By adapting 3D FuseUnet, CNN fSNAP showed better performance in lumen and IPH depiction compared with traditional fSNAP. The results suggest that deep learning can help fast SNAP scans produce high quality images, which could have great clinical utility.
This abstract and the presentation materials are available to members only; a login is required.