AI-Powered Medical Imaging Patents 2026 — PatSnap Eureka
AI-Powered Medical Imaging Technology Landscape 2026
Machine learning and deep learning are now applied across the full imaging pipeline—from acquisition and reconstruction through diagnosis and treatment planning. This report synthesizes signals from 50+ patent filings and scientific literature records spanning 2012–2025.
Four Technical Clusters Defining AI Medical Imaging
AI-powered medical imaging integrates ML and deep learning into every stage of the clinical workflow: image acquisition, reconstruction, segmentation, classification, disease detection, clinical decision support, and treatment response prediction. The field spans X-ray, CT, MRI, PET, OCT, and ultrasound modalities, with CNNs and GANs representing the dominant algorithmic frameworks within this dataset.
Four primary technical sub-domains are evident in this dataset: distributed and federated AI model training for privacy-preserving multi-institutional learning; deep learning-based image reconstruction, segmentation, and classification; generative AI and synthetic image generation for data augmentation; and edge and IoT-integrated imaging systems enabling point-of-care deployment.
Publication dates across retrieved records span 2012 to 2025. The 2021–2022 period shows the highest density, with 15+ records covering FDA clearance trends, federated learning architectures, and clinical translation. By November 2021, the FDA had cleared 151 AI algorithms for medical imaging, with 64.2% using clinical validation data.
The most recent filings (2024–2025) signal a shift toward LLM-driven decision support, miniaturized MEMS-integrated hybrid imaging, and deep learning for biologic therapy response prediction. Remidio Innovative Solutions is the single most prolific assignee with 4 filings spanning WO, US, and IN jurisdictions, all focused on federated and distributed AI training architectures.
A Decade of AI Imaging: From Foundational Infrastructure to Generative AI
Records in this dataset span 2012 to 2025, tracing a clear progression from early data infrastructure through algorithmic acceleration and into the current generative AI and edge deployment phase. The 2021–2022 period represents the densest cluster, with 15+ records addressing clinical translation and regulatory engagement.
AI Medical Imaging Patent & Literature Activity by Phase (2012–2025)
The 2021–2022 phase produced the highest record density with 15+ entries, reflecting concurrent FDA clearance milestones, federated learning patent filings, and COVID-19-driven deployment.
↗ Click bars to exploreAI Medical Imaging Patent Filings by Jurisdiction
India (IN) leads by raw filing count with 6 filings, largely from individual inventors and startups; US filings are concentrated among established commercial entities.
↗ Click bars to exploreKey Clinical Application Areas in AI Medical Imaging
The dataset reveals six major clinical application domains where AI imaging is being deployed or researched, ranging from dominant oncology applications to emerging implantable device monitoring. Oncology accounts for the largest share, with breast cancer imaging the single most frequently cited clinical application across at least 8 literature records.
Oncology — Breast, Lung, Brain
Oncology accounts for the largest share of AI imaging applications in this dataset. Breast cancer imaging is the single most frequently cited clinical application, with dedicated coverage across mammography, ultrasound, and MRI in at least 8 literature records. AiXScan’s 2024 US patent addresses lung nodule detection via X-ray tomosynthesis, while the CHAIMELEON project (2022) targets lung, breast, prostate, and colorectal cancers using multimodal MR, CT, and PET/CT data from a pan-European repository.
Oncology ImagingCOVID-19 & Pulmonology Imaging AI
COVID-19 accelerated AI deployment in chest imaging and is represented by at least 6 literature records in this dataset. A 2020 synthesis covered 463 manuscripts on AI for COVID-19 chest X-ray and CT diagnosis. A 2023 paper specifically highlights AI’s role in low-dose imaging optimization for coronavirus disease diagnosis, signaling a transition from pandemic response to durable clinical infrastructure.
Infectious DiseaseOphthalmology — AMD & OCT Diagnostics
OCT-based AI for age-related macular degeneration (AMD) is described as a mature clinical deployment case in this dataset, with cloud-based telemedicine implementation documented in a 2019 literature record. The 2025 Indian patent by Trisha M describes a MEMS-miniaturized hybrid OCT-PAI platform with embedded real-time AI classification, targeting ophthalmic and dermatological point-of-care diagnostics in resource-limited settings.
OphthalmologyNuclear Medicine & Molecular Imaging
AI applications in PET, SPECT, and hybrid PET/CT and PET/MRI imaging are documented in two literature records from 2020 and 2022 in this dataset, covering PET image reconstruction, denoising, dosimetry, and outcome prediction. AI is also applied to quality assurance in IMRT and VMAT radiation therapy, as documented in a 2021 study, and an intelligent imaging layout system trained on 11,205 patients across multiple CT manufacturers automates lung nodule management workflows.
Nuclear MedicineLeading Organizations Filing AI Medical Imaging Patents
Within this dataset, Remidio Innovative Solutions is the single most prolific patent assignee with 4 filings across WO, US, and IN jurisdictions. US filings are concentrated among established commercial entities including Siemens, GE, Microsoft/Nuance, ONC.AI, Merative, and AiXScan, indicating stronger commercialization orientation compared to India-based individual inventor filings.
Top Patent Assignees by Filing Count (AI Medical Imaging Dataset)
↗ Click bars to exploreRemidio Innovative Solutions Pvt. Ltd.
Remidio is the single most prolific patent assignee in this dataset with 4 filings spanning WO (2020), US (2021 and 2024), and IN (2023) jurisdictions. All four patents cover distributed training of systems for medical image analysis using federated learning, where local AI models send model parameters—rather than raw patient data—to a global AI model for retraining. The 2024 US filing extends this architecture to support offline prediction and asynchronous model synchronization for bandwidth-limited clinical environments.
India (IN) — headquarteredSiemens Medical Solutions USA, Inc.
Siemens Medical Solutions USA has 1 filing in this dataset: a 2025 US patent titled “Generative Artificial Intelligence for Decision Making in Medical Imaging,” in which LLM-generated programs call imaging system functions to answer clinical queries through a natural language interface. This filing represents the clearest signal in the dataset of LLMs being embedded directly into imaging system GUIs, marking a paradigm shift from task-specific models toward general-purpose imaging AI assistants.
United StatesMicrosoft Technology Licensing / Nuance
Microsoft Technology Licensing, LLC and Nuance Communications, Inc. jointly account for 2 filings in this dataset: a 2022 US patent and a 2022 WO patent, both titled “Medical Intelligence System and Method,” targeting AI-assisted documentation and image-based content generation during clinical encounters. These filings reflect the two companies’ combined focus on AI workflow automation in radiology and clinical decision support following Microsoft’s acquisition of Nuance.
United StatesGeneral Electric Company
General Electric Company has 1 filing in this dataset: a 2019 WO patent titled “Systems and Methods for Synchronization of Imaging Systems and an Edge Computing System,” which streams imaging data to an edge computing system for concurrent AI processing during scan acquisition. This filing positions GE as an early mover in edge-integrated AI imaging infrastructure, consistent with the broader industry trend of incumbent imaging hardware manufacturers patenting AI software integration.
United StatesFour Forward Vectors Shaping AI Medical Imaging 2024–2025
The most recent filings in this dataset (2024–2025) point to four distinct forward vectors: LLM integration into imaging workflows, deep learning for longitudinal treatment response prediction, miniaturized hybrid multi-modal imaging with on-device AI, and continuous federated edge learning for global scaling.
LLM-Driven Imaging Assistants in Clinical GUIs
Siemens Medical Solutions USA’s 2025 US patent embeds LLMs directly into imaging system graphical user interfaces, allowing clinicians to query imaging systems conversationally. LLM-generated programs orchestrate imaging system functions to answer clinical queries, representing a paradigm shift from task-specific models toward general-purpose imaging AI assistants. IP strategists should track LLM-imaging system integration claims as a new category distinct from traditional image analysis patents.
Longitudinal Imaging for Biologic Therapy Response Prediction
ONC.AI’s 2024 US patent trains AI models to predict lesion volume changes and survival rates from longitudinal imaging data—integrating baseline and follow-up scans with lesion volume dynamics to recommend specific pharmaceutical products. This extends AI imaging beyond diagnosis into therapy selection, pointing toward precision oncology applications. Within this dataset, this filing appears as an isolated signal in a space where patent density appears low relative to clinical need.
Federated Learning vs. Centralized AI Training in Medical Imaging
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| Dimension | Federated / Distributed AI Training | Centralized AI Training |
|---|---|---|
| Core Mechanism | Local AI models extract image parameters; send model parameters to global AI model for retraining — no raw patient data transferred | Raw imaging data aggregated into a central repository; model trained on unified dataset |
| Patient Privacy | Preserved by design — raw data never leaves the imaging site; cryptographically secure protocols demonstrated across 7 US and Indian sites (2021 literature) | Requires de-identification, consent frameworks, and secure data transfer agreements across institutions |
| Patent Density (Dataset) | Most patent-dense cluster — anchored by Remidio Innovative Solutions with 4 filings across WO, US (×2), and IN jurisdictions | No dedicated centralized training patents identified in this dataset; addressed primarily in literature |
| Offline / Bandwidth Support | Remidio 2024 US patent explicitly supports offline prediction and asynchronous model synchronization for bandwidth-limited environments | Requires continuous network connectivity to central training infrastructure |
| Data Scarcity Mitigation | Enables multi-site learning without data sharing, expanding effective training set size | Addressed via synthetic data augmentation — Merative 2021 US patent uses GANs to generate 3D images from 2D inputs and population-level priors |
| Clinical Validation Evidence | Multi-institution encrypted validation across 7 sites demonstrated without data transfer (2021 literature record) | 151 FDA-cleared AI algorithms by November 2021; 64.2% used clinical validation data (2022 literature) |
| Deployment Target | Resource-limited, bandwidth-constrained, and LMIC clinical environments; rural point-of-care | Well-resourced hospital networks with centralized IT infrastructure and data governance |
Frequently Asked Questions: AI-Powered Medical Imaging Patents 2026
Remidio Innovative Solutions Pvt. Ltd. is the single most prolific patent assignee in this dataset with 4 filings spanning WO (2020), US (2021 and 2024), and IN (2023) jurisdictions. All four patents are focused on distributed training of systems for medical image analysis using federated learning architectures.
According to the 2022 literature record on trends in clinical validation and usage of FDA-cleared AI algorithms for medical imaging, 151 AI algorithms had been cleared by the FDA as of November 2021, with 64.2% using clinical validation data.
Oncology accounts for the largest share of AI imaging applications in this dataset. Breast cancer imaging is the single most frequently cited clinical application, with dedicated coverage across mammography, ultrasound, and MRI in at least 8 literature records. Lung and neuro-oncology applications are also extensively represented.
The four primary technical sub-domains are: (1) distributed and federated AI model training for privacy-preserving multi-institutional learning; (2) deep learning-based image reconstruction, segmentation, and classification; (3) generative AI and synthetic image generation for data augmentation; and (4) edge and IoT-integrated imaging systems enabling point-of-care deployment.
The 2024–2025 filings point to four vectors: LLM integration into imaging system GUIs (Siemens Medical Solutions USA, 2025); deep learning for biologic therapy response prediction from longitudinal imaging data (ONC.AI, 2024); MEMS-miniaturized hybrid OCT-PAI systems with embedded AI for point-of-care deployment (2025, IN); and asynchronous federated edge learning supporting offline prediction in bandwidth-limited environments (Remidio, 2024).
India leads by raw filing count with 6 filings, but several are from individual inventors with pending legal status rather than established commercial assignees. Remidio Innovative Solutions, an India-headquartered startup, accounts for multiple IN and international filings. The dataset notes this signals grassroots innovation activity but less institutional R&D concentration compared to US commercial filers such as Siemens, GE, and Microsoft/Nuance.