Embedded AI in endoscopy: Exceptional performance when it matters most

Today, modern endoscopy stands for precision, efficiency, and patient-centered innovation. While a few decades ago, technical possibilities were limited to simple image transmission, users today expect razor-sharp HD or 4K images supplemented by smart AI processes, such as automatic polyp detection and 3D reconstruction of complex structures. 
These technologies must be reliably available to physicians and teams in everyday clinical practice, not only under laboratory conditions. The key lies in powerful hardware that processes image data in real time with virtually no delay – and this is exactly where embedded systems come into play.

Compact, efficient, and reliable with embedded AI

Every millisecond counts in the operating room. Minimally invasive procedures and diagnostic processes require constant real-time capability, which is enabled by the deterministic processing of image data using specialized embedded hardware. This provides physicians with immediate visual support when precise control of instruments is needed or critical areas must be identified. Unlike PC-based solutions, which offer more flexibility but can cause higher latencies, the specialized embedded architecture guarantees fast, controlled data processing, thereby fostering confidence in the safety and efficiency of the procedure.

In addition to speed, compactness and reliability are essential. Endoscopic systems should be highly functional, handy, and robust. Embedded hardware provides the necessary computing power directly within the device or camera head while remaining energy-efficient. These platforms are designed for continuous operation in clinical environments and have low failure rates. Their architecture significantly simplifies the path through regulatory validation and approval. This improves everyday usability and ensures that advanced image processing benefits patients.

Embedded systems for medical applications are impressive because of their specialization. They can be configured to perform complex image processing algorithms, such as narrow-band imaging, automatic segmentation, 3D reconstruction, and AI-based analyses. Combining multiple applications on a single platform facilitates integration into existing devices and opens up new possibilities for innovative functionalities. This creates sustainable added value for medical practices, clinics, and research projects.