French
English
CREATIS laboratory (Lyon, France) opens a postdoctoral position funded for two years.
Keywords Single-pixel imaging, compressive video imaging, instrumentation development.
Background
Our group is particularly interested in developing computational imaging systems that combine advances in hardware and software [1, 2, 3]. Single-pixel imaging is a paradigm that enables two-dimensional imaging from a point detector. It leads to high-performance optical imaging systems (e.g., hyperspectral and/or time-of-flight measurements) at very low cost. Single-pixel cameras comprise a single point detector that is coupled with a spatial light modulator. By performing a sequence of optical measurements for different modulation patterns, it is possible to recover the image of the observed scene provided that ad-hoc reconstruction algorithms are implemented [4]. Successful applications of single-pixel imaging include three-dimensional imaging [5], hyperspectral imaging [6], fluorescence microscopy [7], infrared imaging [8] and terahertz imaging [9]. Compressive imaging also generated the interest of large private companies [10].
Project
Fluorescence-guided surgery is an imaging technique that helps surgeons to perform safer and less invasive surgery. While quantitative fluorescence imaging requires to exploit the full spectrum, there are no traditional hyperspectral cameras with sufficient spectral resolution. Therefore, current solutions are based on point measurements only. A single-pixel camera could bring high spectral resolution together with high spatial resolution. However, current single-pixel cameras are two slow to operate in real time. In this project, we aim to develop a fast single-pixel camera for fluorescence guide surgery.
Context
The position is funded by the French National Research Agency (ANR) in the framework of the ARMONI young researcher (JCJC) project. The successful candidate will have access to an existing prototype to test his ideas. He will work in close collaboration with a PhD student.
Skills
We are looking for an enthusiastic and experienced candidate with a background in optical instrumentation development and a strong interest in biomedimedical imaging. Good knowledge of signal processing and/or machine leaning would be a plus. Strong programming skills in Labview and Python are required.
How to apply?
Send CV, motivation letter, and academic records to
nicolas.ducros@creatis.insa-lyon.fr, bruno.montcel@creatis.insa-lyon.fr, and peyrin@esrf.fr
Salary
€2200 net per month (this is a minimum, salary depends on experience and is negotiable)
References
[0] Our single-pixel imaging webpage https://www.creatis.insa-lyon.fr/~ducros/WebPage/single_pixel_imaging.html
[1] Rousset, F. et al. Adaptive basis scan by wavelet prediction for single-pixel imaging. IEEE Transactions on Computational Imaging 3, 36–46 (2017).
[2] Rousset, F. et al. A semi nonnegative matrix factorization tech- nique for pattern generalization in single-pixel imaging. IEEE Transactions on Computational Imaging 4, 284–294 (2018).
[3] Rousset, F. et al. Time-resolved multispectral imaging based on an adaptive single-pixel camera. Opt. Express 26, 10550– 10558 (2018).
[4] Candes, E. J. & Wakin, M. B. An introduction to compressive sampling. IEEE Signal Processing Magazine 25, 21–30 (2008).
[5] Sun, M.-J. et al. Single-pixel three-dimensional imaging with time-based depth resolution. Nature Communications 7, 12010 (2016).
[6] Pian, Q. et al. Compressive hyperspectral time-resolved wide-field fluorescence lifetime imaging. Nature photonics 11, 411– 414 (2017).
[7] Studer, V. et al. Compressive fluorescence microscopy for biological and hyperspectral imaging. Proceedings of the Na- tional Academy of Sciences of the United States of America 109, E1679–E1687 (2012).
[8] Radwell, N. et al. Single-pixel infrared and visible microscope. Optica 1, 285–289 (2014).
[9] Watts, C. M. et al. Terahertz compressive imaging with meta- material spatial light modulators. Nature Photonics 8, 605– 609 (2014).
[10] Miao, X. & Amirparviz, B. Single pixel camera. Google LLC, US Patent US9071739B2 (2015).