Monday, December 11, 2017

Compressive 3D ultrasound imaging using a single sensor

Pieter just sent me the following:

Dear Igor,
I have been following your blog for a couple of years now as it served as an excellent introduction to the field of CS and an active source of inspiration for new ideas. Many thanks for that! It was a quite a journey, but finally we managed to get some form of CS working in the field of ultrasound imaging. In our paper (online today:http://advances.sciencemag.org/content/3/12/e1701423, and a short video about this work: https://www.youtube.com/watch?v=whbbaF1nT4A ) we show that 3D ultrasound imaging can be done using only one sensor and a simple coding mask. Unfortunately we do not show any phase transition map and there is not much exploitation of sparsity but it does show that hardware prototyping and the utilisation of signal structure in conjunction with linear algebra can reveal powerful, new ways of imaging.
It would mean a lot to me (a long-held dream) if you could mention our paper on your blog some time.


Kind regards,
Pieter Kruizinga
Awesome Pieter !



Compressive 3D ultrasound imaging using a single sensor by Pieter Kruizinga, Pim van der Meulen, Andrejs Fedjajevs, Frits Mastik, Geert Springeling, Nico de Jong, Johannes G. Bosch and Geert Leus

Three-dimensional ultrasound is a powerful imaging technique, but it requires thousands of sensors and complex hardware. Very recently, the discovery of compressive sensing has shown that the signal structure can be exploited to reduce the burden posed by traditional sensing requirements. In this spirit, we have designed a simple ultrasound imaging device that can perform three-dimensional imaging using just a single ultrasound sensor. Our device makes a compressed measurement of the spatial ultrasound field using a plastic aperture mask placed in front of the ultrasound sensor. The aperture mask ensures that every pixel in the image is uniquely identifiable in the compressed measurement. We demonstrate that this device can successfully image two structured objects placed in water. The need for just one sensor instead of thousands paves the way for cheaper, faster, simpler, and smaller sensing devices and possible new clinical applications. 




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