Physics-Informed Deep Learning Approaches to Restore and Enhance Hyperspectral Images of Brain

Brisbane Convention & Exhibition Centre 

Hyperspectral imaging (HSI) is vital in biomedical fields like brain imaging, distinguishing tissues via spectral differences for diagnostics and surgical tools (Fabelo, 2018; Yoon, 2022). Mass Spectrometry Imaging (MSI), a prominent HSI technique, maps thousands of chemicals but faces "3S triangle" trade-offs between spectral resolution, spatial resolution, and speed, limiting spatial resolution to 10–100 µm.
HyReS, a deep learning-based restoration and super-resolution method, overcomes these challenges. By integrating physics-informed Fourier constraints, it ensures spectral and spatial fidelity without large datasets. HyReS restores resolution beyond hardware limits, preserving data integrity and enabling precise downstream analyses, advancing HSI applications.