Medical image segmentation with uncertainty estimation
AssigneeSiemens Healthcare GmbH
InventorsAthira Jacob, Mehmet Gulsun, Puneet Sharma
Life of this patent
Estimating the term…
Abstract
Systems and methods for generating a segmentation mask of an anatomical structure, along with a measure of uncertainty of the segmentation mask, are provided. In accordance with one or more embodiments, a plurality of candidate segmentation masks of an anatomical structure is generated from an input medical image using one or more trained machine learning networks. A final segmentation mask of the anatomical structure is determined based on the plurality of candidate segmentation masks. A measure of uncertainty associated with the final segmentation mask is determined based on the plurality of candidate segmentation masks. The final segmentation mask and/or the measure of uncertainty are output.
Claims20
A method comprising:
- generating a plurality of candidate segmentation masks of an anatomical structure from an input medical image using one or more trained machine learning networks;
- determining a final segmentation mask of the anatomical structure based on the plurality of candidate segmentation masks;
- and
- determining a measure of uncertainty associated with the final segmentation mask based on the plurality of candidate segmentation masks.
An apparatus, comprising:
- means for generating a plurality of candidate segmentation masks of an anatomical structure from an input medical image using one or more trained machine learning networks;
- means for determining a final segmentation mask of the anatomical structure based on the plurality of candidate segmentation masks;
- and
- means for determining a measure of uncertainty associated with the final segmentation mask based on the plurality of candidate segmentation masks.
A non-transitory computer readable medium storing computer program instructions, the computer program instructions when executed by a processor cause the processor to perform operations comprising:
- generating a plurality of candidate segmentation masks of an anatomical structure from an input medical image using one or more trained machine learning networks;
- determining a final segmentation mask of the anatomical structure based on the plurality of candidate segmentation masks;
- and
- determining a measure of uncertainty associated with the final segmentation mask based on the plurality of candidate segmentation masks.
Dependencies are inferred from the claim text.