Alcon had 13 patents in artificial intelligence during Q1 2024. Alcon Inc has filed patents for integrated analysis of MSI and OCT images for diagnosing eye disorders, characterizing vitreous floaters using wavefront elevation maps, determining IOL parameters for cataract surgeries, and providing an alignment guide for toric IOL during surgery. These patents involve the use of machine learning models and advanced imaging techniques to improve the accuracy and efficiency of ophthalmic procedures. GlobalData’s report on Alcon gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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Alcon grant share with artificial intelligence as a theme is 15% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: System for imaging and diagnosis of retinal diseases (Patent ID: US20240099577A1)

The patent filed by Alcon Inc. describes a system and method for diagnosing eye disorders by integrating analysis of Multispectral Imaging (MSI) and Optical Coherence Tomography (OCT) images. The system involves processing MSI and OCT images using separate input machine learning models to create input feature maps, which are then input to an intermediate machine learning model. This intermediate model generates a final feature map that is processed by output machine learning models to estimate representations of eye pathologies. The system includes a single device that captures both OCT and non-OCT images using a shared sensor or an optical component to direct light from the retina to the imaging devices.

The claims of the patent detail the components and functionalities of the system, such as capturing OCT and non-OCT images using shared sensors or optical components, utilizing different imaging modalities like Fundus Autofluorescence (FAF) or multi-spectral imaging, and employing machine learning models to process images for diagnosing retinal pathologies. The method involves capturing OCT images, reconfiguring the imaging device for non-OCT modalities, capturing additional images, and processing them using machine learning models to diagnose retinal pathologies or identify specific features related to the condition. The method also includes transitioning between different light sources, utilizing spectrometers, and employing output machine learning models to obtain accurate diagnoses and stages of retinal pathologies.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.