Apparatus, method, and system for image-based human embryo cell classification

An apparatus for automated cell classification, comprising a classification module configured to:

• apply a plurality of first classifiers to each of a plurality of images of one or more cells to determine, for each image, a first classification probability associated with each first classifier, wherein:
• each first classifier is associated with a distinct first number of cells, and is configured to determine the first classification probability for the each image based on a plurality of cell features including one or more machine learned cell features;
• and
• the first classification probability indicates a first estimated likelihood that the distinct first number of cells associated with the each first classifier is shown in the each image, the each of the plurality of images thereby having a plurality of the first classification probabilities associated therewith;
• and
• classify each image as showing a second number of cells based on the distinct first number of cells associated with the each first classifier and the plurality of first classification probabilities associated therewith;
• the classification module being implemented in at least one of a memory or a processing device.

A system for automated cell classification, comprising a computing apparatus configured for automated cell classification, the computing apparatus configured to:

• apply a plurality of first classifiers to each of a plurality of images of one or more cells to determine, for each image, a first classification probability associated with each first classifier, wherein:
• each first classifier is associated with a distinct first number of cells, and is configured to determine the first classification probability for the each image based on a plurality of cell features including one or more machine learned cell features;
• and
• the first classification probability indicates a first estimated likelihood that the distinct first number of cells associated with the each first classifier is shown in the each image, the each of the plurality of images thereby having a plurality of the first classification probabilities associated therewith;
• and
• classify each image as showing a second number of cells based on the distinct first number of cells associated with the each first classifier and the plurality of first classification probabilities associated therewith.

A method for image-based outcome determination, comprising:

• applying a classifier to a first time-sequential series of images of one or more cells to determine, for the first time-sequential series of images, a classification probability, wherein:
• the classification probability indicates an estimated likelihood that a first outcome for development of the one or more cells is shown by the first time-sequential series of images;
• and
• the first outcome is included in a plurality of outcomes for cell development associated with the classifier;
• and
• classifying the first time-lapse series of images as showing the first outcome based on the plurality of outcomes associated with the classifier and the classification probability.

An apparatus for image-based outcome determination, comprising a classification module configured to:

• apply a classifier to a first time-sequential series of images of one or more cells to determine, for the first time-sequential series of images, a classification probability, wherein:
• the classification probability indicates an estimated likelihood that a first outcome for development of the one or more cells is shown by the first time-sequential series of images;
• and
• the first outcome is included in a plurality of outcomes for cell development associated with the classifier;
• and
• classify the first time-lapse series of images as showing the first outcome based on the plurality of outcomes associated with the classifier and the classification probability,
• wherein the classification module is implemented in at least one of a memory or a processing device.

A system for image-based outcome determination, comprising:

• an imaging device configured to acquire a first time-lapse series of images of one or more cells and to acquire a plurality of time-lapse series of images;
• an input interface configured to associate the a first time-lapse series of images with an unknown or uncertain outcome each of a plurality of time-lapse series of images with a specified outcome of a plurality of outcomes;
• a computing apparatus configured for image-based outcome determination, the computing apparatus configured to:
• apply a classifier to a first time-sequential series of images of one or more cells to determine, for the first time-sequential series of images, a classification probability, wherein:
• the classification probability indicates an estimated likelihood that a first outcome for development of the one or more cells is shown by the first time-sequential series of images;
• and
• the first outcome is included in a plurality of outcomes for cell development associated with the classifier;
• and
• classify the first time-lapse series of images as showing the first outcome based on the plurality of outcomes associated with the classifier and the classification probability,
• a display device configured to:
• display one or more of the first time-lapse sequential series of images and the plurality of time-lapse series of images;
• and
• present one or more characteristics of the one or more cells in the first time-lapse sequential series of images based on one or more of the following:
• the classification probability, the classifying, and the first outcome;
• and
• present one or more characteristics of one or more cells in the plurality of time-lapse series of images based on the feature information.