Parallel Implementations Assessment of a Spatial-Spectral Classifier for Hyperspectral Clinical Applications

arXiv:2404.10631v1 Announce Type: cross
Abstract: Hyperspectral (HS) imaging presents itself as a non-contact, non-ionizing and non-invasive technique, proven to be suitable for medical diagnosis. However, the volume of information contained in these images makes difficult providing the surgeon with information about the boundaries in real-time. To that end, High-Performance-Computing (HPC) platforms become necessary. This paper presents a comparison between the performances provided by five different HPC platforms while processing a spatial-spectral approach to classify HS images, assessing their main benefits …

abstract applications arxiv assessment classifier clinical computing cs.lg cs.pf diagnosis however images imaging information medical performance real-time spatial type