US 12,406,363 B2
System and method for automatically estimating knee cartilage thickness for femoral, tibial, patellar, and meniscal cartilages
Veerasravanthi Mudiyam, Kurnool (IN); Deepthi Sundaran, Bangalore (IN); Jignesh Dholakia, Bangalore (IN); and Maggie Fung, Jersey City, NJ (US)
Assigned to GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed by GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed on Mar. 7, 2023, as Appl. No. 18/118,250.
Prior Publication US 2024/0303805 A1, Sep. 12, 2024
Int. Cl. G06T 7/00 (2017.01); A61B 5/00 (2006.01)
CPC G06T 7/0012 (2013.01) [A61B 5/4514 (2013.01); G06T 2207/30008 (2013.01)] 21 Claims
OG exemplary drawing
 
19. A non-transitory computer-readable medium, the computer-readable medium comprising processor-executable code that when executed by a processor, causes the processor to:
pre-process a segmented image of region of interests (ROIs) of a knee of a subject to separate the ROIs into individual ROI volumes, wherein the ROI volumes comprise at least one cartilage region;
perform surface separation between a respective subchondral surface and a respective articular surface for each ROI volume to extract a respective separate subchondral surface and a respective separate articular surface for each ROI volume; and
estimate cartilage thickness values for the at least one cartilage region utilizing a nearest neighbor algorithm based on the respective separate subchondral surface and the respective separate articular surface for each ROI volume, wherein pre-processing the segmented image, performing surface separation, and estimating cartilage thickness values all occur without utilizing deep-learning.