AI-based Medical Imaging Market Size & Forecast Report - 2025 to 2030

The global AI-based medical imaging market was accounted at around USD 1.5 billion in 2024 and estimated to register a higher CAGR of over 30% during the forecast period from 2025 to 2030. The market is experiencing rapid expansion, driven by the growing need for accurate diagnostics, early disease detection, and efficient healthcare delivery. Artificial intelligence, particularly deep learning and computer vision, is increasingly integrated into imaging modalities such as CT, MRI, X-ray, and ultrasound to enhance image reconstruction, automate detection, and assist radiologists in reducing interpretation errors. Rising prevalence of chronic conditions like cancer, cardiovascular diseases, and neurological disorders has accelerated the demand for AI-enabled tools that support faster and more precise diagnosis. In addition, regulatory approvals, strategic collaborations between healthcare providers and AI technology firms, and increased investments in healthcare digitization are further fueling market adoption.

Regionally, North America leads the market, supported by advanced healthcare infrastructure, strong funding for AI in healthcare, and early adoption of innovative imaging solutions. Europe is also witnessing significant growth, driven by favorable regulatory frameworks and government initiatives to encourage AI integration in healthcare systems. Meanwhile, Asia-Pacific is emerging as the fastest-growing region due to increasing healthcare expenditures, a large patient pool, and rapid adoption of digital health technologies in countries like China, India, and Japan. With a projected CAGR of 25–30% over the next few years, the AI-based medical imaging market is set to transform diagnostic practices globally, improving patient outcomes while reducing costs and clinical workload.

Market Drivers in AI-based Medical Imaging Market:

The global AI-based medical imaging market is primarily driven by the rising demand for early and accurate diagnosis, the growing prevalence of chronic diseases such as cancer and cardiovascular conditions, and the increasing volume of medical imaging procedures worldwide. AI enables enhanced image analysis, automated reporting, and reduced human error, which significantly improves diagnostic efficiency and patient outcomes. Hospitals and diagnostic centers are adopting AI-powered imaging tools to streamline workflows, optimize radiologist time, and manage the increasing workload caused by the global shortage of radiologists. Furthermore, the integration of AI with PACS (Picture Archiving and Communication Systems) and cloud-based imaging platforms is expanding adoption in both developed and emerging healthcare markets.

Another key driver is technological advancement and regulatory support for AI in healthcare. For example, in Sep 2022, GE HealthCare announced the FDA clearance of its AI-enabled AIR Recon DL for 3D and PROPELLER MRI scans, designed to improve image quality and reduce scan times, marking a significant step in clinical adoption. Such innovations highlight how leading players are focusing on developing AI tools that address real-world clinical challenges, such as speed, accuracy, and accessibility of medical imaging. Combined with rising investments, government initiatives to promote digital health, and growing trust in AI-driven diagnostic support, these factors are expected to accelerate market growth in the coming years.

Market Snapshot:

Market Trends Shaping the AI-based Medical Imaging Market

Integration of Generative AI & Large Language Models (LLMs)

The market is witnessing a strong shift towards the use of generative AI and large language models in medical imaging. These technologies go beyond simple image recognition by combining visual data with patient history, lab results, and clinical notes. This multimodal analysis allows healthcare professionals to gain deeper insights, such as predicting disease progression or assessing treatment effectiveness. For example, LLMs can help generate comprehensive radiology reports by interpreting both images and contextual patient data, thereby reducing reporting time and improving diagnostic accuracy.

Cloud-based & Federated Learning Platforms

Cloud technology is playing a critical role in expanding access to AI-based imaging solutions. Cloud platforms enable hospitals and diagnostic centers to process large volumes of imaging data in real time, without heavy on-premises infrastructure. In parallel, federated learning is emerging as a key trend, where AI models are trained on decentralized datasets across multiple hospitals without actually sharing sensitive patient information. This not only enhances the performance of AI algorithms but also ensures compliance with stringent healthcare data privacy regulations like HIPAA and GDPR.

Workflow Automation & Decision Support

Radiologists worldwide are experiencing a growing workload due to the increasing demand for imaging procedures. AI is addressing this by automating repetitive tasks such as scan prioritization, anomaly detection, and even preliminary reporting. For instance, AI can automatically flag critical findings such as stroke or lung nodules, ensuring that urgent cases are reviewed faster. This trend is making diagnostic workflows more efficient, reducing turnaround times, and supporting physicians in making better-informed clinical decisions.

Regulatory Approvals & Clinical Validation

One of the strongest drivers of adoption is the growing number of regulatory approvals. Agencies like the FDA and EMA are actively clearing AI-based medical imaging tools for clinical use. With approvals comes greater trust among clinicians, who often rely on peer-reviewed validation studies before integrating new technologies into practice. Companies are therefore focusing on publishing clinical evidence that proves their solutions’ accuracy, safety, and reliability. This trend is helping AI move from pilot projects to routine clinical workflows.

Personalized & Precision Medicine

Precision medicine is becoming a cornerstone of modern healthcare, and AI is a critical enabler in this field. By analyzing imaging biomarkers in CT, MRI, or PET scans, AI algorithms can provide personalized insights into disease characteristics, enabling tailored treatment strategies. For example, in oncology, AI can help identify tumor subtypes and predict response to therapies, while in cardiology, it can analyze heart imaging data to recommend patient-specific interventions. This trend aligns with the broader healthcare movement toward individualized care.

AI-based Medical Imaging Market Opportunities:

The AI-based Medical Imaging Market presents significant opportunities driven by the increasing need for early diagnosis, precision medicine, and improved healthcare efficiency. One major opportunity lies in the integration of AI with cloud-based and remote imaging platforms, enabling healthcare providers to analyze imaging data in real time, even across geographically dispersed facilities. This creates scope for tele-radiology expansion, where AI tools can assist in delivering faster and more accurate diagnostic support in regions with limited radiology expertise. Moreover, as global imaging volumes continue to rise, AI solutions that can automate routine tasks, reduce interpretation errors, and optimize workflow will gain strong adoption across hospitals and diagnostic centers, particularly in emerging markets where healthcare infrastructure is rapidly modernizing.

A standout opportunity lies in precision and personalized medicine driven by imaging biomarkers. AI-powered tools that integrate imaging data with genetic and clinical insights enable predictive and tailor-made treatment plans across major specialties like oncology, cardiology, and neurology. In line with this, a recent breakthrough in July 2025 saw Philips receive FDA 510(k) clearance for its SmartSpeed Precise – the industry’s first integrated dual-AI MRI reconstruction software—offering up to 3× faster scanning and 80% sharper images in a single click. This advancement not only highlights growing clinical validation of AI technologies but also opens scalable, upgradeable pathways for healthcare providers to enhance diagnostic precision and operational efficiency across existing MRI systems.

Ai-based Medical Imaging Market Insights:

By Technology: Deep Learning Category Dominated the Ai-based Medical Imaging Market

The global AI-based medical imaging market is bifurcated into technology, modalities, application, end-use, and geography. On the basis of technology, the dominant segment in the market is deep learning. This is because deep learning algorithms excel at analyzing complex medical images, identifying patterns, and detecting anomalies with a high degree of accuracy. Across imaging modalities such as CT, MRI, X-ray, and ultrasound, deep learning enables tasks like tumor detection, organ segmentation, and image reconstruction, which are critical for accurate diagnosis and treatment planning. Its ability to continuously improve with larger datasets and its compatibility with modern imaging equipment has made it the backbone of most AI-powered imaging solutions adopted in hospitals and diagnostic centers worldwide.

Deep learning’s dominance is also reinforced by its wide clinical validation and regulatory approvals. Many FDA-cleared and CE-marked AI tools in radiology, oncology, and cardiology rely primarily on deep learning models due to their proven performance and reliability. Hospitals increasingly prefer deep learning–based solutions because they can integrate seamlessly with PACS and other imaging systems, automate routine tasks, and reduce radiologist workload without compromising diagnostic accuracy. With the rising global adoption of AI in healthcare, especially for early disease detection and precision medicine, deep learning is expected to continue leading the market while other technologies like NLP and classical machine learning grow in supportive or complementary roles.

By Modalities: CT-scan category holds the largest market share of AI-based Medical Imaging Market

On the basis of modalities, the global AI-based medical imaging market is further segmented into CT-scan, MRI, X-rays, ultrasound, and nuclear imaging. The CT (Computed Tomography) scans segment holds the largest market share in 2024 in terms of revenue. CT scans are widely used across hospitals and diagnostic centers due to their ability to produce detailed cross-sectional images of the body quickly, which is critical for emergency care, oncology, and cardiology applications. AI integration enhances CT imaging by improving image reconstruction, reducing noise, and enabling automated detection of abnormalities such as tumors, lung nodules, and vascular diseases. These capabilities not only increase diagnostic accuracy but also significantly reduce the time required for image interpretation, making CT scans the preferred modality for AI adoption in medical imaging.

CT scans’ dominance is further reinforced by their versatility and high clinical demand. With rising incidences of chronic diseases and acute conditions requiring rapid diagnosis, healthcare providers are increasingly deploying AI-powered CT solutions to improve workflow efficiency and patient outcomes. Many FDA-cleared and CE-marked AI tools are focused on CT imaging due to the modality’s high resolution and widespread availability, allowing hospitals to integrate AI seamlessly into existing Picture Archiving and Communication Systems (PACS). As a result, CT scans continue to lead the AI-based medical imaging market, while other modalities like MRI, X-ray, and ultrasound complement the market with specialized applications.

The AI-based medical imaging market research report presents the analysis of each segment from 2020 to 2030 considering 2024 as the base year for the research. The compounded annual growth rate (CAGR) for each respective segment is calculated for the forecast period from 2025 to 2030.

Historical & Forecast Period

• 2020-23 – Historical Year
• 2024 – Base Year
• 2025-2030 – Forecast Period

Market Segmentation:

By Technology:

• Deep Learning
• Natural Language Processing (NLP)
• Others

By Modality:

• CT Scan
• MRI
• X-rays
• Ultrasound
• Nuclear Imaging

By Application:

• Neurology
• Respiratory and Pulmonary
• Cardiology
• Breast Screening
• Orthopedics
• Others

By End-Use:

• Hospitals
• Diagnostic Imaging Centers
• Others

By Region:

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Regional Analysis: North America Leads the AI-based Medical Imaging Market

Geographically, the North America dominated the global AI-based medical imaging market in the benchmark year 2024. This leadership is driven by a combination of factors, including advanced healthcare infrastructure, early adoption of cutting-edge technologies, and robust regulatory support. The U.S. Food and Drug Administration (FDA) has been at the forefront, granting numerous clearances for AI-driven medical imaging devices. As of mid-2025, over 1,200 clinical AI algorithms have been approved, with more than 1,000 of these specific to medical imaging, underscoring the region’s commitment to integrating AI into healthcare. This regulatory environment fosters innovation and encourages investment in AI technologies, further solidifying North America’s position as a global leader in AI-based medical imaging.

North America’s dominance is also supported by a strong focus on precision medicine and increasing imaging volumes due to the prevalence of chronic diseases such as cancer, cardiovascular disorders, and neurological conditions. Continuous collaborations between technology providers, healthcare institutions, and academic research centers are fostering innovation in AI-based imaging solutions. The widespread adoption of AI-driven imaging solutions in the U.S. is further supported by the FDA’s streamlined approval processes, which facilitate the introduction of innovative medical devices to the market. These developments underscore North America’s leadership in the AI-based medical imaging sector, driven by a combination of regulatory support, technological innovation, and widespread adoption.

While Europe and Asia-Pacific are growing rapidly, North America remains the largest market due to its established infrastructure, early technology adoption, and significant clinical validation of AI imaging tools.

AI-based Medical Imaging Market: Competitive Landscape

Some of the prominent market players operating in the global AI-based medical imaging market are GE HealthCare, Microsoft, Digital Diagnostics Inc., TEMPUS, Butterfly Network, Inc., and Advanced Micro Devices, Inc. Companies are exploring markets by expansion, new investment, the introduction of new services, and collaboration as their preferred strategies. Players are exploring new geography through expansion and acquisition to gain a competitive advantage through joint synergy.

Key Companies:

• GE HealthCare
• Microsoft
• Digital Diagnostics Inc.
• TEMPUS
• Butterfly Network, Inc.
• Advanced Micro Devices, Inc.
• HeartFlow, Inc.
• Enlitic, Inc.
• Canon Medical Systems USA, Inc.
• ai, Inc.
• EchoNous, Inc.
• HeartVista Inc.

Key Questions Answered by AI-based Medical Imaging Market Report

• Global AI-based medical imaging market forecasts from 2025-2030
• Regional market forecasts from 2025-2030 covering Asia-Pacific, North America, Europe, Middle East & Africa, and Latin America
• Country-level forecasts from 2025-2030 covering 15 major countries from the regions as mentioned above
• AI-based medical imaging submarket forecasts from 2025-2030 covering the market by technology, modality, application, end-use, and geography
• Various industry models such as SWOT analysis, Value Chain Analysis about the market
• Analysis of the key factors driving and restraining the growth of the global, regional, and country-level AI-based medical imaging markets from 2025-2030
• Competitive Landscape and market positioning of top 10 players operating in the market