Paige.AI has been granted a patent for a computer-implemented method that enhances the review of digital pathology data. The method involves receiving and displaying digital pathology images, pairing them with physical tokens, and allowing user commands to modify the displayed images interactively. GlobalData’s report on Paige.AI gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Paige.AI, AI assisted radiology was a key innovation area identified from patents. Paige.AI's grant share as of June 2024 was 25%. Grant share is based on the ratio of number of grants to total number of patents.
Digital pathology image review and modification method
The granted patent US11994665B2 outlines a computer-implemented method and system for reviewing digital pathology data. The method involves receiving a digital pathology image associated with a patient and displaying it on a screen. A key feature of the system is the pairing of the digital image with a physical token, which allows users to interactively select different visualizations of the image. The system processes commands from the user to modify the displayed image based on the selected visualization, enabling various manipulations such as rotation, zoom adjustments, and navigation through multiple images. The method also incorporates sensors to track the position and orientation of the physical token, enhancing the interactivity of the review process.
Additionally, the patent describes the use of a mock microscope that integrates a surface for supporting the physical token, further facilitating the visualization process. The visualizations available include tissue map, tissue hop, and point of focus views. The system is designed to respond dynamically to changes in the token's position or orientation, allowing for real-time updates to the displayed image. The patent also covers a non-transitory machine-readable medium that stores instructions for executing these operations, ensuring that the technology can be implemented in various computing systems for efficient digital pathology data review.
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