AI-superpowered medical imaging

World's first AI-based vessel scanners and out-of-box medical imaging software​

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Engaging New Challenges in Medical Vision Engaging New Challenges in Medical Vision

Engaging New Challenges in Medical Vision

Our multipurpose scanning systems are applicable to a variety of medical fields ranging from eased and more comfortable venipuncture procedures to phlebology and aesthetic cosmetology.

Engaging New Challenges in Medical Vision

Key facts

Patented Technology

Patented Technology

Our team has successfully registered 2 international patents covering the technologies we use in our systems

Peer-reviewed results

Peer-reviewed results

We have published 2 project-related scientific papers in peer-reviewed journals: IEEE Control Systems Letters and IEEE ICARCV

$40K Fundraised

$40K Fundraised

We raised 40,000 USD to reach the TRL-5 stage and acquire patents. And we keep working hard according to our go-to-market strategy

Always moving on

We are a rapidly growing startup and our competences are trusted by top industry companies

Our partners
Skolkovo residents since 2022

Skolkovo residents since 2022

Vein CV is happy to announce that we have been accepted to the Skolkovo Innovation Center residency.

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Our Recent News


Media coverage and company updates

International patent approved

International patent approved

The present invention relates to a method for neural network training for near-infrared vein imaging, the method including obtaining a set of raw images based on near-infrared radiation from vein; pre-processing the set of raw images using a filter and/or an adaptive filter, and/or a denoising network to enhance the visibility of veins and applying an annotation tool for removing the noise and for generating annotated ground truth masks;

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Новая российская разработка поможет взять кровь из вены без лишней боли

Новая российская разработка поможет взять кровь из вены без лишней боли

С помощью этого устройства можно достаточно точно определить контуры вен на ногах и руках, причем в абсолютно автоматическом режиме, не требующем пользовательских данных. Это стало возможным благодаря использованию искусственных нейронных сетей и методов обучения с подкреплением.

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