VaraNEW

Vara is an AI-powered software platform specifically developed for breast cancer screening and mammography reading. The CE-marked solution acts as an intelligent assistant for radiologists to identify suspicious lesions with higher precision and efficiency. By integrating advanced deep learning algorithms, Vara helps reduce false-negative results and speeds up the triage of normal mammograms.

The platform operates by analyzing digital DICOM mammography images directly imported from existing PACS systems in clinics and screening centers. Vara automatically evaluates image data, visually highlights suspicious areas, and provides a structured pre-assessment. Radiologists maintain full clinical control at all times and make the final diagnostic decisions.

Vara is deployed primarily in national and regional breast cancer screening programs as well as specialized radiological practices. By streamlining diagnostic workflows, the platform enables medical professionals to focus more time on complex cases. Ultimately, Vara contributes significantly to early cancer detection and improves the standard of care for patients.

• Automated Triage & Worklist Prioritization — Vara categorizes mammograms according to risk profiles and pre-sorts routine normal findings. This allows radiologists to identify and evaluate urgent suspicious cases more quickly.
• AI-Powered Lesion Detection — Advanced deep learning models highlight microcalcifications and abnormal tissue structures directly on DICOM images. This minimizes the risk of missing early-stage tumors.
• Seamless PACS & RIS Integration — The software embeds directly into established radiological IT infrastructures. Physicians continue working within their familiar reading environment without workflow disruptions.

The platform is aimed at radiologists, mammography screening centers, breast clinics, and healthcare system operators.

A regional breast screening center processes hundreds of screening mammograms every day. Using Vara, clear normal scans are triaged efficiently while subtle microcalcifications and suspicious masses are automatically highlighted for radiological review. This reduces average reading time per patient significantly while simultaneously boosting the detection rate of early-stage breast cancer.

• The platform is aimed at radiologists, mammography screening centers, breast clinics, and healthcare system operators.
• A regional breast screening center processes hundreds of screening mammograms every day.
• Automated Triage & Worklist Prioritization: Vara categorizes mammograms according to risk profiles and pre-sorts routine normal findings. This allows radiologists to identify and evaluate urgent suspicious cases more quickly.
• AI-Powered Lesion Detection: Advanced deep learning models highlight microcalcifications and abnormal tissue structures directly on DICOM images. This minimizes the risk of missing early-stage tumors.
• Seamless PACS & RIS Integration: The software embeds directly into established radiological IT infrastructures. Physicians continue working within their familiar reading environment without workflow disruptions.

Vara is not intended for standalone diagnosis by patients or non-medical personnel and should not be used outside of dedicated mammography reading workflows.

• Aignostics — Paid · HQ: Berlin, Germany · Unclear
• contextflow — Paid · HQ: Wien, Austria · GDPR / EU
• deepc — Paid · HQ: München, Germany · GDPR / EU
• mediaire — Paid · HQ: Berlin, Germany · Unclear