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12 month Post-doc offer Diffuse Optical Tomography in the SWIR

13 Septembre 2023

Catégorie : Post-doctorant

New algorithmic approaches for Fluorescence Diffuse Optical Tomography in the second biological window (SWIR)

Principal Investigator: Dr Anabela Da Silva, PhD (Senior researcher @ CNRS)

Email :

Research team: DiMABio, Institut Fresnel/CERIMED

Address: Institut Fresnel, Av Escadrille Normandie-Niémen, 13397 Marseille Cedex 20, France

Work carried out in partnership with KAER LABS (Nantes) and Institut pour l'Avancée des Biosciences (IAB, Grenoble)

Funding : Fondation AMIDEX, 12 months

Key words: Inverse problems, Diffuse Optical Tomography (DOT), Radiative Transfer Equation, Small Animal Imaging, Fluorescence in NIR I (Near InfraRed 600-900 nm), NIR II or SWIR (Short Wave InfraRed 900-1700 nm)

We are offering a 12-month post-doc position (AMIDEX funding) in the field of modeling and image processing for optical biomedical imaging. The work will take place at the Institut Fresnel in Marseille, within the DiMABio team (, as part of a collaboration with the Optimal platform of the Institut pour l'Avancée des Biosciences (IAB) in Grenoble (, and Kaer Labs in Nantes (, for the development of a fluorescence tomography system in the second biological window NIR II or SWIR (Short Wave InfraRed 900-1700 nm). The candidate's mission will be to develop 3D reconstruction algorithms for the localization of fluorescence sources detectable in vivo in mouse models.


Scientific background and objective

Optical biomedical imaging is a fast-growing non-conventional imaging technique. Fluorescence Diffuse Optical Tomography (FDOT) is a non-invasive imaging technique capable of detecting and quantifying localized fluorescent sources in deep organs of living organisms (rodents). Conventional FDOT uses non-ionizing radiation in the visible to near infrared spectral range (

More specifically, the project concerns the development of a reconstruction algorithm using fluorescence images from a small animal fluorescence imaging system similar to that described in publications [1-4], but in the "NIR-II" or "SWIR" spectral range (1000 to 1700 nm), co-developed by Kaer Labs, IAB and Institut Fresnel. This algorithm must: i) be based on the numerical resolution of a light propagation model capable of taking into account the high absorption and scattering levels of biological tissues at these wavelengths (Radiative Transfer Equation); ii) take into account the technical characteristics of the instruments (acquisition geometry, type of sensor and source, fluorescence filter, etc.). The candidate will be able to draw on preliminary work and numerical tools already implemented (work started two years ago), as well as on the expertise and infrastructures of the teams.

The algorithm developed will then be applied to the detection of new organic (cyanine derivatives) and inorganic (gold nanoclusters) SWIR contrast agents [5] with cancer-specific motif targeting functions. The in vivo biological behavior of these contrast agents will be evaluated after administration in mice. First, their in vivo biodistribution will be assessed in healthy mice, then their tumor-targeting capacity will be evaluated in mouse models of cancer [6].

The work will thus comprise the following 3 phases:

- Implementation of numerical tools, in particular the development of a Radiation Transfer Equation solver using Monte Carlo simulations or the Finite Element Method, optimized for coupling to a reconstruction algorithm.

- Experimental validation on phantoms

- Pre-clinical study

Candidate profile As the models and methods for solving the equations are known, this project requires strong skills in numerical modeling (solving the Radiation Transfer Equation using numerical or stochastic methods), applied mathematics and information processing.The multi-disciplinary context, at the interface between physics and biomedical research, calls for an independent and open-minded candidate, capable of taking experimental and biological constraints into account.The main skills required for the project concern knowledge of physical models, scientific computing (numerical analysis for PDEs, optimization, algorithms, Deep Learning and HPC), signal and image processing.

No specific chemistry or biology skills are required, but candidates should be open to the prospect of contributing to these experiments. Programming languages: C/C++, Python, MATLAB, VTK, CUDA.

Candidates are requested to submit:

- a cover letter explaining shortly the relevance and motivation of the application

- a detailed CV

- 2 major publications

- 2 academic references

The application should be addressed to


[1] L. Hervé, A. Koenig, A. Da Silva, M. Berger, J. Boutet, J.M. Dinten, P. Peltié, P. Rizo, NonContact Fluorescence Diffuse Optical Tomography of Heterogeneous Media, Applied Optics 46(22), 4896- 4906, 2007.

[2] L. Hervé, A. Da Silva, A. Koenig, J.-M. Dinten, J. Boutet, M. Berger, I. Texier, P. Peltié and P. Rizo, Fluorescence tomography enhanced by taking into account the medium heterogeneity, Nuclear Instruments and Methods in Physics Research A, 571 (1-2) 60–63, 2007.

[3] Anne Koenig, Lionel Hervé, Véronique Josserand, Michel Berger, Jérôme Boutet, Anabela Da Silva, Jean-Marc Dinten, Philippe Peltié, Jean-Luc Coll, Philippe Rizo, In vivo mice lungs tumors follow-up with fluorescence diffuse optical tomography, Journal of Biomedical Optics 13(1), 011008 2008.

[4] Koenig A, Hervé L, Gonon G, Josserand V, Berger M, Dinten JM, Boutet J, Peltié P, Coll JL, Rizo P. Fluorescence diffuse optical tomography for free-space and multi-fluorophore studies. J Biomed Opt. 2010 Jan-Feb;15(1):016016. doi: 10.1117/1.3309738. PMID: 20210462.

[5] Z. Yu, B. Musnier, K. D. Wegner, M. Henry, B. Chovelon, A. Desroches-Castan, A. Fertin, U. Resch-Genger, S. Bailly, J.-L. Coll, Y. Usson, V. Josserand, X. Le Guével, ACS Nano 2020, 14, 4973-4981.

[6] C. Bouclier, M. Simon, G. Laconde, M. Pellerano, S. Diot, S. Lantuejoul, B. Busser, L. Vanwonterghem, J. Vollaire, V. Josserand, B. Legrand, J. L. Coll, M. Amblard, A. Hurbin, M. C. Morris, Theranostics 2020, 10, 2008-2028.