Neural network processing of oct data to generate predictions of geographic-atrophy growth rates
AssigneeGenentech, Inc.
InventorsQi Yang, Simon S. Gao
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Abstract
Embodiments disclosed herein generally relate to predicting geographic-atrophy lesion growth and/or geographic atrophy lesion size in an eye. The predictions can be generated by processing a data object using a neural network. The data object may include a three-dimensional data object representing a depiction of at least part of the eye or a multi-channel data object representing one or more depictions of at least part of the eye. The neural network can include a convolutional multi-task neural network that is trained to learn features that are predictive of both lesion-growth and lesion-size outputs.
Claims23
A method comprising:
- accessing a three-dimensional data object that corresponds to at least a partial depiction of an eye of a subject;
- generating, by a trained machine-learning model and based on the three-dimensional data object, a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of the geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye;
- and
- outputting at least one of the first prediction and the second prediction.
A method comprising:
- receiving input data that includes or identifies a three-dimensional data object that corresponds to at least a partial depiction of an eye of a subject;
- receiving a request communication that corresponds to a request to generate a predicted subsequent geographic-atrophy characteristic of the eye of the subject, the request communication including the input data;
- generating, by a trained machine-learning model and based on the three-dimensional data object, a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of the geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye;
- and
- outputting at least one of the first prediction and the second prediction.
Use of a geographic-atrophy prediction in a treatment of a subject, wherein the geographic-atrophy prediction is provided by a computing device implementing a computational model based on subject data to provide the geographic-atrophy prediction, the computational model including a machine-learning model configured to process a three-dimensional data object corresponding to at least a partial depiction of an eye of the subject, wherein the machine-learning model was trained to generate a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of the geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye.
A method comprising:
- accessing a data object that includes at least three data channels, each of the at least three data channels comprising a two-dimensional image corresponding to at least a partial depiction of an eye of a subject;
- generating, by a trained machine-learning model and based on the data object, a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of the geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye;
- and
- outputting at least one of the first prediction and the second prediction.
A system comprising:
- one or more data processors;
- and
- a non-transitory computer readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to:
- access a three-dimensional data object that corresponds to at least a partial depiction of an eye of a subject;
- generate, by a trained machine-learning model and based on the three-dimensional data object, a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of the geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye;
- and
- output at least one of the first prediction and the second prediction.
A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to:
- access a three-dimensional data object that corresponds to at least a partial depiction of an eye of a subject;
- generate, by a trained machine-learning model and based on the three-dimensional data object, a first prediction of a current size of a geographic-atrophy lesion in the eye and a second prediction of a subsequent growth of a geographic-atrophy lesion in the eye or a subsequent size of the geographic-atrophy lesion in the eye;
- and
- output at least one of the first prediction and the second prediction.
Dependencies are inferred from the claim text.