Machine-learning based iol position determination
AssigneeCarl Zeiss Meditec AG
InventorsHendrik Burwinkel, Holger Matz, Stefan Saur, Christoph Hauger
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Abstract
The invention relates to a computer-assisted method for position determination for an intraocular lens supported by machine learning. The method comprises providing a scan result for an eye. The scan result here represents an image of an anatomical structure of the eye. The method further comprises use of a trained machine learning system for the direct determination of a final location of an intraocular lens to be fitted, wherein digital data of the scan of the eye is used as the input data for the machine learning system.
Claims29
A computer-implemented method for a machine learning-supported determination of position for an intraocular lens, the method including the steps of
- providing a scan result of an eye, the scan result representing an image of an anatomical structure of the eye and
- using a trained machine learning system to directly determine a final location of an intraocular lens to be inserted, digital data of the scan of the eye serving as input data for the machine learning system.
A prediction system for a machine learning-supported determination of position for an intraocular lens, the prediction system comprising:
- a provision module adapted to provide a scan result of an eye, the scan result representing an image of an anatomical structure of the eye, and
- a trained machine learning system adapted to directly determine a final location of an intraocular lens to be inserted, digital data of the scan of the eye serving as input data for the machine learning system.
Dependencies are inferred from the claim text.