  Over the last two decades, augmented reality (AR) has led to the rapid
development of new interfaces in various fields of social and technological
application domains. One such domain is medicine, and to a higher extent
surgery, where these visualization techniques help to improve the effectiveness
of preoperative and intraoperative procedures. Following this trend, this paper
presents SLIMBRAIN, a real-time acquisition and processing AR system suitable
to classify and display brain tumor tissue from hyperspectral (HS) information.
This system captures and processes HS images at 14 frames per second (FPS)
during the course of a tumor resection operation to detect and delimit cancer
tissue at the same time the neurosurgeon operates. The result is represented in
an AR visualization where the classification results are overlapped with the
RGB point cloud captured by a LiDAR camera. This representation allows natural
navigation of the scene at the same time it is captured and processed,
improving the visualization and hence effectiveness of the HS technology to
delimit tumors. The whole system has been verified in real brain tumor
resection operations.
