Patent ID: 11972593
Assignee: GE PRECISION HEALTHCARE LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC A  G

Claim 6:
7. A method comprising:
receiving a medical image including an anatomical region of interest;
applying a plurality of augmentations to the medical image to produce a plurality of augmented images;
feeding each of the plurality of augmented images to a trained machine learning model to produce a plurality of segmentation masks of the anatomical region of interest;
determining a mean segmentation mask of the anatomical region of interest from the plurality of segmentation masks;
determining pixel-wise variation of segmentation labels across the plurality of segmentation masks to produce an uncertainty map of the anatomical region of interest;
placing a caliper at a position within the medical image based on the mean segmentation mask;
determining an uncertainty of the position of the caliper based on the uncertainty map by determining a plurality of uncertainty values in a region proximal to, and including, the position of the caliper, wherein the plurality of uncertainty values are obtained by accessing locations of the uncertainty map corresponding to the region proximal to, and including, the position of the caliper; and
determining the uncertainty of the position of the caliper based on an average of the plurality of uncertainty values.