Global AI Lung Screening System Market Growth (Status and Outlook) 2026-2032
Description
The global AI Lung Screening System market size is predicted to grow from US$ 329 million in 2025 to US$ 755 million in 2032; it is expected to grow at a CAGR of 12.6% from 2026 to 2032.
AI Lung Screening System is an integrated software-driven solution that supports early detection and risk stratification of lung cancer—primarily by analyzing low-dose CT (LDCT) scans in screening or incidental nodule workflows. The system typically performs automated lung nodule detection, segmentation, volumetry, growth tracking, malignancy risk scoring, and structured reporting, aiming to reduce radiologist workload, improve consistency, and standardize follow-up recommendations. In practice, it functions as a clinical decision support layer within radiology operations: it flags suspicious findings, prioritizes worklists, and helps quantify change over time. Commercially, “system” usually refers to a deployable product package (software + workflow integration + validation/regulatory package), rather than an algorithm alone, and is increasingly delivered as a platform with continuous model updates, audit trails, and performance monitoring.
From a multi-angle segmentation standpoint, the market can be parameterized by: (1) Clinical scenario: population LDCT screening vs incidental pulmonary nodules; (2) Algorithmic functions: detection-only, detection+volumetry, full risk scoring (e.g., malignancy probability), and longitudinal tracking; (3) Deployment: on-premise server, private cloud, public cloud/SaaS, or hybrid; (4) Integration depth: standalone viewer vs PACS/RIS embedded workflow with structured reporting; (5) Regulatory class & claims: CAD support vs triage vs quantified decision support. Additional quantitative “type” parameters include supported CT slice thickness, acceptable dose range, nodule size range (e.g., ≥3 mm), sensitivity at fixed false-positive rates, throughput (studies/hour), and interoperability standards (DICOM, HL7/FHIR).
In transaction terms, pricing commonly follows (a) annual subscription per site, (b) per-scan fee, or (c) enterprise license tied to volume tiers, with separate charges for integration, validation support, and service-level agreements. Procurement often runs through hospital IT/security reviews and radiology leadership, with pilots (3–6 months) preceding multi-year contracts. Key trends include tighter workflow embedding (worklist triage + structured reporting), expansion from single-task CAD to end-to-end nodule management, growing emphasis on generalizability and bias control across scanners and populations, and integration of multimodal data (clinical risk factors, prior imaging) to improve risk stratification. As screening volumes rise and radiologist shortages persist, vendors that can prove reduced recall burden, stable false-positive control, and seamless integration are best positioned for durable share gains.
LPI (LP Information)' newest research report, the “AI Lung Screening System Industry Forecast” looks at past sales and reviews total world AI Lung Screening System sales in 2025, providing a comprehensive analysis by region and market sector of projected AI Lung Screening System sales for 2026 through 2032. With AI Lung Screening System sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI Lung Screening System industry.
This Insight Report provides a comprehensive analysis of the global AI Lung Screening System 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 Lung Screening System portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI Lung Screening System market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI Lung Screening System 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 Lung Screening System.
This report presents a comprehensive overview, market shares, and growth opportunities of AI Lung Screening System market by product type, application, key players and key regions and countries.
Segmentation by Type:
Lung Cancer Early Screening
Pulmonary Nodule Detection & Tracking
High-Risk Population Screening
Incidental Lung Finding Screening
Others
Segmentation by Imaging Modality & Data Source:
LDCT-based Screening System
Standard Chest CT AI System
Others
Segmentation by Deployment & Integration Model:
On-premise
Private Cloud (Hospital-owned Cloud)
Public Cloud / SaaS
Others
Segmentation by Application:
Medical Institutions
Great Health Scene
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.
Lunit
Aidoc
VUNO, Inc.
Riverain Technologies, LLC
Viz.ai
RapidAI
Enlitic
ANNALISE-AI PTY LTD
INFERVISION TECHNOLOGY
Lianying Intelligent Medical Technology
Please note: The report will take approximately 2 business days to prepare and deliver.
AI Lung Screening System is an integrated software-driven solution that supports early detection and risk stratification of lung cancer—primarily by analyzing low-dose CT (LDCT) scans in screening or incidental nodule workflows. The system typically performs automated lung nodule detection, segmentation, volumetry, growth tracking, malignancy risk scoring, and structured reporting, aiming to reduce radiologist workload, improve consistency, and standardize follow-up recommendations. In practice, it functions as a clinical decision support layer within radiology operations: it flags suspicious findings, prioritizes worklists, and helps quantify change over time. Commercially, “system” usually refers to a deployable product package (software + workflow integration + validation/regulatory package), rather than an algorithm alone, and is increasingly delivered as a platform with continuous model updates, audit trails, and performance monitoring.
From a multi-angle segmentation standpoint, the market can be parameterized by: (1) Clinical scenario: population LDCT screening vs incidental pulmonary nodules; (2) Algorithmic functions: detection-only, detection+volumetry, full risk scoring (e.g., malignancy probability), and longitudinal tracking; (3) Deployment: on-premise server, private cloud, public cloud/SaaS, or hybrid; (4) Integration depth: standalone viewer vs PACS/RIS embedded workflow with structured reporting; (5) Regulatory class & claims: CAD support vs triage vs quantified decision support. Additional quantitative “type” parameters include supported CT slice thickness, acceptable dose range, nodule size range (e.g., ≥3 mm), sensitivity at fixed false-positive rates, throughput (studies/hour), and interoperability standards (DICOM, HL7/FHIR).
In transaction terms, pricing commonly follows (a) annual subscription per site, (b) per-scan fee, or (c) enterprise license tied to volume tiers, with separate charges for integration, validation support, and service-level agreements. Procurement often runs through hospital IT/security reviews and radiology leadership, with pilots (3–6 months) preceding multi-year contracts. Key trends include tighter workflow embedding (worklist triage + structured reporting), expansion from single-task CAD to end-to-end nodule management, growing emphasis on generalizability and bias control across scanners and populations, and integration of multimodal data (clinical risk factors, prior imaging) to improve risk stratification. As screening volumes rise and radiologist shortages persist, vendors that can prove reduced recall burden, stable false-positive control, and seamless integration are best positioned for durable share gains.
LPI (LP Information)' newest research report, the “AI Lung Screening System Industry Forecast” looks at past sales and reviews total world AI Lung Screening System sales in 2025, providing a comprehensive analysis by region and market sector of projected AI Lung Screening System sales for 2026 through 2032. With AI Lung Screening System sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI Lung Screening System industry.
This Insight Report provides a comprehensive analysis of the global AI Lung Screening System 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 Lung Screening System portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI Lung Screening System market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI Lung Screening System 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 Lung Screening System.
This report presents a comprehensive overview, market shares, and growth opportunities of AI Lung Screening System market by product type, application, key players and key regions and countries.
Segmentation by Type:
Lung Cancer Early Screening
Pulmonary Nodule Detection & Tracking
High-Risk Population Screening
Incidental Lung Finding Screening
Others
Segmentation by Imaging Modality & Data Source:
LDCT-based Screening System
Standard Chest CT AI System
Others
Segmentation by Deployment & Integration Model:
On-premise
Private Cloud (Hospital-owned Cloud)
Public Cloud / SaaS
Others
Segmentation by Application:
Medical Institutions
Great Health Scene
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.
Lunit
Aidoc
VUNO, Inc.
Riverain Technologies, LLC
Viz.ai
RapidAI
Enlitic
ANNALISE-AI PTY LTD
INFERVISION TECHNOLOGY
Lianying Intelligent Medical Technology
Please note: The report will take approximately 2 business days to prepare and deliver.
Table of Contents
84 Pages
- *This is a tentative TOC and the final deliverable is subject to change.*
- 1 Scope of the Report
- 2 Executive Summary
- 3 AI Lung Screening System Market Size by Player
- 4 AI Lung Screening System by Region
- 5 Americas
- 6 APAC
- 7 Europe
- 8 Middle East & Africa
- 9 Market Drivers, Challenges and Trends
- 10 Global AI Lung Screening System Market Forecast
- 11 Key Players Analysis
- 12 Research Findings and Conclusion
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