Lung lesions segmentation on CT scans

AI tool detection of potential melanoma metastases

Early and precise detection of lung lesions in CT scans is critical for diagnosing melanoma metastases. AI segmentation technique enhances accuracy and efficiency.

Challenge

The client required a reliable, automated method to detect and characterize lung lesions while accounting for the unique properties of lung CT scans.

Approach

  • Developed segmentation models optimized for lung CT scans.
  • Utilized SOTA computer vision techniques for enhanced accuracy.

Results

  • Automated lesion detection, improving melanoma metastasis identification.
  • Enabled quantification of radiomic features for lesion characterization.

This AI supported approach improves early melanoma detection, supporting timely and effective treatment decisions.

Want to achieve similar efficiency gains? Let's discuss how we can optimize your clinical project.

You might be also interested in:

Accelerating biomarker discovery through omic data integration into drug screens
Accelerating biomarker discovery through omic data integration
Two scientists observing AI-driven cell analysis on a digital screen, representing decision-making in biotech innovation.
Build or Buy? Strategic Considerations for Biotech Companies Implementing AI Solutions
biotech US market
AI in biotech: What the US market got right (and what it’s still learning)
From Data Chaos to Drug Discovery – Ardigen Talk at NextGen Omics Conference

Contact

Ready to transform drug discovery?

Discover how one of the top AI CROs in the world, can be your trusted partner in revolutionizing drug discovery through AI.

Contact us today to learn more about our tailored solutions for empowering your drug development journey.

Send us a message and we will contact you back within 48 hours.

Newsletter

Become an insider

Be the first to know about Ardigen’s latest news and get access to our publications, webinars and more!