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Biomedical Imaging Group
Laboratoire d'imagerie biomédicale (LIB)

Fractional Splines


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The Wavelet Digest
The electronic newsletter of the wavelet community is hosted by the EPFL.

Freely available software and computer sessions for teaching and programming image processing in Java.



Prof. Michael Unser


Claudia Gasparini
Tel: +41 21 693 11 85
Fax: +41 21 693 68 10

Mailing Address

BM 4.134 (Bâtiment BM)
Station 17
CH-1015 Lausanne VD





Institute of Microengineering


School of Engineering


Center for Imaging in Bio-Medecine


Swiss Federal Institute of Technology Lausanne


The biomedical imaging group pursues research on the development of new algorithms and mathematical tools for the advanced processing of medical and biological images. Topics of interest are image reconstruction, multi-modal imaging, image analysis and visualization. Research efforts are taking place at two complementary levels:

NEWS rss

May 2019
Shayan Aziznejad won an ICASSP 2019 Best Student Paper Award for his work on Deep Spline Networks with Control of Lipschitz Regularity.

April 2019
Thanh-an Pham won the ISBI 2019 Best Paper Award (runner-up) for his work on Closed-Form Expression of the Fourier Ring Correction for Single Molecule Localization Microscopy

October 2018
Julien Fageot is the recipient of the EPFL Doctorate Award 2018 for his thesis entitled "Gaussian versus Sparse Stochastic Processes: Construction, Regularity, Compressibility ". Congratulations for this truly exceptional achievement !

June 2018
Virginie Uhlmann received EPFL's Best Doctoral Thesis Award in Electrical Engineering 2018 for her thesis entitled "Landmark Active Contours for Bioimage Analysis : A Tale of Points and Curves". Congratulations to Virginie for her excellent work!

May 2018
The Startup Mirrakoi, an offspring of BIG, achieved the 3rd stage of Venture Kick and won the CHF 130'000 award. Bravo for being in the top of Swiss innovation !!!
More info ...

March 2018
Michael Unser is the recipient of the 2018 Technical Achievement Award "for fundamental contributions to the theory of sparse stochastic processes and sparsity-based signal processing" from the European Association for Signal and Image Processing.
More info ...

March 2018
Virginie Uhlmann has been appointed as a research group leader at EMBL-EBI (European Bioinformatics Institute) at Cambridge, UK. Congrats!
Interview of Virginie

December 2017
Stamatis, Aurélien and Michael are the happy recipients of the 2017 SPS Best Paper Award from the IEEE Signal Processing Society for their paper Stamatis Lefkimmiatis, Aurélien Bourquard, and Michael Unser “Hessian-Based Norm Regularization for Image Restoration With Biomedical Applications” IEEE Transactions on Image Processing, Volume 21, No. 3, March 2012.

June 2017
Ulugbek Kamilov (BIG alumni) accepted an Assistant Professorship (with tenure track) at Washington University in St. Louis. Good luck and welcome to academia !!!


Twenty Years of Biomedical Imaging and Splines
Invited speakers: Michael Unser, Stephane Mallat, Christophe Rabut, Akram Aldroubi, Thierry Blu, Erik Meijering, Costanza Conti, and Dimitri Van De Ville

Program: EPFL, Friday March 23, 2018

Carl de Boor Celebration

Newsletter of the Institute for Mathematical Sciences, National University of Singapore, Jan-June 2018, issue 31, p 5.

Workshop on Spline Approximation and its Applications on Carl de Boor’s 80th Birthday

In the late 60s, Carl de Boor embarked on an ambitious program to develop a mathematical foundation for spline functions that would be friendly to computation. The cornerstone of this development was his work on Schoenberg’s B-splines – splines with minimal support, and it became clear that spline functions can provide efficient representations of functions, curves, surfaces and digital data. Today, spline functions are widely used in areas such as automotive design, computer aided geometric design, imaging science and data science

Cell detection by functional inverse diffusion and non-negative group sparsity
Pol del Aguila Pla
Can neural networks always be trained? On the boundaries of deep learning
Matt J. Colbrook
Measure Digital, Reconstruct Analog
Julien Fageot
More info ...