King's College London

Research portal

Super-Resolved Micro-Vascular Imaging Using Microbubbles and Machine Learning

Research output: Chapter in Book/Report/Conference proceedingConference paper

Original languageEnglish
Title of host publicationIEEE EMBS 2014 Micro and Nanotechnology in Medicine Conference
Number of pages1
StatePublished - 2014

King's Authors


Recent developments in sub-diffraction ultrasound (US) imaging using clinical US systems has shown the potential to resolve structures on the micrometer scale using microbubbles (MBs). These rely on user-defined thresholds for MB identification making their clinical application challenging. Here, an automated post-processing algorithm based on k-means clustering has been developed to identify noise, individual and multiple MB in vivo without user interaction. This method has the potential to non-invasively image in real-time pathological or therapeutic changes in the micro-vasculature at centimeter depths in a clinical setting.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454