Global AI Image-assisted Diagnosis Software Market Growth (Status and Outlook) 2026-2032

The global AI Image-assisted Diagnosis Software market size is predicted to grow from US$ 4486 million in 2025 to US$ 19455 million in 2032; it is expected to grow at a CAGR of 23.4% from 2026 to 2032.

AI Image-assisted Diagnosis Software refers to regulated software systems that apply machine learning and deep neural networks to medical images—such as X-ray, CT, MRI, ultrasound, mammography, and digital pathology—to support clinical diagnosis. These solutions assist physicians by detecting abnormalities, segmenting organs or lesions, quantifying disease burden, prioritizing urgent cases, and providing diagnostic-level recommendations, while final clinical responsibility remains with licensed clinicians. Most products are commercialized as Software as a Medical Device (SaMD) or embedded within imaging equipment, and are integrated into PACS, RIS, or enterprise imaging platforms. Compared with general image analysis tools, image-assisted diagnosis software is more tightly regulated, more clinically validated, and more directly linked to diagnostic decision-making, making it a core segment within the broader artificial intelligence diagnostics market.

The market can be segmented by imaging modality (X-ray, CT, MRI, ultrasound, mammography, pathology), by diagnostic function level (detection, segmentation, classification, severity scoring, diagnostic recommendation), by clinical application (radiology, oncology, cardiology, neurology, women’s health, ophthalmology), by deployment model (on-premise, cloud SaaS, scanner-embedded, enterprise imaging platform), and by regulatory/commercial type (standalone SaMD, bundled software, clinical decision support).

Upstream participants include imaging equipment OEMs, detector and sensor suppliers, GPU and AI accelerator vendors, cloud infrastructure providers, and hospitals contributing annotated imaging datasets. Midstream consists of AI software developers that design, train, validate, and obtain regulatory clearance for diagnostic algorithms, often collaborating with academic centers. Downstream customers are hospitals, imaging centers, and integrated delivery networks, typically procuring solutions through enterprise IT budgets or bundled imaging system contracts.

Key cost components include data acquisition and labeling, algorithm development, clinical validation, regulatory approval, and continuous software updates. Due to software-centric economics, gross margins commonly range from 65% to 80%. Commercial transactions are dominated by subscription SaaS, per-study pricing, or multi-year enterprise licenses, frequently bundled with imaging hardware or PACS upgrades. Market trends include rapid regulatory approvals, consolidation through acquisitions, deeper OEM integration, expansion from radiology into multi-disciplinary diagnostics, and growing adoption driven by radiologist shortages and value-based care initiatives.

LPI (LP Information)' newest research report, the “AI Image-assisted Diagnosis Software Industry Forecast” looks at past sales and reviews total world AI Image-assisted Diagnosis Software sales in 2025, providing a comprehensive analysis by region and market sector of projected AI Image-assisted Diagnosis Software sales for 2026 through 2032. With AI Image-assisted Diagnosis Software sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI Image-assisted Diagnosis Software industry.

This Insight Report provides a comprehensive analysis of the global AI Image-assisted Diagnosis Software 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 AI Image-assisted Diagnosis Software portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI Image-assisted Diagnosis Software market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI Image-assisted Diagnosis Software 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 AI Image-assisted Diagnosis Software.

This report presents a comprehensive overview, market shares, and growth opportunities of AI Image-assisted Diagnosis Software market by product type, application, key players and key regions and countries.

Segmentation by Type:
Ultrasound Image
Radiographic Image
Radiation Therapy
Pathological Analysis
Endoscopic Image

Segmentation by Regulatory & Commercial Type:
Standalone SaMD (FDA/CE cleared)
Bundled with Imaging Equipment
Others

Segmentation by Deployment & Integration:
On-prem
Cloud SaaS
Edge / Embedded
Hybrid
Others

Segmentation by Application:
Hospital
Ambulatory Surgery Center

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.
Butterfly Network
Merative
Tempus
RetinAi
Nanox
Lunit
DiA Imaging
Subtle Medical
BrainMiner
GE
Siemens
Aidoc
Imagen Technologies, Inc.
VUNO, Inc.
Digital Diagnostics
NeuraSignal
Riverain Technologies, LLC
Philips
Microsoft
Viz.ai
RapidAI
Canon Medical
Enlitic
BioMind
ANNALISE-AI PTY LTD
icometrix
KONFOONG BIOTECH INTERNATIONAL CO., LTD（KFBIO）

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