter inserted into it.
15. The method of claim 12 , wherein segmenting the plurality of echo depth maps comprises:
extracting object features of the object of interest from the plurality of echo depth maps; and
segmenting the plurality of echo depth maps as a function of the object features.
16. The method of claim 12 , wherein determining the depth datum comprises:
training a depth model using depth training data, wherein the depth training data comprises exemplary segmented echo depth maps correlated to exemplary depth datums; and
determining the depth datum using the trained depth model.
17. The method of claim 12 , wherein the pose estimation model comprises a regression model and the pose estimation training data comprises synthetic 3D point clouds generated from a computer aided design (CAD) model of the object of interest.
18. The method of claim 12 , wherein:
the pose datum comprises a 6D pose datum; and
generating the pose datum comprises generating the 6D pose datum related to a second object of interest relative to the object of interest as a function of a rigidity constraint between the object and the second object of interest.
19. The method of claim 18 , wherein:
the object of interest of a catheter comprises a distinct shape; and
an electrode of the catheter comprises the second object of interest.
20. The method of claim 12 , further comprising:
generating, by the at least a processor, a 3D model as a function of the 3D point cloud;
generating, by the at least a processor, a user interface including the 3D model; and
displaying, by the at least a processor, the user interface including the 3D model on a display device.
21. The method of claim 12 , further comprising:
generating, using the at least a processor, an anatomical datum as a function of the pose datum, wherein the anatomical datum comprises a dimension datum of the object of interest.
22. The method of claim 12 , wherein the pose datum comprises a five degree (5D) pose datum.