Video model for medical 3d segmentation
AssigneeAlign Technology, Inc.
InventorsNiko Benjamin Huber, Shipra Jain, Qi Ma
Life of this patent
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Abstract
A method for using a video model for medical three-dimensional (3D) segmentation includes dividing 3D medical image data into one or more two-dimensional (2D) images. The method includes generating a temporal sequence of the plurality of 2D images. The method includes processing the temporal sequence of the a plurality of 2D images using one or more models trained to process videos, the one or more models outputting segmentation information of anatomical structures in the plurality of 2D images. The method includes storing the segmentation information in a datastore. Methods for training the video model are also disclosed.
Claims20
A method comprising:
- dividing three-dimensional (3D) medical image data into a plurality of two-dimensional (2D) images;
- generating a temporal sequence of the plurality of 2D images;
- processing the temporal sequence of the plurality of 2D images using one or more models trained to process videos, wherein the one or more models output segmentation information of anatomical structures in the plurality of 2D images;
- and
- storing the segmentation information in a datastore.
A system, comprising:
- one or more processors;
- and
- a memory coupled to the one or more processors, the memory storing computer program instructions that, when executed by the one or more processors, perform a computer-implemented method comprising:
- dividing three-dimensional (3D) medical image data into a plurality of two-dimensional (2D) images;
- generating a temporal sequence of the plurality of 2D images;
- processing the temporal sequence of the plurality of 2D images using one or more models trained to process videos, wherein the one or more models output segmentation information of anatomical structures in the plurality of 2D images;
- and
- storing the segmentation information in a datastore.
A system, comprising:
- a first computing device configured to:
- divide three-dimensional (3D) medical image data into a plurality of two-dimensional (2D) images;
- generate a temporal sequence of the plurality of 2D images;
- and
- process the temporal sequence of the plurality of 2D images using one or more models trained to process videos, wherein the one or more models output segmentation information of anatomical structures in the plurality of 2D images.
Dependencies are inferred from the claim text.