@ARTICLE{ iet:/content/journals/10.1049/htl.2013.0043, author = {Darren Craven}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, author = {Martin O'Halloran}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, author = {Brian McGinley}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, author = {Raquel C. Conceicao}, affiliation = {Faculdade de Ciencias, Universidade de Lisboa, Instituto de Biofisica e Engenharia Biomedica, Lisbon, Portugal}, author = {Liam Kilmartin}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, author = {Edward Jones}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, author = {Martin Glavin}, affiliation = {College of Engineering and Informatics, National University of Ireland Galway, University Road, Galway, Ireland}, keywords = {subsampling acquisition;imaging time;compressed sensing;biomedical imaging;reconstruction quality;compressive sampling;data acquisition time;time critical microwave imaging;}, language = {English}, abstract = {Across all biomedical imaging applications, there is a growing emphasis placed on reducing data acquisition and imaging times. This research explores the use of a technique, known as compressive sampling or compressed sensing (CS), as an efficient technique to minimise the data acquisition time for time critical microwave imaging (MWI) applications. Where a signal exhibits sparsity in the time domain, the proposed CS implementation allows for sub-sampling acquisition in the frequency domain and consequently shorter imaging times, albeit at the expense of a slight degradation in reconstruction quality of the signals as the compression increases. This Letter focuses on ultra wideband (UWB) radar MWI applications where reducing acquisition is of critical importance therefore a slight degradation in reconstruction quality may be acceptable. The analysis demonstrates the effectiveness and suitability of CS with UWB applications.}, title = {Compressive sampling for time critical microwave imaging applications}, journal = {Healthcare Technology Letters}, issue = {1}, volume = {1}, year = {2014}, month = {March}, pages = {6-12(6)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=6epsbumgn8jrt.x-iet-live-01content/journals/10.1049/htl.2013.0043} }