The generative artificial intelligence (AI) in medical imaging market size is expected to see exponential growth in the next few years. It will grow to $7.96 billion in 2030 at a compound annual growth rate (CAGR) of 33.5%. The growth in the forecast period can be attributed to AI assisted diagnostics adoption, regulatory approval of AI imaging tools, integration with clinical workflows, demand for early disease detection, expansion of precision medicine. Major trends in the forecast period include AI generated medical image synthesis, image enhancement and reconstruction, synthetic data for model training, AI based diagnostic support, automated image quality optimization.
The rising prevalence of chronic diseases is expected to drive the growth of generative artificial intelligence (AI) in the medical imaging market in the coming years. Chronic diseases are long-term health conditions that persist over extended periods, often lasting throughout an individual’s lifetime. The growing prevalence of chronic diseases is attributed to factors such as unhealthy lifestyle habits, including poor diet, lack of physical activity, and exposure to environmental risks. Generative AI in medical imaging supports the management of chronic diseases by enabling earlier detection, enhancing diagnostic precision, and personalizing treatment strategies through advanced analysis and synthesis of complex imaging data. For example, in April 2024, according to Allergy UK, a UK-based national charity, more than 21 million people in the UK were affected by allergies, which became the most frequently reported chronic health condition in 2022, and forecasts suggest that by 2026, half of Europe’s population will experience at least one allergy. Therefore, the increasing prevalence of chronic diseases is fueling the growth of generative artificial intelligence (AI) in the medical imaging market.
Major companies in the generative artificial intelligence (AI) in medical imaging market are focusing on developing AI tools through collaborations to improve diagnostic accuracy, streamline workflows, and accelerate research and development. These generative AI tools leverage advanced algorithms, including deep learning and generative models, to create, enhance, or interpret medical images. For example, in February 2024, HOPPR, a US-based AI imaging model developer, introduced a groundbreaking foundation model named Grace, created in partnership with Amazon Web Services (AWS), a US-based cloud computing company. Grace is designed to advance medical imaging by expediting development, analyzing a broad spectrum of grayscale shades, and supporting multi-modal learning through an accessible application programming interface (API). This API facilitates integration into various applications, potentially transforming radiology workflows and enhancing patient outcomes. Grace's advanced insights into medical imaging are expected to aid clinicians in making more informed decisions, leading to earlier interventions and improved treatment outcomes.
In July 2024, GE HealthCare Technologies Inc., a US-based medical technology company, announced its acquisition of Intelligent Ultrasound Group plc for $51 million. This strategic acquisition is intended to strengthen GE's position in the generative artificial intelligence (AI) sector within the medical imaging market. By integrating Intelligent Ultrasound's advanced AI capabilities into its ultrasound technologies, GE aims to enhance diagnostic accuracy and streamline workflows in medical imaging. Intelligent Ultrasound Group plc, based in the UK, specializes in developing AI-powered ultrasound imaging solutions, making it a valuable addition to GE's portfolio in improving healthcare outcomes.
Major companies operating in the generative artificial intelligence (AI) in medical imaging market are Google LLC, Siemens AG, NVIDIA Corporation, Philips Healthcare, GE Healthcare, VSP Global, HOPPR.AI, Successive Technologies Inc., Canon Medical Systems Corporation, Aidoc Inc., Viz.AI Inc., Qure.AI Technologies Pvt. Ltd., Yellow.ai, XenonStack Inc., Arterys Inc., Quantib B.V., NiramAI Health Analytix Pvt Ltd., Kheiron Medical Technologies Ltd., QSS Technosoft Inc., Subtle Medical Inc., Enlitic Inc.
North America was the largest region in the generative artificial intelligence (AI) in medical imaging market in 2025. The regions covered in the generative artificial intelligence (AI) in medical imaging market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the generative artificial intelligence (AI) in medical imaging market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have influenced the generative artificial intelligence in medical imaging market by increasing costs of imaging hardware, processors, and data center infrastructure required for AI workloads. These impacts are more pronounced in hospital and diagnostic center deployments across north america, europe, and parts of asia pacific. Higher equipment costs have delayed some technology upgrades. At the same time, tariffs are encouraging local manufacturing, cloud based imaging platforms, and cost optimized AI solutions, supporting sustainable long term adoption.
The generative artificial intelligence (AI) in medical imaging market research report is one of a series of new reports that provides generative artificial intelligence (AI) in medical imaging market statistics, including generative artificial intelligence (AI) in medical imaging industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in medical imaging market share, detailed generative artificial intelligence (AI) in medical imaging market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in medical imaging industry. This generative artificial intelligence (AI) in medical imaging market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Generative artificial intelligence (AI) in medical imaging involves employing AI, particularly deep learning algorithms, to generate, enhance, or simulate medical images. Techniques such as generative adversarial networks (GANs) and variational autoencoders (VAEs) enable these AI models to create new data that resembles real-world medical images and to improve the quality of existing imaging data. The main goal of generative AI in this field is to enhance the accuracy, efficiency, and functionality of imaging technologies used in healthcare.
The key types of generative AI in medical imaging include generative adversarial networks (GANs), variational autoencoders (VAEs), and other methods. GANs consist of two neural networks a generator and a discriminator that work against each other to produce realistic synthetic data through an adversarial process. These models are applied to various imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), X-ray, and ultrasound. Their applications include diagnosis, image reconstruction, enhancement, and monitoring disease progression. This technology is utilized by a broad range of users, including hospitals, diagnostic centers, research institutes, and more.
The generative artificial intelligence (AI) in medical imaging market consists of revenues earned by entities by providing services such as image synthesis and enhancement, image reconstruction, disease detection and diagnosis, predictive modeling, and training and education. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative AI in medical imaging market also includes sales of products including synthetic data generators, AI-powered diagnostic assistants, data augmentation platforms, and anomaly detection systems. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
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Table of Contents
Executive Summary
Generative Artificial Intelligence (AI) In Medical Imaging Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses generative artificial intelligence (AI) in medical imaging market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for generative artificial intelligence (AI) in medical imaging? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The generative artificial intelligence (AI) in medical imaging market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Report Scope
Markets Covered:
1) By Type: Generative Adversarial Networks (GANs); Variational Autoencoders (VAEs); Other Types2) By Imaging Modality; Magnetic Resonance Imaging (MRI); Computed Tomography (CT); X-Ray; Ultrasound
3) By Application: Diagnosis; Image Reconstruction; Image Enhancement; Disease Progression Monitoring; Other Applications
4) By End-User: Hospitals; Diagnostic Centers; Research Institutes; Other End-Users
Subsegments:
1) By Generative Adversarial Networks (GANs): Image Synthesis And Reconstruction; Data Augmentation For Training Models; Image Super-Resolution; Denoising And Artifact Removal In Medical Images2) By Variational Autoencoders (VAEs): Anomaly Detection In Medical Imaging; Latent Space Representation For Medical Image Analysis; Data Compression And Reconstruction; Multimodal Medical Image Synthesis
3) By Other Types: Deep Convolutional Networks For Imaging; Transformer Networks In Medical Imaging; Hybrid Models; Reinforcement Learning In Image Diagnostics
Companies Mentioned: Google LLC; Siemens AG; NVIDIA Corporation; Philips Healthcare; GE Healthcare; VSP Global; HOPPR.AI; Successive Technologies Inc.; Canon Medical Systems Corporation; Aidoc Inc.; Viz.AI Inc.; Qure.AI Technologies Pvt. Ltd.; Yellow.ai; XenonStack Inc.; Arterys Inc.; Quantib B.V.; NiramAI Health Analytix Pvt Ltd.; Kheiron Medical Technologies Ltd.; QSS Technosoft Inc.; Subtle Medical Inc.; Enlitic Inc
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this Generative AI in Medical Imaging market report include:- Google LLC
- Siemens AG
- NVIDIA Corporation
- Philips Healthcare
- GE Healthcare
- VSP Global
- HOPPR.AI
- Successive Technologies Inc.
- Canon Medical Systems Corporation
- Aidoc Inc.
- Viz.AI Inc.
- Qure.AI Technologies Pvt. Ltd.
- Yellow.ai
- XenonStack Inc.
- Arterys Inc.
- Quantib B.V.
- NiramAI Health Analytix Pvt Ltd.
- Kheiron Medical Technologies Ltd.
- QSS Technosoft Inc.
- Subtle Medical Inc.
- Enlitic Inc
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | February 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 2.5 Billion |
| Forecasted Market Value ( USD | $ 7.96 Billion |
| Compound Annual Growth Rate | 33.5% |
| Regions Covered | Global |
| No. of Companies Mentioned | 22 |


