5 papers
Reliable Mislabel Detection for Video Capsule Endoscopy Data
Julia Werner, Julius Oexle, Oliver Bause +5
The classification performance of deep neural networks relies strongly on access to large, accurately annotated datasets. In medical imaging, however, obtaining such datasets is pa…
Seeing More with Less: Video Capsule Endoscopy with Multi-Task Learning
Julia Werner, Oliver Bause, Julius Oexle +4
Video capsule endoscopy has become increasingly important for investigating the small intestine within the gastrointestinal tract. However, a persistent challenge remains the short…
Enhanced Anomaly Detection for Capsule Endoscopy Using Ensemble Learning Strategies
Julia Werner, Christoph Gerum, Jorg Nick +4
Capsule endoscopy is a method to capture images of the gastrointestinal tract and screen for diseases which might remain hidden if investigated with standard endoscopes. Due to the…
Smart Video Capsule Endoscopy: Raw Image-Based Localization for Enhanced GI Tract Investigation
Oliver Bause, Julia Werner, Paul Palomero Bernardo +1
For many real-world applications involving low-power sensor edge devices deep neural networks used for image classification might not be suitable. This is due to their typically la…
Systematic Hardware Integration Testing for Smart Video-based Medical Device Prototypes
Oliver Bause, Julia Werner, Oliver Bringmann
This paper presents a hardware-in-the-loop (HIL) verification system for intelligent, camera-based in-body medical devices. A case study of a Video Capsule Endoscopy (VCE) prototyp…