Use Cases

With standardized interfaces and high performance, our SDK provides a powerful solution for algorithm reuse and compatibility.

Our areas of expertise and how they can benefit your project.

How web applications based on open source platforms can simplify your processes and ensure easy deployment to your customers' systems.

We customize LLMs to your specific requirements and support seamless integration into your systems!

Chimaera is here to support you every step of the way on your journey to getting your medical device approved under the MDR. We don't just offer software solutions. We also help you explore the best tech options for your needs and get your product to market quickly and affordably.

We are your partner for efficient embedded solutions in NDT by integrating our 3D AI model into embedded systems.

Discover how the Chimaera SDK can revolutionize your web application development and offer your customers the seamless, centralized solutions. Whether you're managing data, advanced rendering, processing images, or developing AI solutions, our SDK provides the tools you need to succeed as a web application.

Our Chimaera team knows AI, data management, labeling, and regulatory affairs inside out. We make sure your project is ready for the market, including all the MDR requirements.

Supporting our clients in the first steps towards designing individual stand-alone apps with our Chimaera SDK.

In the field of orthopedic diagnosis and treatment, generative AI (GenAI) offers great potential for the development of personalized implants.

This use case demonstrates the compensation of cardiac motion in a 3D time series acquired with an MR scanner.

Automation is strongly on the rise in the dental industry. With our experience in radiology, we quickly and cost-effectively develop AI solutions in the dental sector as well.

Our team is currently engaged in a fascinating collaboration with Fraunhofer IKTS on a project centered around battery research.

In this use case, we show how we typically perform an initial project research for an Innovation service project for the use case of AI-based denoising for applications in cone beam CTs.

Using the example of the automatic segmentation of hip and femur from computed tomography, this blog post will show how the path to creating an AI model proceeds and what requirements must be met.

We have developed an algorithm that intelligently reduces the number of parameters of a neural network, while trying to maintain the highest possible accuracy.

Showcase for our Image Registration to compensate respiratory motion in a PET-CT image pair of a melanoma patient. The images were acquired at different times with individual scanners.

In this use case we realized a robust and accurate segmentation of the liver, the spleen, the kidneys and the heart in various Magnetic Resonance Imaging (MRI) sequences.