Seeing the Unseen:
Revolutionizing Early Breast Cancer Screening

Designed specifically for dense breast tissue. By combining cutting-edge AI with 3D volumetric ultrasound technology, we are elevating early detection rates to world-leading levels and redefining healthcare standards for women globally.

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Verified Screenings
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Detection Rate Increase
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Screening Sites Nationwide

The Global Challenge: Dense Breast Tissue

For the majority of women globally with dense breast tissue, traditional screening methods face significant limitations. Hundreds of millions of women need a more precise solution.

Traditional 2D X-Ray
Traditional 2D X-Ray

Obscured by Density

In dense breasts, lesions often overlap with healthy tissue, leading to a missed diagnosis rate as high as 40% - 60%.

PathoVision 3D Solution

Unprecedented Clarity

Blind-spot-free tomographic scanning with AI-assisted lesion localization completely solves the tissue overlap issue.

An Innovation-Driven Holistic Ecosystem

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3D Volumetric Ultrasound

Radiation-free, highly comfortable, and automatically acquires complete 3D breast data, breaking the dependency on an operator's manual skills.

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AI-Driven Diagnosis

Deep learning algorithms analyze massive 3D data in real-time, accurately identifying tiny calcifications and masses to assist doctors.

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Cloud & Grid Operation

Secure data aggregation in the cloud empowers grassroots clinics, enabling efficient, standardized screening operations at a massive scale.

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Remote Expert System

Direct connection to top-tier hospital expert teams, breaking geographical barriers to provide authoritative remote reviews.

Transforming City-Wide Defense: The Shenzhen Model

In Shenzhen, a city of 20 million, PathoVision's comprehensive solution has been fully implemented. Validated by large-scale screening, we have increased the early breast cancer detection rate by nearly 8 times, reaching and exceeding international leading levels.

4 / 10,000
Traditional Screening
31 / 10,000
PathoVision Model

* Source: Shenzhen Health Commission & Field Validation. Results published in the American Journal of Roentgenology and the St. Gallen Breast Cancer Conference.