Welcome to the Computational Imaging Group!

The Computational Imaging Group (CIG) at Washington University in St. Louis pursues research on the development of advanced algorithms and mathematical tools for biomedical and industrial imaging.

Over the past two decades, there has been a significant paradigm shift in imaging research. Increasingly, researchers are coming to consensus that computation is a cornerstone of future imaging systems. Our research focuses on that aspect of imaging by developing computational methods that enable new imaging capabilities. Specifically, we aim to leverage the advances in optimization, machine learning, and statistical inference to design new models, algorithms, and systems for imaging. Our work is inherently interdisciplinary and has broad applications in biomedical imaging, defense, physical science, and industrial inspection. We extensively collaborate with researchers in optics, medicine, biology, as well as with those working in industry.



[CIG-2018]

Latest News

September 2018: Ulugbek and Adam Scholefield are organizing a special session on “Recent Advances in Signal Processing for Large-Scale Computational Imaging” at IEEE ICASSP 2019.

September 2018: Our manuscript Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging was accepted to IEEE Transactions on Computational Imaging.

September 2018: New arXiv manuscript An Online Plug-and-Play Algorithm for Regularized Image Reconstruction.

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