Seminar Series in Imaging – 19 September 2019

Imaging: From Compressed Sensing To Deep Learning

 

Venue: SV1717 

Free registration: Doodle

Chair: Prof. Michael Unser, Biomedical Imaging Group – EPFL


Program 

16:00 – Prof. Yonina Eldar 

Weizmann Institute of Science, Israel 

Imaging: From Compressed Sensing to Deep Learning 

The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal and image processing. However, in many modern applications, the signal bandwidths have increased tremendously, while the acquisition capabilities have not scaled sufficiently fast. Consequently, conversion to digital has become a serious bottleneck.  Furthermore, the resulting high rate digital data requires storage, communication and processing at very high rates which is computationally expensive and requires large amounts of power.  In the context of medical imaging sampling at high rates often translates to high radiation dosages, increased scanning times, bulky medical devices, and limited resolution.

In this talk, we present a framework for sampling and processing a wide class of wideband analog signals at rates far below Nyquist by exploiting signal structure and the processing task and show several demos of real-time sub-Nyquist prototypes. We consider applications of these ideas to a variety of problems in imaging including fast and quantitative MRI, wireless ultrasound, fast Doppler imaging, and correlation based super-resolution in microscopy and ultrasound which combines high spatial resolution with short integration time. We then show how the ideas of exploiting the task, structure and model can be used to develop interpretable model-based deep learning methods that can adapt to existing structure and are trained from small amounts of data. These networks achieve a more favorable trade-off between increase in parameters and data and improvement in performance while remaining interpretable.

16:45 – Coffee break

17:00 – Short Presentations by Group Leaders (Chair: Prof. Christophe Moser)

To promote cross-fertilization in imaging, group leaders are invited to showcase their research activities with short presentations during the [email protected] seminars. 

Prof. Aleksandra Radenovic, Laboratory of Nanoscale Biology (LBEN)

Prof. Volkan Cevher, Laboratory for Information and Inference Systems (LIONS)

Prof. Michael Liebling, Computational Bioimaging Group (CBG-IDIAP)

Prof. Suliana Manley, Laboratory of Experimental Biophysics (LEB)

Prof. Demetri Psaltis, Optics Laboratory (LO)

17:30 – Apéritif