US 11,989,851 B2
Deformable image registration using deep learning
Virgil Matthew Willcut, Kirkwood, MO (US)
Assigned to Elekta, Inc., Atlanta, GA (US)
Filed by Elekta, Inc., Atlanta, GA (US)
Filed on May 18, 2021, as Appl. No. 17/303,007.
Claims priority of provisional application 63/199,947, filed on Feb. 4, 2021.
Prior Publication US 2022/0245757 A1, Aug. 4, 2022
Int. Cl. G06T 3/00 (2006.01); G06N 20/00 (2019.01); G06T 3/14 (2024.01); G06T 7/00 (2017.01)
CPC G06T 3/14 (2024.01) [G06N 20/00 (2019.01); G06T 7/0012 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30016 (2013.01)] 25 Claims
OG exemplary drawing
 
1. A method for generating a biomechanically accurate deformation vector field (DVF) for input images, the method comprising:
receiving first and second images depicting an anatomy of a subject;
applying a trained machine learning model to a first data set associated with the first image, the first data set excluding a first contour associated with the first image, and a second data set associated with the second image to estimate a biomechanically accurate DVF representing a mapping of pixels or voxels from the first image to the second image without processing the first contour of the first image, the machine learning model trained to establish a relationship between a plurality of pairs of data sets associated with images of a patient anatomy and respective biomechanically accurate DVF representations of pixel or voxel mapping between the plurality of pairs of data sets; and
applying the estimated biomechanically accurate DVF to deform a dose from a previous treatment session.