Unifying Insight: From Image to Impact
Intelligent risk. Confident detection.
Clinically calibrated AI models.
Unified in one visionary ecosystem.
Volpara x Lunit has unified under the Lunit name – and our mission is clear: delivering a comprehensive AI-powered breast ecosystem where every insight works together.
Detection that finds cancers earlier, quality tools that improve accuracy, and image-based risk that forecasts the future – all combined into one seamless workflow. Our ecosystem transforms images to impact, enabling breast care teams to deliver smarter, more confident care at every step of the journey.
Lunit INSIGHT Image-Based Risk *coming soon
Forecast near-term breast cancer risk
Estimates a woman’s risk of developing breast cancer in the next five years – based solely on her mammogram – enabling more proactive and personalized care.
Volpara Analytics
Elevate imaging quality & compliance
Tracks image quality and technologist performance with AI-powered analytics to reduce retakes, improve consistency, and ensure compliance.
Volpara Risk Pathways
Personalized lifetime screening plans
Combines genetics, family history and density to create a unified long-term risk profile for precision screening.
Explore Risk Pathways
Volpara Scorecard
Automated, objective density measurement
Provides consistent, validated breast density scores to reduce variability and strengthen diagnostic confidence across radiologists.
Explore Scorecard
Volpara Patient Hub
Keep patients engaged & informed
Integrates risk into records and workflows to deliver personalized reminders, education, and clearer patient communication.
Explore Patient Hub
Where Innovation Meets Insight: Join Our Workshops
Join Lunit for expert-led workshops featuring top radiologists and innovators advancing the future of AI in breast cancer screening. Reserve your spot now.
Spotlight Session: Essential Viewing for you:
Bridging Radiology and Epidemiology to Understand Image-Based Risk
📆 Sunday, November 30, 2025
🕒 1:30 PM - 2:00 PM CST
Emerging image-based risk (IBR) models are transforming how we understand and predict breast cancer risk. This session bridges radiology and epidemiology to illustrate how imaging phenotypes can inform an individual woman’s risk within the broader framework of population-level risk stratification—offering a powerful complement to traditional models Instructor Led Course | Volpara x Lunit Academy
Speakers
Graham Colditz, MD, DrPH
Associate Director, Prevention and Control at Siteman Cancer Center and Neiss-Gain Professor, Washington University, St. Louis, Missouri
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Shu (Joy) Jiang, PhD
Associate Professor of Surgery, Division of Public Health Sciences, Washington University School of Medicine, St. Louis, Missouri & Director of the Epidemiology & Biostatistics Cancer Imaging Research Center at Washington University School of Medicine
Hari M. Trivedi, MD
Associate professor in the Department of Radiology and Imaging Sciences and Department of Biomedical Informatics at Emory University School of Medicine, Atlanta, GA
Christopher Austin, MD, MSc
Global Medical Director for Cancer Screening at Lunit, Seattle WA
Putting Breast AI into Practice: How Should Academic Centers Lead The Way?
📆 Tuesday, December 2, 2025
🕒 10:30 AM - 11:00 AM CST
Despite the absence of formal reimbursement, radiologist interest and patient demand are driving the use of AI in breast cancer screening globally—particularly among private, fee-for-service providers, where some centers now offer women the option to add incorporate AI as a second reader in the interpretation of their mammogram. Academic medical centers, however, often face a different decision landscape— carefully balancing innovation with evidence generation, equity, training residents/fellows, and resource stewardship.Twelve months ago, under the leadership of Dr Elizabeth Morris, UC Davis became one of the first U.S. academic institutions to implement an FDA-cleared breast AI detection solution (Lunit INSIGHT DBT) for all screening participants—not as a research tool, but as part of routine clinical practice. By contrast, Dr Elizabeth Burnside and her team at the University of Wisconsin–Madison are preparing to participate in the two-year, multi-center, prospective PRISM study, designed to rigorously evaluate breast AI performance and impact before broad adoption. Join us for a lively and collegial debate with two leading academic breast imagers as they explore what shaped their respective approaches—evidence, ethics, cost, and risk—and consider the broader question: What does academic leadership look like in bringing Breast AI from research to routine care? Instructor Led Course | Volpara x Lunit Academy
Speakers
Liz Morris, MD
Department Chair Radiology at University of California, Davis - School of Medicine
Elizabeth Burnside, MD, MPH, MS, FACR, FSBI
Professor, Department of Radiology, U. Wisconsin School of Medicine and Public Health, Madison, WI
Christopher Austin, MD, MSc
Global Medical Director for Cancer Screening at Lunit, Seattle WA
The Ripple Effect of AI
Sol Radiology credit INSIGHT MMG & DBT with faster reads, stronger referrals, and smaller cancers detected.
Precision Medicine and Seamless IT
Read how Kettering Health uses Volpara Risk Pathways to achieve precision medicine and seamless IT in their personalized cancer prevention program.
Setting the Bar High
Learn why the University of Rochester relies on Volpara Analytics to help provide consistent, exceptional imaging and experience low technical repeat rates.
