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AI In Medical Imaging Market Revenue Outlook: What CAGR Is Expected Through 2030?
The AI in medical imaging market size has observed substantial growth over recent years. Its valuation is anticipated to increase from $3.79 billion in 2025 to $5.29 billion in 2026, achieving a compound annual growth rate (CAGR) of 39.5%. The expansion witnessed in the past can be ascribed to a rise in medical imaging procedures, the imperative for improved diagnostic accuracy, the development of radiology departments, the digitalization of imaging systems, and heightened healthcare spending.
The AI in medical imaging market is projected to experience substantial expansion in the coming years. This market is forecast to reach $20.28 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 39.9%. Factors driving this growth during the projection period include the wider availability of AI-powered radiology tools, a scarcity of radiologists, the need for quicker diagnostic processes, the uptake of cloud-based imaging solutions, and the increasing prevalence of oncology and cardiology imaging. Key trends anticipated within this forecast timeframe encompass AI-assisted interpretation of images, imaging analysis powered by deep learning, streamlined radiology workflows through automation, real-time support for imaging decisions, and sophisticated image reconstruction methods.
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AI In Medical Imaging Market Growth Factors Supporting Long-Term Expansion
The increasing prevalence of chronic diseases is anticipated to drive the expansion of the AI in medical imaging market in the future. Chronic conditions are defined as persistent health issues that typically last for three months or longer. The application of AI in medical imaging for chronic ailments allows for better diagnostics, prompt interventions, and customized treatment strategies through the use of advanced image analysis algorithms, thereby enabling early identification, accurate assessment, and optimized care of chronic conditions to enhance patient outcomes. As an illustration, in September 2023, the World Health Organization (WHO), a Switzerland-based intergovernmental entity, reported that 41 million deaths worldwide occur annually, with 74% of all fatalities being attributed to chronic diseases. This statistic includes 17.9 million deaths from cardiovascular diseases, 9.3 million from cancer, 4.1 million from chronic respiratory diseases, and 2.0 million from diabetes. Therefore, the rising incidence of chronic diseases is a key factor propelling the growth of the AI in medical imaging market.
AI In Medical Imaging Market Segmentation And Category Breakdown
The AI in medical imaging market covered in this report is segmented –
1) By Technology: Deep Learning, Natural Language Processing (NLP)
2) By Solution: Software Tools, Services
3) By Modality: Computed Tomography (CT) Scan, Magnetic Resonance Imaging (MRI), X-Rays, Ultrasound, Nuclear Imaging
4) By Application: Digital Pathology, Oncology, Cardiovascular, Neurology, Lung (Respiratory System), Breast (Mammography), Liver (GI), Oral Diagnostics, Other Applications
5) By End-Use: Hospitals, Diagnostic Imaging Centers, Other End-Users
Subsegments:
1) By Deep Learning: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Transfer Learning
2) By Natural Language Processing (NLP): Speech Recognition, Text Analytics, Information Extraction, Clinical Decision Support Systems
AI In Medical Imaging Market Trends Reshaping Industry Growth
Leading companies in the AI in medical imaging market are prioritizing the development of advanced solutions, such as cloud-native radiology operating systems, to improve diagnostic accuracy and workflow efficiency. A cloud-native radiology operating system unifies imaging data, clinical workflows, and AI tools into a singular platform, enabling quicker and more precise diagnoses. For example, in February 2025, DeepHealth, a US-based company, released new AI-powered radiology informatics and population screening solutions featuring its DeepHealth OS system. This launch introduced Diagnostic Suite, which redefines traditional imaging systems with a unified AI-powered workspace that integrates patient data, reporting, and visualization tools for radiologists. Additionally, it included SmartMammo, an end-to-end diagnostic SaaS solution for mammography that boosts cancer detection rates and enhances workflow integration. The suite supports AI-driven screening for lung, prostate, and brain health, facilitating faster diagnostic interpretation and greater clinical confidence. These innovations highlight DeepHealth’s efforts to enhance operational efficiency and advance precision care across radiology practices.
AI In Medical Imaging Market Competitive Analysis Of Major Industry Participants
Major companies operating in the AI in medical imaging market are Siemens Healthineers AG; GE HealthCare Technologies Inc.; Koninklijke Philips NV; Lunit Inc.; DeepMind; Viz.AI Inc.; Aidoc; AZmed; Digital Diagnostics Inc.; Butterfly Network Inc.; Cleerly; Behold.ai; Enlitic; Nano-X Imaging Ltd.; Arterys; Caption Health; EchoNous Inc.; Gleamer; CellmatiQ GmbH; Mediwhale
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AI In Medical Imaging Market Regional Distribution: Which Areas Drive Market Expansion?
North America was the largest region in the AI in medical imaging market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the AI in medical imaging market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
