# AI System for Analyzing Medical Images Using Magnification-Aligned Transformers > This 2025 patent describes an AI system that analyzes medical images, like those from pathology slides, by using a special 'Transformer' model that understands how image details change with magnification. - **Patent:** US 20260080696 - **Original title:** Method and system for analyzing pathological images based on magnification-aligned transformer (mat) - **Owner:** GUANGDONG PROVINCIAL PEOPLE'S HOSPITAL - **Status:** Active - **Times cited:** 0 - **Field:** biotech, medical_devices, ai_ml, software ## What it does This patent details a method for analyzing pathological images, such as those from whole-slide images (WSIs) used in medical diagnosis. First, it identifies and isolates the actual tissue regions within these large images, discarding blank or unusable areas. Then, it breaks down these tissue regions into smaller 'patches.' The core of the invention is a 'Magnification-Aligned Transformer' (MAT) classification network model. This model has two main parts: one that aligns features from images taken at different magnifications (like zooming in or out) and another that uses both global (big picture) and local (detailed) attention mechanisms, combining the strengths of Transformers for overall understanding and Convolutional Neural Networks (CNNs) for fine details. This trained model then predicts a classification for the pathological image, helping doctors diagnose conditions. For example, it could help identify cancerous cells in a tissue sample. ## What it does NOT cover - Analyzing images that are not pathological or medical in nature. - Methods that do not involve breaking down whole-slide images into patches. - AI models that do not use a Transformer architecture. - Systems that do not specifically align features across different image magnifications. - Analysis that relies solely on global features without considering local details. ## The clever bit The clever part is how the system aligns features extracted from images at different magnifications. It uses a self-supervised approach to ensure that the AI understands the same underlying tissue structures whether it's looking at a zoomed-out overview or a highly magnified view, preventing loss of critical detail during analysis. ## Real-world examples 1. AI-assisted pathology slide analysis software 2. Digital pathology platforms 3. Computer-aided diagnosis systems for cancer detection ## Why it matters This patent is significant because it addresses the challenge of analyzing complex medical images, particularly whole-slide pathology images, which are massive and contain crucial diagnostic information at various levels of detail. By developing an AI that can intelligently process these images across different magnifications, it aims to improve the accuracy and efficiency of disease diagnosis, potentially aiding pathologists in identifying subtle abnormalities. ## Frequently asked questions ### What does AI System for Analyzing Medical Images Using Magnification-Aligned Transformers cover? This 2025 patent describes an AI system that analyzes medical images, like those from pathology slides, by using a special 'Transformer' model that understands how image details change with magnification. ### Who owns patent US 20260080696? This patent is owned by GUANGDONG PROVINCIAL PEOPLE'S HOSPITAL. ### When does this patent expire? This patent is expected to expire on November 25, 2045, when the invention enters the public domain. ### What problem does this patent solve? This patent is significant because it addresses the challenge of analyzing complex medical images, particularly whole-slide pathology images, which are massive and contain crucial diagnostic information at various levels of detail. By developing an AI that can intelligently process these images across different magnifications, it aims to improve the accuracy and efficiency of disease diagnosis, potentially aiding pathologists in identifying subtle abnormalities. ### What does this patent NOT cover? Analyzing images that are not pathological or medical in nature. **Full plain-English explainer:** https://patentbrief.org/patent/us/20260080696/method-and-system-for-analyzing-pathological-images-based-on-magnification-align **Original patent:** https://patents.google.com/patent/US20260080696 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How AI Models Understand Language Using 'Attention'](https://patentbrief.org/patent/us/10452978/transformer-attention-mechanism) — This patent describes a neural network architecture, known as a Transformer, that uses a "self-attention" mechanism to process sequences of information, like words in a sentence, by weighing the importance of different parts of the input. - [Using Nuclear Magnetic Resonance to Detect Cancer in Tissue](https://patentbrief.org/patent/us/3789832/mri-magnetic-resonance-imaging) — This 1974 patent describes a method and apparatus using nuclear magnetic resonance (NMR) to measure how quickly certain atomic nuclei in a tissue sample return to their normal energy state, helping to distinguish cancerous from healthy tissue. - [Adapting AI Models to Fit Device Resources](https://patentbrief.org/patent/us/20220383078/data-processing-method-and-related-device) — This patent describes how a computer system can automatically shrink a large artificial intelligence model, specifically a "transformer" type, to fit the available computing power of a phone or other device. - [How AI Uses Question-Guided Attention to Answer Questions About Images](https://patentbrief.org/patent/us/9965705/systems-and-methods-for-attention-based-configurable-convolutional-neural-networks-abc-cnn-for-visual-question-answering) — A method for AI to answer questions about images by dynamically focusing on relevant parts of the picture based on the specific question asked. - [Training AI Models Across Different Computers](https://patentbrief.org/patent/us/12574477/distributed-deep-learning-using-a-distributed-deep-neural-network) — This 2026 patent describes a way to train AI models on one computer, send a version to another computer for further training with private data, and then update the original model with the improvements.