LED-based hyperspectral endoscopic imaging: Optical simulation-guided illumination optimization

Digestive system cancers, particularly esophageal cancer, remain difficult to detect in early stages due to the limited sensitivity of conventional white-light endoscopy. Hyperspectral endoscopic imaging enhances tissue contrast by exploiting wavelength-dependent optical properties. However, its performance depends on efficient and uniform spectral illumination under highly constrained and asymmetric endoscope tip geometries. In practice, the imaging sensor is offset from the center due to the existence of instrument channels and air/water nozzles, complicating LED placement and degrading illumination uniformity. In this work, we present an optical simulation-driven framework for optimizing LED placement in an LED-based, asymmetric hyperspectral endoscopic illumination system. Non-sequential ray tracing and merit-function-based optimization were implemented in Zemax OpticStudio to optimize LED spatial configurations. Two local optimization algorithms-Damped Least Squares (DLS) and Orthogonal Descent (OD)-were systematically evaluated across fifteen wavelength groups. Both methods achieved measurable improvements in irradiance distribution. Overall, OD slightly outperformed DLS, yielding average irradiance improvements of 11.30% on the esophagus wall and 10.15% on the LED field of view relative to the pre-optimization configuration, whereas DLS achieved corresponding average increases of 7.03% and 6.55%, respectively. Rather than prescribing a fixed LED placement pattern, the results provide practical design guidance by demonstrating how adaptive, optimization-driven LED positioning can effectively compensate for asymmetric endoscope geometries while prioritizing different illumination targets. These findings demonstrate that simulation-based LED placement optimization can provide effective guidance for the design of hyperspectral endoscopic illumination systems, high-fidelity modeling, and experimental validation.