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公开(公告)号：US20250049512A1
公开(公告)日：2025-02-13
申请号：US18798322
申请日：2024-08-08
Applicant: LightLab Imaging, Inc.
Inventor： Humphrey Chen , Ajay Gopinath , Gregory Patrick Amis , Avi Motova , Songyuan Tang , Chiedza Chauruka , Chih-Hao Liu , Karl W. Engel
Abstract: The present disclosure provides systems and methods for dynamically visualizing the delivery of a device within a vessel by correlating at least one first extraluminal image with second extraluminal images. The extraluminal images may be correlated based on motion features, without the use of other sensors or timestamps. The first extraluminal image may be a high dose contrast x-ray angiogram (“XA”) and the second extraluminal images may be low dose contrast XAs. The high dose contrast XA may be used to generate a vessel map. The low dose contrast XAs may be taken during the delivery of a device, such as a balloon, stent, probe, or the like. Correlating the high dose XA and low dose XA based on motion features allows for the vessel map to be overlaid on the low dose XA to provide the physician visualization of where the device is within the vessel tree in real time.
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公开(公告)号：US20230018499A1
公开(公告)日：2023-01-19
申请号：US17862991
申请日：2022-07-12
Applicant: LightLab Imaging, Inc.
Inventor： Justin Akira Blaber , Ajay Gopinath , Humphrey Chen , Kyle Edward Savidge , Angela Zhang , Gregory Patrick Amis
Abstract: Aspects of the disclosure relate to systems, methods, and algorithms to train a machine learning model or neural network to classify OCT images. The neural network or machine learning model can receive annotated OCT images indicating which portions of the OCT image are blocked and which are clear as well as a classification of the OCT image as clear or blocked. After training, the neural network can be used to classify one or more new OCT images. A user interface can be provided to output the results of the classification and summarize the analysis of the one or more OCT images.
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