World Market for Oncology Imaging AI

Oncology is where medical imaging AI is being tested most aggressively—and where it is starting to stick. Breast and lung screening programs, complex CT/MRI staging, PET-based theranostics, and RT planning are all pushing clinicians toward faster, more consistent, more quantitative imaging decisions.

This Markintel™ Horizon report quantifies and explains that shift. It analyzes the World Market for Oncology Imaging AI from 2023 to 2032, using a consistent segmentation across:

• Modality: CT, X-ray/DR (incl. DBT), MRI, PET/Nuclear, Ultrasound• Tumor site: Breast, Lung/Chest, Prostate, Colorectal, Liver, Neuro-oncology, and others• Clinical application & pathway stage: from Screening & Risk through Treatment Planning and Response• Revenue stream & buyer type: Hardware attach, Software, Services, Cloud/PPU across Cancer Centers, IDNs/AMCs, Community providers, and Teleradiology

Beyond the numbers, the report applies the full Markintel framework stack—M³, ARC-Index, GTM Growth–Maturity, and the new Upgrade & Package Ladders—to show how AI Software vendors, Imaging OEMs, RT planning providers, AI Platforms, Providers/Telerad networks, and Imaging-Pharma/CROs can convert opportunity into repeatable, profitable business.

The goal is not just to describe the market, but to give executives an insights-to-action playbook: where Oncology Imaging AI is truly ready to scale, which clusters will capture the value, and what evidence, packaging, and partnerships will matter most over the next three to five years.

What’s Covered

Global market sizing & forecast (2023–2032) – total Oncology Imaging AI market today and through 2032, with growth outlook, scenario commentary and key inflection points along the decade.

Granular segmentation of value pools – analysis by modality, tumor site, clinical application, pathway stage, revenue stream and end-use setting (cancer centers, IDNs/AMCs, community hospitals, imaging centers, teleradiology), aligned with the broader Markintel™ AI-in-Imaging taxonomy.

Regional & country perspectives – detailed views for North America, Europe, Asia-Pacific, Latin America and Middle East & Africa, including commentary on leading and fast-growth countries, screening initiatives, and local regulatory/reimbursement dynamics.

Clinical & technology trends across the oncology pathway – how AI is being deployed from breast and lung screening through CT/MR staging, RT planning, PET theranostics and longitudinal response assessment, with use-case mapping to Screening, Diagnosis, Staging, Planning, Response and Surveillance stages.

Regulatory, reimbursement and evidence landscape (ARC) – assessment of Approvals, Reimbursement and Clinical validation by key use case (e.g., DBT AI, CT-lung, adaptive RT, PET response, radiomics), including where Oncology Imaging AI is deployment-ready vs where it remains pilot-only.

Competitive landscape by cluster – analysis of six major competitive clusters (AI Software, Imaging OEMs, RT/TPS vendors, AI Platforms & Cloud, Providers & Teleradiology, Imaging-Pharma/CRO & Trials), with GTM Growth–Maturity positioning and qualitative company spotlights.

GTM & packaging strategies – Markintel Upgrade & Package Ladders for each cluster (Foundation / Advanced / Elite), recommended commercial and pricing rules, channel and partnership strategies, and implications for attach-rate expansion and suite-based selling.

Strategic implications & scenarios – cross-cutting insights on where Oncology Imaging AI is likely to become “workflow-critical infrastructure,” how APAC’s faster growth changes global competition, and what boards, product leaders and investors should prioritize over the next 3–5 years. Show more