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

Claim 10:
11. A system for determining uncertainty in a segmented region of interest comprising:
a memory, wherein the memory stores instructions, a trained machine learning model, and an augmentation module;
a display device; and
a processor communicably coupled to the memory and the display device, wherein, when executing the instructions, the processor is configured to:
receive a medical image including an anatomical region of interest;
feed the medical image to the augmentation module, wherein a plurality of augmentations are applied to the medical image to produce a plurality of augmented images;
map the plurality of augmented images to a plurality of segmentation masks of the anatomical region of interest using the trained machine learning model;
determine pixel-wise variations of segmentation labels across the plurality of segmentation masks to produce an uncertainty map of the anatomical region of interest;
place a caliper at a position within the anatomical region of interest;
determine 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
summing the plurality of uncertainty values to produce the uncertainty of the position of the caliper and

respond to the uncertainty of the position of the caliper exceeding a pre-determined uncertainty threshold by:
automatically displaying the position of the caliper overlaid on the medical image; and
prompting a user to confirm or adjust the position of the caliper.