Ex Vivo

Ex vivo research involves studying biological samples outside of a living organism, offering controlled environments for experimentation and analysis not possible in vivo. Current research focuses on developing and validating advanced imaging and sensing techniques, including lidar, hyperspectral imaging, and ultrasound, often coupled with machine learning algorithms like graph neural networks and deep learning models, for applications such as precise tissue mapping, tumor segmentation, and robotic surgical assistance. These advancements are significantly improving the accuracy and efficiency of medical procedures, particularly in minimally invasive surgery and diagnostics, by providing detailed, real-time information about tissue properties and anatomy. The resulting datasets and improved analytical methods are also accelerating the development of more robust and interpretable AI-driven tools for medical image analysis.