How does the solution integrate into existing radiology systems?

Continue using your existing systems and supplement them with the Vara platform and cloud-based analysis. The AI complements diagnostic reporting with additional analysis results and supports radiologists in evaluating abnormal findings in their daily screening work.

What data leaves the hospital, and how is it protected?

For analysis, image data is transferred to the cloud and processed there. Processing takes place as part of the described hybrid data processing model, which combines local preprocessing with cloud-based analysis in a sovereign, European cloud environment.

How can you get started without major upfront investments?

Use cloud resources as needed. Usage-based billing enables a phased rollout without high initial investments. This allows you to evaluate and measure initial efficiency potential early on and then expand it in a targeted manner.

AI-Assisted Mammography Screening

Improve the quality and speed of your mammography screening with AI-powered image analysis on STACKIT

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Medical professional examining mammogram images on a screen with a patient standing at the mammography machine.

Challenge: Diagnostic accuracy under high volume and cost pressures

In mammography screening, you face significant pressure to handle high volumes while maintaining quality. Images must be interpreted quickly, while expectations for reliable early detection continue to rise. Clinics also face additional challenges:

High diagnostic uncertainty

In women with dense breast tissue, tumors are often missed in standard screenings, and false negatives jeopardize early detection.

False alarms and their associated costs

False positives lead to unnecessary follow-up tests, cause anxiety among patients, and tie up valuable resources.

Enormous pressure to maintain throughput

Radiologists must evaluate as many images as possible in a short amount of time. Signs of fatigue increase the risk of careless errors.

IT investment backlog

Local server capacity is often insufficient to perform the computationally intensive AI analyses required for modern 3D tomosynthesis images.

Measurable Value: Greater confidence, higher throughput, more flexible costs

Use AI to specifically alleviate the workload on your radiology teams and improve the quality of diagnostic reporting. By combining Vara AI with STACKIT infrastructure, you can increase diagnostic precision and gain financial flexibility for future growth:

Maximum process efficiency: By automatically filtering out unremarkable cases—which account for about 40 to 50%—radiologists can focus on critical findings and increase throughput.
Significantly reduced analysis workload: Automated normal filtering reduces the amount of manual routine review.
Minimized liability: AI acts as a second opinion and reduces errors due to carelessness.
Cost flexibility in screening operations: Pay-per-use for compute and storage replaces high one-time investments in proprietary hardware.

Solution: Hybrid AI pipeline with Vara and STACKIT

Leverage your existing systems and supplement them with a specialized AI pipeline. The Vara platform handles AI-assisted normal filtering and flags areas of concern for the radiologist. Data processing is hybrid: local preprocessing and in-depth analysis on scalable STACKIT GPU clusters in the cloud work in tandem. There, computationally intensive models run at peak performance. Use STACKIT Object Storage to store large volumes of image data cost-effectively and for the long term. This creates an integrated analysis process that sustainably improves diagnostic accuracy and screening efficiency.

Competitive Advantage: Position Your Clinic as a Leader in Quality and Innovation

With AI-powered mammography screening, you clearly distinguish yourself in the market. You combine greater diagnostic accuracy with more efficient processes and visibly position your clinic as a modern provider of early detection services.

Quality Leadership in Diagnostics

AI-supported diagnostic accuracy becomes a visible hallmark of your facility’s quality.

Greater trust among patients and referring physicians

The added assurance provided by a second, AI-based review fosters acceptance.

Liability and Reputation Protection

Reduced error rates lower the risk of costly claims.

An attractive employer for skilled workers

Modern systems support radiologists in their day-to-day work, thereby reducing the pressure of high caseloads.

Foundation: AI-powered data processing for mammography screening

The technical foundation combines specialized AI analysis with scalable cloud processing and efficient data storage. It creates the conditions necessary to reliably process large volumes of high-resolution image data and make it usable for diagnostic interpretation. At the same time, the analysis processes are designed to meet the increasing demands for speed and precision in screening.

A doctor wearing a face mask, glasses, and gloves stands in a modern, futuristically lit medical room. He is holding a tablet and interacting with two glowing, holographic screens displaying medical data, charts, and scans. A luminous, blue MRI or CT scanner is visible in the background. The image symbolizes medical technology and digital health data.

Vara AI Platform

Filtering of unremarkable findings (“Normal Filtering”) and highlighting of areas of concern for interpretation

Abstract visualization of flowing data streams and binary code in cyan on a black technological background.

Hybrid Data Processing

A combination of local preprocessing and in-depth analysis on scalable STACKIT GPU clusters in the cloud

STACKIT Compute Engine GPU

Providing scalable computing power for AI analysis of high-resolution image data

More information

Visualization of structured data records and file containers

STACKIT Object Storage

Cost-effective long-term archiving of large volumes of image data

More about STACKIT Object Storage

Frequently Asked Questions (FAQ)

Ready for more accurate diagnostics and greater efficiency in mammography screening?

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