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Annonce

3 septembre 2020

3D reconstruction algorithms for Optical Diffraction Tomography


Catégorie : Post-doctorant


Subject title: 3D reconstruction algorithms for Optical Diffraction Tomography of biological living samples.

Host laboratory: Laboratoire Hubert Curien (LaHC), 18 Rue Pr B. Lauras, 42000 SAINT-ÉTIENNE.

Supervisor: Fabien Momey (fabien.momey@univ-st-etienne.fr).

Keywords: Inverse problems, 3D image reconstruction, tomographic reconstruction, deep learning, numerical modelization, optical diffraction tomography.

Duration: 20 months.

Starting date: as soon as possible.

Salary: ~ 2200 euros/month net (for experience post-PhD <= 3 years).

 

Subject title: 3D reconstruction algorithms for Optical Diffraction Tomography of biological living samples.

Host laboratory: Laboratoire Hubert Curien (LaHC), 18 Rue Pr B. Lauras, 42000 SAINT-ÉTIENNE.

Supervisor: Fabien Momey (fabien.momey@univ-st-etienne.fr).

Keywords: Inverse problems, 3D image reconstruction, tomographic reconstruction, deep learning, numerical modelization, optical diffraction tomography.

Duration: 20 months.

Starting date: as soon as possible.

Salary: ~ 2200 euros/month net (for experience post-PhD <= 3 years).

Context and problematics:

Optical microscopy techniques are among the preferred methods for biological studies, thanks to their unique capability of imaging living specimens in 3-D. Optical diffraction tomography (ODT) or Tomographic Diffractive Microscopy (TDM) is an emergent technique, which permits to image transparent specimens in 3-D [1], without preparation or staining. It uses digital holography microscopy acquisitions in "tomographic" mode, performed by either specimen rotation or illumination scanning. It allows for the measurement of the specimen index of refraction distribution in 3-D, and with a resolution twice better than conventional microscopy.

IRIMAS (Mulhouse) has built such a microscope [2,3], which has demonstrated its ability to reach an isotropic 3-D resolution in the 100 nm range [4]. The state-of-art 3D reconstruction principle consists in a 3D mapping of the object of interest's frequencies space, as in conventional X-ray tomography (Fourier slice theorem). The more an isotropic coverage of the angular hologram acquisitions, the more the 3D frequency spectrum of the object can be fulfilled.

The ANR HORUS project [https://anr.fr/Projet-ANR-18-CE45-0010], involving a collaboration between the IRIMAS laboratory (Mulhouse), the Hubert Curien laboratory (Saint-Étienne) and the IGBMC institute (Strasbourg), and funded by the Agence Nationale de la Recherche (ANR), aims at improving this imaging technique in terms of instrumentation and reconstruction algorithms. The goal is to adapt the technique to the imaging of living samples. The goal of IGBMC team is to benefit from a complementary imaging technique - combined with fluorescence microscopy - to study the mechanisms of the HIV virus infection process. The expertise in optical instrumentation is carried out by IRIMAS, while The Hubert Curien laboratory brings its expertise in inverse problems dedicated to image reconstruction in microscopy and tomography.

Subject of the Post-Doc : 3D reconstruction algorithms

The Post-Doc is inserted in the improving task of 3D reconstruction algorithms, which is an active research area. The recruited candidate will have to improve or overcome already existing reconstruction methods, mostly based on the direct inversion of first Born approximation (the above mentioned 3D frequency spectrum mapping algorithm) [2,5,6].

The HORUS project particularely aims at exploring regularized inverse problems approaches to perform the reconstruction [7,8,9,10,11], with the ambitious challenge of reaching high spatial and temporal resolution to make possible to image microscopic living samples. Jointly exploring deep learning based methods for the reconstruction task [12] can also be an interesting field of research following the recruited candidate skills. In this context, another concern is the numerical modelization of the image formation process, which deals with 3D diffraction physics [6,13,14,15], and is a correlated task of the HORUS project.

The Hubert Curien Laboratory team is specialized in image reconstruction based on inverse problems strategies, applied to digital holographic microscopy [16]. Already existing tools and algorithms (models, optimization methods, regularizations) will be available to the candidate, that have been implemented and used in the team for image reconstruction of hologram data.

High interactions and transfers of knowledge will occur with the IRIMAS laboratory. A PhD thesis at IRIMAS, mixing instrumentation and image processing, will also start soon, and will be highy interconnected with this Post-Doc.

Required skills: signal and image processing, 2D/3D image reconstruction (digital holography, tomography) and/or inverse problems (modelization, regularization, numerical optimization). A background in deep learning approaches applied to image reconstruction could be also of interest to be combined to the targeted regularized inversion methods.

References:

[1] O. Haeberlé, K. Belkebir, H. Giovaninni, and A. Sentenac. Tomographic diffractive microscopy: basics, techniques and perspectives. Journal of Modern Optics, 57(9):686–699, May 2010.
[2] Matthieu Debailleul, Bertrand Simon, Vincent Georges, Olivier Haeberlé, and Vincent Lauer. Holographic microscopy and diffractive microtomography of transparent samples. Measurement Science and Technology, 19(7):074009, 2008.
[3] B. Simon, M. Debailleul, V. Georges, V. Lauer, and O. Haeberlé. Tomographic diffractive microscopy of transparent samples. The European Physical Journal - Applied Physics, 44(1):29–35, October 2008.
[4] Bertrand Simon, Matthieu Debailleul, Mounir Houkal, Carole Ecoffet, Jonathan Bailleul, Joël Lambert, Arnaud Spangenberg, Hui Liu, Olivier Soppera, and Olivier Haeberlé. Tomographic diffractive microscopy with isotropic resolution. Optica, 4(4):460–463, April 2017.
[5] Emil Wolf. Three-dimensional structure determination of semi-transparent objects from holographic data. Optics
Communications, 1(4):153–156, September 1969.
[6] J. Bailleul, B. Simon, M. Debailleul, L. Foucault, N. Verrier, and O. Haeberlé. Tomographic diffractive microscopy: Towards high-resolution 3-D real-time data acquisition, image reconstruction and
display of unlabeled samples.
Optics Communications, 422:28–37, September 2018.
[7] Yongjin Sung, Wonshik Choi, Christopher Fang-Yen, Kamran Badizadegan, Ramachandra R. Dasari, and Michael S. Feld. Optical diffraction tomography for high resolution live cell imaging. Optics Express, 17(1):266, January 2009.
[8] Micah H. Jenkins and Thomas K. Gaylord. Three-dimensional quantitative phase imaging via tomographic deconvolution phase microscopy. Applied Optics, 54(31):9213–9227, November 2015.
[9] Anthony Berdeu, Fabien Momey, Bastien Laperrousaz, Thomas Bordy, Xavier Gidrol, Jean-Marc Dinten, Nathalie Picollet-D’hahan, and Cédric Allier. Comparative study of fully three-dimensional reconstruction algorithms for lens-free microscopy. Applied Optics, 56(13):3939–3951, May 2017.
[10] H. Y. Liu, U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos. Compressive imaging with iterative forward models. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 6025–6029, March 2017.
[11] Thanh-An Pham, Emmanuel Soubies, Alexandre Goy, Joowon Lim, Ferréol Soulez, Demetri Psaltis, and Michael Unser. Versatile reconstruction framework for diffraction tomography with intensity measurements and multiple scattering. Optics Express, 26(3):2749–2763, February 2018.
[12] Fangshu Yang, Fangshu Yang, Thanh-an Pham, Harshit Gupta, Michael Unser, and Jianwei Ma. Dee -learning projector for optical diffraction tomography. Optics Express, 28(3):3905–3921, February 2020. Publisher: Optical Society of America.
[13] U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis. Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization. IEEE Transactions on Computational Imaging, 2(1):59–70, March 2016.
[14] Emmanuel Soubies, Thanh-An Pham, and Michael Unser. Efficient inversion of multiple-scattering model for optical diffraction tomography. Optics Express, 25(18):21786–21800, September 2017.
[15] H. Y. Liu, D. Liu, H. Mansour, P. T. Boufounos, L. Waller, and U. S. Kamilov. SEAGLE: Sparsity Driven Image Reconstruction under Multiple Scattering. IEEE Transactions on Computational Imaging, PP(99):1–1, 2017.
[16] Fabien Momey, Loı̈c Denis, Thomas Olivier, and Corinne Fournier. From Fienup’s phase retrieval techniques to regularized inversion for in-line holography: tutorial. JOSA A, 36(12):D62–D80, December 2019.

 

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