📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Fluorescence lifetime imaging endomicroscopy based ex-vivo lung cancer prediction using multi-scale concatenated-dilation convolutional neural networks (2021)

First Author: Wang Q

Attributed to: EPSRC IRC Proteus - Multiplexed 'Touch and Tell' Optical Molecular Sensing and Imaging - Lifetime and Beyond funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1117/12.2580467

Publication URI: http://dx.doi.org/10.1117/12.2580467

Type: Conference/Paper/Proceeding/Abstract