Embryo viability evaluation using AI/ML analysis of real-time video
AssigneeEmgenisys, Inc.
InventorsCara Elizabeth Wessels Wells, Russell Killingsworth
Life of this patent
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Abstract
A computer-implemented method for predicting an embryo outcome by processing video image data of the embryo. The method includes receiving image data derived from video of a target embryo taken at substantially real-time frame speed during an embryo observation period of time. The video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time. The movement is represented in the received image data and the received image data is processed using a model generated utilizing machine learning and correlated embryo outcome data.
Claims30
A computer-implemented method for predicting an embryo outcome by processing video image data of an embryo, the method comprising:
- receiving image data derived from video of a target embryo taken at real-time frame speed at least as fast as two frames per second during an embryo observation period of time, wherein said video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time and wherein said recorded morphokinetic movement is represented in the received image data;
- processing the received image data using a model generated utilizing machine learning and correlated embryo outcome data, wherein said machine learning comprises utilization of an artificial neural network;
- and
- predicting a likelihood of successful transfer of the target embryo into a recipient.
A computer-implemented method for predicting an embryo outcome by processing video image data of an embryo, the method comprising:
- obtaining image data derived from video of a target embryo taken at real-time frame speed at least as fast as two frames per second during an embryo observation period of time, wherein said video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time and wherein said recorded morphokinetic movement is represented in the image data;
- and
- processing the image data using a model generated utilizing machine learning and correlated embryo outcome data.
A system comprising:
- one or more processors;
- and
- a computer-readable medium comprising instructions stored therein, which when executed by the one or more processors, cause the one or more processors to:
- predict an embryo outcome by processing video image data of an embryo, said prediction comprising:
- receiving image data derived from video of a target embryo taken at real-time frame speed at least as fast as two frames per second during an embryo observation period of time, wherein said video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time and wherein said recorded morphokinetic movement is represented in the image data;
- and
- processing the image data using a model generated utilizing machine learning and correlated embryo outcome data.
A non-transitory computer-readable storage medium comprising computer-readable instructions, which when executed by a computing system, cause the computing system to:
- predict an embryo outcome by processing video image data of an embryo, said prediction comprising:
- receiving image data derived from video of a target embryo taken at real-time frame speed at least as fast as two frames per second during an embryo observation period of time, wherein said video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time and wherein said recorded morphokinetic movement is represented in the image data;
- and
- processing the image data using a model generated utilizing machine learning and correlated embryo outcome data.
Dependencies are inferred from the claim text.