# 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 to Create Wide-Field Images of Tissue Using OCT Scanners](https://patentbrief.org/patent/us/9677869/autonomous-spaceport-drone-ship-asds) — A method for stitching together multiple high-resolution medical images of uneven tissue samples to create a single, wide-field view for better diagnostic clarity. - [AI Predicts 3D Protein Shapes from Genetic Code](https://patentbrief.org/patent/us/20240412809/protein-structure-prediction-from-amino-acid-sequences-using-self-attention-neur) — This patent describes how a computer uses self-attention neural networks to predict the complex three-dimensional shape of a protein based on its simple amino acid sequence, a process crucial for understanding biology and developing new medicines. - [Computer Model Designs Proteins by Matching Structure to Sequence](https://patentbrief.org/patent/us/12412637/embedding-based-generative-model-for-protein-design) — IBM's 2025 patent describes a computer system that designs new protein sequences by first understanding a target 3D protein shape and then generating a sequence that would fold into that shape. - [How AI Transfers Visual Styles Between Images While Keeping Structure](https://patentbrief.org/patent/us/12282696/method-and-system-for-semantic-appearance-transfer-using-splicing-vit-features) — This patent describes an AI method to generate a new image that combines the structure of one input image with the visual style of another, semantically related image, using a pre-trained Vision Transformer model. - [How Automated Microscopes Use Tags to Focus on Biological Samples](https://patentbrief.org/patent/us/12222345/vertical-integration-at-starbase) — A system for automatically focusing and imaging biological samples on a substrate by using special reference marks called tags to guide the microscope's lens.