We present a real-time stereo hyperspectral imaging (stereo-HSI) system for intraoperative tissue and organ analysis that integrates multispectral snapshot imaging with stereo vision to support clinical decision-making. The system visualize both RGB and high-dimensional spectral data while simultaneously reconstructing 3D surfaces, offering a compact, non-contact solution for seamless integration into surgical workflows. A modular processing pipeline enables robust demosaicing, spectral and spatial fusion, and pixel-wise medical assessment, including perfusion and tissue classification. Our spectral warping algorithm leverages a custom learned mapping, our white-balance network method is the first for snapshot MSI cameras, and our fusion CNN employs spectral-attention modules to exploit the rich hyperspectral domain. Clinical feasibility was demonstrated in 57 surgical procedures, including kidney transplantation, parotidectomy, and neck dissection, achieving high spatial and spectral resolution under standard surgical lighting conditions. The system enables visualization of oxygenation and tissue composition in real-time, offering surgeons a novel tool for image-guided interventions. This study establishes the stereo-HSI platform as a clinically viable and effective method for enhancing intraoperative insight and surgical precision.

We present an interactive and multimodal-based augmented reality system for computer-assisted surgery in the context of ear, nose and throat (ENT) treatment. The proposed processing pipeline uses fully digital stereoscopic imaging devices, which support multispectral and white light imaging to generate high resolution image data, and consists of five modules. Input/output data handling, a hybrid multimodal image analysis and a bi-directional interactive augmented reality (AR) and mixed reality (MR) interface for local and remote surgical assistance are of high relevance for the complete framework. The hybrid multimodal 3D scene analysis module uses different wavelengths to classify tissue structures and combines this spectral data with metric 3D information. Additionally, we propose a zoom-independent intraoperative tool for virtual ossicular prosthesis insertion (e.g. stapedectomy) guaranteeing very high metric accuracy in sub-millimeter range (1/10 mm). A bi-directional interactive AR/MR communication module guarantees low latency, while consisting surgical information and avoiding informational overload. Display agnostic AR/MR visualization can show our analyzed data synchronized inside the digital binocular, the 3D display or any connected head-mounted-display (HMD). In addition, the analyzed data can be enriched with annotations by involving external clinical experts using AR/MR and furthermore an accurate registration of preoperative data. The benefits of such a collaborative surgical system are manifold and will lead to a highly improved patient outcome through an easier tissue classification and reduced surgery risk.