Global Artificial Intelligence in Medical Imaging Market Growth (Status and Outlook) 2026-2032
Description
The global Artificial Intelligence in Medical Imaging market size is predicted to grow from US$ 1467 million in 2025 to US$ 7024 million in 2032; it is expected to grow at a CAGR of 25.9% from 2026 to 2032.
Artificial Intelligence in Medical Imaging refers to software and algorithmic systems that apply machine learning and deep learning to the end-to-end medical imaging workflow, enabling automated detection, segmentation, quantification, risk stratification, and clinical decision support across CT, MRI, X-ray, ultrasound, PET, and multimodal imaging. These solutions typically deliver results as visual overlays, structured measurements, and report suggestions, and are deployed as standalone applications, embedded functions within imaging devices, or integrated modules within PACS, RIS, and HIS environments via on-premise, cloud, or hybrid architectures to support a closed loop from image quality control and triage to longitudinal follow-up assessment.
In practice, the value proposition centers on improving reading efficiency and consistency, reducing missed findings and variability, and providing reproducible quantitative biomarkers for screening, diagnosis, treatment response evaluation, and follow-up management. Adoption has been strongest in high-volume and time-sensitive domains such as oncology, stroke and neuroimaging, cardiovascular, chest imaging, and musculoskeletal applications, with market demand increasingly shifting from single-task algorithms toward scalable department-level and enterprise platform capabilities.
Opportunities and Key Growth Drivers
Rising imaging volumes and persistent radiology capacity constraints are making productivity and quality improvement a structural priority, accelerating AI’s transition from research tooling to clinical production software. In parallel, regulatory momentum remains strong: the number of AI-enabled medical devices authorized for marketing has grown rapidly, with imaging-related tools representing a dominant share—reinforcing confidence in scalable commercialization.
U.S. Food and Drug Administration
Market Challenges and Risks
Commercial scale-up is still constrained by multi-site generalization, real-world performance validation, workflow integration complexity, and data security and privacy compliance. Clinical stakeholders are highly sensitive to false positives, false negatives, explainability, and accountability; solutions that add operational burden or create inconsistent outcomes can face adoption resistance. Heterogeneous hospital IT environments also increase integration and lifecycle support costs, potentially elongating procurement and payback cycles.
Downstream Demand Trends
Demand is shifting from single-disease point solutions to multimodal, multi-task platforms prioritized around workflow-native capabilities such as triage and prioritization, acute critical finding alerts, quantitative follow-up, and structured reporting—alongside deeper integration with PACS and hospital data platforms. As monetization evolves from pilots toward subscription, per-study pricing, and enterprise licensing, large hospitals and IDNs increasingly favor extensible platform vendors with application marketplaces and continuous upgrade roadmaps.
LPI (LP Information)' newest research report, the “Artificial Intelligence in Medical Imaging Industry Forecast” looks at past sales and reviews total world Artificial Intelligence in Medical Imaging sales in 2025, providing a comprehensive analysis by region and market sector of projected Artificial Intelligence in Medical Imaging sales for 2026 through 2032. With Artificial Intelligence in Medical Imaging sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Artificial Intelligence in Medical Imaging industry.
This Insight Report provides a comprehensive analysis of the global Artificial Intelligence in Medical Imaging landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Artificial Intelligence in Medical Imaging portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Artificial Intelligence in Medical Imaging market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Artificial Intelligence in Medical Imaging and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Artificial Intelligence in Medical Imaging.
This report presents a comprehensive overview, market shares, and growth opportunities of Artificial Intelligence in Medical Imaging market by product type, application, key players and key regions and countries.
Segmentation by Type:
Standalone Software
PACS Integrated Module
Imaging Device Embedded
Others
Segmentation by Imaging Modality:
Computed Tomography
Magnetic Resonance Imaging
Ultrasound Imaging
Others
Segmentation by Ai Technology Stack:
Data and Labeling Layer
Model Training and Validation Layer
Inference and Serving Layer
Segmentation by Workflow Stage:
Triage and Prioritization
Detection and Diagnosis Support
Quantification and Measurement
Segmentation by Application:
Oncology Imaging
Cardiovascular Imaging
Neurology Imaging
Others
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Aidoc
Viz.ai
RapidAI
HeartFlow
Lunit
Qure.ai
Gleamer
ScreenPoint Medical
Subtle Medical
Riverain Technologies
Infervision
Shukun
United Imaging Intelligence
Deepwise
Keya Medical
Airdoc
Huiying Medical
YITU Technology
Please note: The report will take approximately 2 business days to prepare and deliver.
Artificial Intelligence in Medical Imaging refers to software and algorithmic systems that apply machine learning and deep learning to the end-to-end medical imaging workflow, enabling automated detection, segmentation, quantification, risk stratification, and clinical decision support across CT, MRI, X-ray, ultrasound, PET, and multimodal imaging. These solutions typically deliver results as visual overlays, structured measurements, and report suggestions, and are deployed as standalone applications, embedded functions within imaging devices, or integrated modules within PACS, RIS, and HIS environments via on-premise, cloud, or hybrid architectures to support a closed loop from image quality control and triage to longitudinal follow-up assessment.
In practice, the value proposition centers on improving reading efficiency and consistency, reducing missed findings and variability, and providing reproducible quantitative biomarkers for screening, diagnosis, treatment response evaluation, and follow-up management. Adoption has been strongest in high-volume and time-sensitive domains such as oncology, stroke and neuroimaging, cardiovascular, chest imaging, and musculoskeletal applications, with market demand increasingly shifting from single-task algorithms toward scalable department-level and enterprise platform capabilities.
Opportunities and Key Growth Drivers
Rising imaging volumes and persistent radiology capacity constraints are making productivity and quality improvement a structural priority, accelerating AI’s transition from research tooling to clinical production software. In parallel, regulatory momentum remains strong: the number of AI-enabled medical devices authorized for marketing has grown rapidly, with imaging-related tools representing a dominant share—reinforcing confidence in scalable commercialization.
U.S. Food and Drug Administration
Market Challenges and Risks
Commercial scale-up is still constrained by multi-site generalization, real-world performance validation, workflow integration complexity, and data security and privacy compliance. Clinical stakeholders are highly sensitive to false positives, false negatives, explainability, and accountability; solutions that add operational burden or create inconsistent outcomes can face adoption resistance. Heterogeneous hospital IT environments also increase integration and lifecycle support costs, potentially elongating procurement and payback cycles.
Downstream Demand Trends
Demand is shifting from single-disease point solutions to multimodal, multi-task platforms prioritized around workflow-native capabilities such as triage and prioritization, acute critical finding alerts, quantitative follow-up, and structured reporting—alongside deeper integration with PACS and hospital data platforms. As monetization evolves from pilots toward subscription, per-study pricing, and enterprise licensing, large hospitals and IDNs increasingly favor extensible platform vendors with application marketplaces and continuous upgrade roadmaps.
LPI (LP Information)' newest research report, the “Artificial Intelligence in Medical Imaging Industry Forecast” looks at past sales and reviews total world Artificial Intelligence in Medical Imaging sales in 2025, providing a comprehensive analysis by region and market sector of projected Artificial Intelligence in Medical Imaging sales for 2026 through 2032. With Artificial Intelligence in Medical Imaging sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Artificial Intelligence in Medical Imaging industry.
This Insight Report provides a comprehensive analysis of the global Artificial Intelligence in Medical Imaging landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Artificial Intelligence in Medical Imaging portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Artificial Intelligence in Medical Imaging market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Artificial Intelligence in Medical Imaging and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Artificial Intelligence in Medical Imaging.
This report presents a comprehensive overview, market shares, and growth opportunities of Artificial Intelligence in Medical Imaging market by product type, application, key players and key regions and countries.
Segmentation by Type:
Standalone Software
PACS Integrated Module
Imaging Device Embedded
Others
Segmentation by Imaging Modality:
Computed Tomography
Magnetic Resonance Imaging
Ultrasound Imaging
Others
Segmentation by Ai Technology Stack:
Data and Labeling Layer
Model Training and Validation Layer
Inference and Serving Layer
Segmentation by Workflow Stage:
Triage and Prioritization
Detection and Diagnosis Support
Quantification and Measurement
Segmentation by Application:
Oncology Imaging
Cardiovascular Imaging
Neurology Imaging
Others
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Aidoc
Viz.ai
RapidAI
HeartFlow
Lunit
Qure.ai
Gleamer
ScreenPoint Medical
Subtle Medical
Riverain Technologies
Infervision
Shukun
United Imaging Intelligence
Deepwise
Keya Medical
Airdoc
Huiying Medical
YITU Technology
Please note: The report will take approximately 2 business days to prepare and deliver.
Table of Contents
134 Pages
- *This is a tentative TOC and the final deliverable is subject to change.*
- 1 Scope of the Report
- 2 Executive Summary
- 3 Artificial Intelligence in Medical Imaging Market Size by Player
- 4 Artificial Intelligence in Medical Imaging by Region
- 5 Americas
- 6 APAC
- 7 Europe
- 8 Middle East & Africa
- 9 Market Drivers, Challenges and Trends
- 10 Global Artificial Intelligence in Medical Imaging Market Forecast
- 11 Key Players Analysis
- 12 Research Findings and Conclusion
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