US 12,229,964 B2
Probabilistic segmentation of volumetric images
Matvey D Ezhov, Moscow (RU); Vladimir Leonidovich Aleksandrovskiy, Moscow (RU); Evgeny S Shumilov, Moscow (RU); Maria Golitsyna, Moscow (RU); and Mamat Shamshiev, Moscow (RU)
Filed by Diagnocat Inc., Wilmington, DE (US)
Filed on Dec. 29, 2021, as Appl. No. 17/564,565.
Application 17/564,565 is a continuation in part of application No. 17/215,315, filed on Mar. 29, 2021, granted, now 12,062,170.
Application 17/215,315 is a continuation in part of application No. 16/783,615, filed on Feb. 6, 2020, granted, now 11,443,423.
Application 16/783,615 is a continuation in part of application No. 16/175,067, filed on Oct. 30, 2018, granted, now 10,991,091, issued on Apr. 27, 2021.
Prior Publication US 2022/0122261 A1, Apr. 21, 2022
Int. Cl. G06T 7/00 (2017.01); G06T 3/4007 (2024.01); G06T 7/11 (2017.01); G06F 16/906 (2019.01)
CPC G06T 7/11 (2017.01) [G06T 3/4007 (2013.01); G06F 16/906 (2019.01); G06T 2207/20076 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30036 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method for automated segmentation of volumetric images, said method comprising the steps of:
receiving a coarse volumetric image comprising at least one anatomical structure in terms of voxels;
defining each voxel a distinct anatomical identifier based on a probabilistic distribution for each of the anatomical structure;
applying the defined coarse volumetric image through a coarse model for a coarse output;
combining the coarse output with the coarse volumetric image;
generating a probabilistic segmentation from applying the combined coarse output/image through a fine model; and
converting the probabilistic segmentation to a polygonal mesh for each defined class applying a volume-to-mesh algorithm for at least one of a dental anatomy condition, or treatment.