Back to results
US 2024/0185567 A1Published application
System and method for outcome evaluations on human ivf-derived embryos
OwnerKang ZHANGinventor
Life of this patent
Estimating the term…
Abstract
AI-based method and system are provided for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live birth outcome prediction in In vitro fertilization (IVF). The method and system can employ deep learning models based on image data of one or more human embryos, where the image data include a plurality of images of the one or more human embryo at different time points within the first few days after the formation of the one or more embryos.
Claims21
A computer-implemented method comprising the steps of:
- receiving image data of one or more human embryos, the image data including a plurality of images of the one or more human embryo at different time points within the first 6 days after the formation of the one or more embryos;
- determining a viability indicator for the one or more human embryos, wherein the viability indicator represents a likelihood that selection for implantation of the one or more embryos will result in a viable embryo, based on one or more the following:
- determining embryo morphological grading of the one or more embryos using a first neural network based on the image data;
- determining aneuploidy of the one or more embryos using a second deep learning model at least partly based on the image data;
- predicting live-birth occurrence of a transfer of the one or more embryos for implantation using a third deep learning model at least partly based on the image data;
- and
- outputting the viability indicator.
4 more elements
A system, including at least one processor configured to:
- receive image data of one or more human embryos, the image data including a plurality of images of the one or more human embryos with at different time points within the first 6 days after the formation of the one or more embryos;
- apply at least one three-dimensional (3D) artificial neural network to the image data to determine a viability indicator for the one or more human embryos;
- and
- output the viability score;
- wherein the viability indicator represents a likelihood that the one or more embryos will result in at least one viable embryo;
- wherein determining the viability indicator for the one or more human embryos comprises at least one of:
- determining embryo morphological grading of the one or more embryos using a first neural network based on the image data;
- determining aneuploidy of the one or more embryos using a second deep learning model at least partly based on the image data;
- and
- predicting live-birth occurrence of a transfer of the one or more embryos for implantation using a third deep learning model at least partly based on the image data.
7 more elements
-24. (canceled)
Dependencies are inferred from the claim text.