Hologic had eight patents in artificial intelligence during Q4 2023. Hologic Inc’s patent involves methods and systems that use artificial intelligence to confirm the identification of a target lesion in breast tissue during subsequent imaging sessions. A computing system with a lesion matching engine analyzes initial and current images to determine the likelihood that a target lesion matches a potential lesion, providing a confidence level indicator on a display for healthcare providers to locate lesions in breast tissue more effectively. GlobalData’s report on Hologic gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
Hologic grant share with artificial intelligence as a theme is 37% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Correlating regions of interest (Patent ID: US20230351600A1)
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The patent filed by Hologic Inc. describes methods and systems that utilize artificial intelligence to identify a region of interest in breast tissue by confirming the presence of a target lesion identified during initial imaging in a subsequent imaging session. A lesion matching engine powered by a machine learning classifier algorithm analyzes the potential lesion identified in the current imaging session to determine the likelihood that it corresponds to the target lesion. The system provides a confidence level indicator on a computing device display to assist healthcare providers in locating lesions in breast tissue accurately.
The method involves receiving initial and current images of the breast, identifying potential lesions, and comparing them to determine confidence levels. The system can perform biopsies on potential lesions, record location coordinates, and analyze potential lesions using an artificial intelligence system trained on digital breast tomosynthesis images. The system can display indicators of confidence scores on graphical user interfaces, access and translate location coordinates, and analyze lesions based on various characteristics like density, stiffness, shape, margins, orientation, texture, pattern, size, and depth within the breast. Additionally, the system can be used during screening and biopsy sessions, communicate confidence scores to displays in communication with x-ray systems, and provide visual indicators on x-ray images.
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