US 11,861,828 B2
Automated estimation of midline shift in brain ct images
Nguyen Nguyen, Columbia, MO (US); Youngjin Yoo, Princeton, NJ (US); Pascal Ceccaldi, New York, NY (US); Eli Gibson, Plainsboro, NJ (US); and Andrei Chekkoury, Erlangen (DE)
Assigned to Siemens Healthcare GmbH, Erlangen (DE)
Filed by Siemens Healthcare GmbH, Erlangen (DE)
Filed on Jun. 10, 2021, as Appl. No. 17/303,932.
Claims priority of provisional application 63/073,075, filed on Sep. 1, 2020.
Prior Publication US 2022/0067929 A1, Mar. 3, 2022
Int. Cl. G06T 7/00 (2017.01)
CPC G06T 7/0012 (2013.01) [G06T 2207/10081 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20101 (2013.01); G06T 2207/30016 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving a 3D medical image of an anatomical object of a patient;
determining an initial location of landmarks on the anatomical object in the 3D medical image using a first machine learning network;
extracting a 2D slice depicting the initial location of the landmarks from the 3D medical image;
refining the initial location of the landmarks in the 2D slice using a second machine learning network;
quantifying a shift of the anatomical object based on the refined location of the landmarks in the 2D slice; and
outputting the quantified shift of the anatomical object.