Younes Farouj

Intro

I'm currently a postdoctoral researcher with Prof. Ruben Portugues studying motor behavior in zebrafish using light microscopy.

My research interests also include wavelets, anisotropic analysis and regularization, optimization, nonparametric/adaptive/data-driven estimation and their applications in bio-medical signal and image processing, in particular functional imaging of the brain.

I prepared my Ph.D. degree at the CREATIS Lab, affiliated to the INSA de Lyon, between 2013 and 2016 (thesis manuscript: english, french, slides). During this period, I was also a teaching assistant at the Pôle de Mathématiques affiliated to the same institute.

Before joining TUM in June 2021 as a postdoc, I worked at the MIPLAB within the EPFL. Before that, I spent two months at SAINBIOSE ( École des Mines - Saint-Étienne) as research assistant.

Before starting my Ph.D thesis in Lyon, I was trained at the University of Toulouse where I obtained a Master degree in Applied Mathematics (2012) then a Master degree in Mathematical Engineering - Image Processing (2013).

A (probably) updated version of my resumé can be found here.

Resume

I prepared my Ph.D. degree at the CREATIS Lab, affiliated to the INSA de Lyon, between 2013 and 2016 (thesis manuscript: english, french, slides). During this period, I was also a teaching assistant at the Pôle de Mathématiques affiliated to the same institute.

Before joining MIPLAB in January 2017 as a post-doc, I spent two months at SAINBIOSE ( École des Mines - Saint-Étienne) as an R&D engineer.

Before starting my Ph.D thesis in Lyon, I was trained at the University of Toulouse where I obtained a Master degree in Applied Mathematics (2012) then a Master degree in Mathematical Engineering - Image Processing (2013).

Publications

Here is a list of my publications sorted by date.

2021

D. Van De Ville, Y. Farouj, M.G. Preti, R. Liégeois & E. Amico. When makes you unique: Temporality of the human brain fingerprint. Science Advances. 2021, VOL. 7, NO. 42. (doi).

V. Siffredi, Y. Farouj, A. Tarun, V. Anderson, A.G. Wood, A. McIlroy, R.J. Leventer, M. Spencer-Smith & D. Van De Ville. Large-scale functional network dynamics in human callosal agenesis: increased subcortical involvement and preserved laterality.. NeuroImage. 2021, vol. 243, p. 118471. (doi).

2020

Y. Farouj, F.I. Karahanoglu & D. Van De Ville. Deconvolution of Sustained Neural Activity from Large-Scale Calcium Imaging Data. IEEE Transactions on Medical Imaging. vol. 39, no. 4, pp. 1094-1103, April 2020 (doi, pdf, Supplementary).

2019

Y. Farouj, F.I. Karahanoğlu & D. Van De Ville. BOLD Signal Deconvolution Under Uncertain Hemodynamics: A Semi-Blind Approach. Proceedings of the 16th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'19), pp. 1792-1796. (doi, pdf)

T.A.W. Bolton, Y. Farouj, M. Inan & D. Van De Ville. Structurally-Informed Deconvolution of Functional Magnetic Resonance Imaging Data. Proceedings of the 16th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'19), pp. 1545-1549. (doi, pdf)

2018

T. Bolton, Y. Farouj, S. Obertino & D. Van De Ville. Graph Slepians to Strike a Balance Between Local and Global Network Interactions: Application to Functional Brain Imaging. Proceedings of the 15th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'18), pp. 1239-1243.(doi, pdf)

F.I. Karahanoğlu, C. Piguet, Y. Farouj, P. Vuilleumier & D. Van De Ville. Quantification of Resting-State fMRI Networks Driven by Hemodynamically Informed Spatiotemporal Regularization. Proceedings of the Fifty-Second Asilomar Conference on Signals, Systems and Computers, pp. 363-367. (doi, pdf)

Y. Farouj, L. Navarro,J.-M. Freyermuth, M. Clausel, and P. Delachartre. Ultrasound Spatio- temporal Despeckling via Kronecker Wavelet-Fisz Thresholding. Signal, Image and Video Processing, 2018, vol. 12, no 6, p. 1125-1132. (doi, pdf)

2017

Younes Farouj, F.I. Karahanoğlu, and D. Van De Ville. Regularized spatiotemporal deconvolution of fMRI data using gray-matter constrained total variation. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI 2017), pp. 472-475, 2017. (doi, pdf)

Y. Farouj, J.-M. Freyermuth, L. Navarro, M. Clausel, and P. Delachartre. Hyperbolic Wavelet-Fisz denoising for a model arising in Ultrasound Imaging. IEEE Transactions on Computational Imaging, vol. 3, no. 1, pp. 1–10, 2017. (doi, ps, pdf)

2015

Y. Farouj, L. Navarro, M. Clausel, and P. Delachartre, Débruitage de séquences d’images dynamiques par ondelettes espace-temps hyperboliques. Gretsi 2015. (pdf)

2014

Y. Farouj, L. Wang, P. Clarysse, L. Navarro, M. Clausel, and P. Delachartre, Cardiac Motion Analysis using wavelet projections from Tagged MR sequences. In proc. IEEE Int. Conf. on Image Processing (ICIP’14), Paris , pp. 183-193, 2014. (doi, pdf)

Y. Farouj, L. Navarro, M. Clausel, and P. Delachartre, A variational Shearlet-based model for aortic stent detection. In Proc. IEEE Conf. on Signal Processing (ICSP’14), HangZhou, China, pp. 1052-1056, October, 2014 (doi, pdf).

Code

Calcium Deconvolution

Calcium Deconvolution with Spike and Block models following the paper:

Y. Farouj, F.I. Karahanoglu & D. Van De Ville. Deconvolution of Sustained Neural Activity from Large-Scale Calcium Imaging Data. IEEE Transactions on Medical Imaging. In press.
Link to code (Matlab)

Fast fMRI mapping

A tool for Fast fMRI deconvolution: Link to code (Matlab & Python)

Total Activation

Total Activation (TA) on MIPLAB website accompanying the papers:

Younes Farouj, F.I. Karahanoğlu, and D. Van De Ville. Regularized spatiotemporal deconvolution of fMRI data using gray-matter constrained total variation. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI 2017), pp. 472-475, 2017.

F.I. Karahanoğlu, C. Caballero-Gaudes, F. Lazeyras and D. Van De Ville. Total activation: fMRI deconvolution through spatio-temporal regularization. Neuroimage, 73, 121-134, 2013.

The initial TA code was developped by Işık Karahanoğlu and is continiously improved by Daniela Zöller, Thomas Bolton and myself.

US Denoising

A tool for ultrasound spatiotemporal despeckling accompanying the papers:

Y. Farouj, J.-M. Freyermuth, L. Navarro, M. Clausel, and P. Delachartre. Hyperbolic Wavelet-Fisz denoising for a model arising in Ultrasound Imaging. IEEE Transactions on Computational Imaging, vol. 3, no. 1, pp. 1–10, 2017.

Y. Farouj, L. Navarro,J.-M. Freyermuth, M. Clausel, and P. Delachartre. Ultrasound Spatio- temporal Despeckling via Kronecker Wavelet-Fisz Thresholding. Signal, Image and Video Processing, 2018, vol. 12, no 6, p. 1125-1132.

Links

Links to webistes of some of the academics I work(ed) with

Ruben Portugues
Dimitri Van De Ville
Işık Karahanoğlu
Vanessa Siffredi
Laurent Navarro
Marianne Clausel
Philippe Delachartre
Guy Courbebaisse
Jean-Marc Freyermuth

Few talented young researchers I collaborate(d) with

Daniela Zöller
Thomas Bolton

And few talented students I had the chance to supervise

Roser Viñals Terrés (Master Student - EPFL)
Pedro Abranches (Master Student - EPFL)
Mohammad Torabi (Exchange Student - Sharif University, IRAN)

Contact

Address

Institut für Neurowissenschaften
Technische Universität München
CBiedersteiner Str. 29
80802 München, DE

Mail

 younes.farouj'at'tum.de

• Twitter
• GitHub

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