Imperial College London
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Professor Chris Dunsby

Faculty of Natural Sciences, Department of Physics

Professor of Biomedical Optics
 
 
 
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Contact

 

+44 (0)20 7594 7755christopher.dunsby Website

 
 
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Location

 

622Blackett LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Jeffries:2017:10.1109/ULTSYM.2017.8091563,
author = {Jeffries, KC and Schirmer, M and Brown, J and Harput, S and Tang, MX and Dunsby, C and Aljabar, P and Eckersley, R},
doi = {10.1109/ULTSYM.2017.8091563},
title = {Notice of Removal: Automated super-resolution image processing in ultrasound using machine learning},
url = {http://dx.doi.org/10.1109/ULTSYM.2017.8091563},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Clinical implementation of super-resolution (SR) ultrasound imaging requires accurate single microbubble detection, and would benefit greatly from automation in order to minimize time requirements and user dependence. We present a machine learning based post-processing tool for the application of SR ultrasound imaging, where we utilize superpixelation and support vector machines (SVMs) for foreground detection and signal differentiation.
AU  - Jeffries,KC
AU  - Schirmer,M
AU  - Brown,J
AU  - Harput,S
AU  - Tang,MX
AU  - Dunsby,C
AU  - Aljabar,P
AU  - Eckersley,R
DO  - 10.1109/ULTSYM.2017.8091563
PY  - 2017///
SN  - 1948-5719
TI  - Notice of Removal: Automated super-resolution image processing in ultrasound using machine learning
UR  - http://dx.doi.org/10.1109/ULTSYM.2017.8091563
ER  -
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