Alcon, Inc.

Sinchan Bhattacharya

Ramesh Sarangapani

Bryan Stanfill

Hyo Won Choi

A system and method for augmenting an original OCT (optical coherence tomography) image includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The system includes one or more learning modules selectively executable by the controller. The learning modules are trained by a training network with a training dataset having a plurality of training ultrasound bio-microscopy images and respective training OCT images. Execution of the instructions by the processor causes the controller to obtain the original OCT image, captured through an OCT device. The controller is configured to generate an augmented OCT image based in part on the original OCT image, by executing the (trained) learning modules. The augmented OCT image at least partially extends a peripheral portion of the original OCT image.

Augmentation of optical coherence tomography image of eye based on learning modules

A method and system for selecting an intraocular lens, with a controller having a processor and tangible, non-transitory memory. A plurality of machine learning models is selectively executable by the controller. The controller is configured to receive at least one pre-operative image of the eye and extract, via a first input machine learning model, a first set of data. The controller is configured to receive multiple biometric parameters of the eye and extract, via a second input machine learning model, a second set of data. The first set of data and the second set of data are combined to produce a mixed set of data. The controller is configured to generate, via an output machine learning model, at least one output factor based on the mixed set of data. An intraocular lens is selected based in part on the at least one output factor.

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Denton, TX, United States of America

Sinchan Bhattacharya