US 12,444,127 B2
System and method for reconstruction of 3D volumes from biplanar radiographic images
Eugene Alma Gregerson, North Salt Lake, UT (US)
Assigned to See All AI Inc., Nashua, NH (US)
Filed by See All AI Inc., Nashua, NH (US)
Filed on Dec. 9, 2024, as Appl. No. 18/974,545.
Claims priority of provisional application 63/608,122, filed on Dec. 8, 2023.
Claims priority of provisional application 63/607,956, filed on Dec. 8, 2023.
Prior Publication US 2025/0191279 A1, Jun. 12, 2025
Int. Cl. A61B 6/00 (2024.01); A61B 6/58 (2024.01); A61B 34/20 (2016.01); G06T 7/33 (2017.01); G06T 7/73 (2017.01); G06T 11/00 (2006.01); G06T 15/08 (2011.01); A61B 90/00 (2016.01)
CPC G06T 15/08 (2013.01) [A61B 6/52 (2013.01); A61B 6/5205 (2013.01); A61B 6/582 (2013.01); A61B 34/20 (2016.02); G06T 7/33 (2017.01); G06T 7/73 (2017.01); G06T 11/006 (2013.01); A61B 2034/2065 (2016.02); A61B 2090/367 (2016.02); A61B 2090/376 (2016.02); A61B 2090/3966 (2016.02); G06T 2207/10116 (2013.01); G06T 2207/30204 (2013.01)] 6 Claims
OG exemplary drawing
 
1. A method for constructing a three-dimensional (3D) volume from a set of two or more medical images, the method comprising:
A) acquiring two or more biplanar radiographic images with an X-ray imaging device;
B) calibrating each of the biplanar radiographic images both intrinsically and extrinsically in relation to a common coordinate system wherein the intrinsic calibration includes determining one of lens distortions and focal length of the X-ray imaging device;
C) encoding the calibrated images using a machine learning or deep learning algorithm executing on a processor;
D) back-projecting the encoded images into the common coordinate system based on known relative 3D poses; and
E) decoding the back-projected images to reconstruct the 3D volume.