AI Histological Fingerprinting Patent Granted to Siemens Healthineers
Summary
The USPTO has granted patent US12584984B2 to Siemens Healthineers AG for an AI-powered histological fingerprinting system. This patent covers methods for using AI to analyze magnetic resonance imaging data to map tissue microstructure, enhancing diagnostic capabilities.
What changed
The United States Patent and Trademark Office (USPTO) has issued patent US12584984B2 to Siemens Healthineers AG. This patent covers systems and methods for AI-powered histological fingerprinting, which uses machine learning to analyze magnetic resonance imaging (MR) signal data and ground truth tissue microstructure data. The technology aims to generate a dictionary or train a model to map MR signals to histological parameters, including tissue microstructure, and includes a signal-to-signal translation model for improved sensitivity.
This patent grant represents a new technological development in medical imaging and diagnostics. While it does not impose direct compliance obligations on other entities, it signifies innovation in AI applications within healthcare. Companies operating in the medical device and diagnostic imaging sectors, particularly those developing AI-driven solutions, should be aware of this granted patent as it may impact future product development and intellectual property strategies.
Source document (simplified)
AI-powered histological fingerprinting
Grant US12584984B2 Kind: B2 Mar 24, 2026
Assignee
Siemens Healthineers AG
Inventors
Mahmoud Mostapha, Dorin Comaniciu, Mariappan S. Nadar
Abstract
Systems and methods for AI-powered histological fingerprinting in magnetic resonance imaging. MR signal data of an object is acquired using a high sensitivity scanner. Ground truth tissue microstructure data is acquired for the object. A forward model is learned using machine learning. The forward model is used to generate a dictionary or to train a model to map the signals to the histological parameters including the tissue microstructure of a scanner object. A signal-to-signal translation model is also provided to provide signals with improved sensitivity.
CPC Classifications
A61B 5/055 G01R 33/5608
Filing Date
2023-08-03
Application No.
18364498
Claims
8
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