Paige.AI has been granted a patent for systems and methods to analyze pathology specimen images using artificial intelligence. The technology identifies salient features like biomarkers and cancer sub-types, suppresses non-salient regions, and provides diagnostic value for each pixel. The method aims to improve pathology analysis accuracy. GlobalData’s report on Paige.AI gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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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 January 2024 was 27%. Grant share is based on the ratio of number of grants to total number of patents.
Analyzing pathology specimen images using artificial intelligence
A recently granted patent (Publication Number: US11887304B2) outlines a computer-implemented method and system for analyzing images of pathology specimens using artificial intelligence (AI) technology. The method involves determining a salient region overlay for digitized images of pathology specimens, representing this overlay with super-pixels and scores, suppressing non-salient regions based on diagnostic values, and normalizing the overlay to indicate the presence of salient features in each pixel. Additionally, the method includes converting the overlay into a tissue map, detecting salient features using AI, alerting users when the overlay is available, and resizing it to match the original image size.
The system described in the patent includes at least one memory storing instructions and a processor executing these instructions to perform various operations. These operations involve determining the salient region overlay, suppressing non-salient regions, normalizing the overlay, and representing it through binary and semantic segmentation to indicate the presence and probability of salient features in each pixel. The system also includes features such as developing a pipeline for archiving patient data, converting the overlay into a tissue map, and utilizing machine learning to produce tissue visualizations. Overall, the patent highlights a sophisticated method and system for analyzing pathology specimen images using AI technology, offering a comprehensive approach to identifying and visualizing salient features for diagnostic purposes.
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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.
