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Compressed Sensing for Dose Reduction in STEM Tomography11 Apr 2017

Laurène Donati
EPFL STI LIB

Chasing Mycobacteria10 Apr 2017

Virginie Uhlmann
EPFL STI LIB

Multifractal analysis for signal and image classification23 Mar 2017

Stéphane Jaffard
UPEC

3D SIM and measurements time-reallocation for scanning based systems: Introduction and preliminary results on these two problems14 Mar 2017

Emmanuel Soubies
EPFL STI LIB

Inverse problems and multimodality for biological imaging28 Feb 2017

Denis Fortun
EPFL STI LIB

RKHS to find the Representer Theorem for regularization operators whose null space is not finite dimensional09 Feb 2017

Harshit Gupta
EPFL STI LIB

A unified reconstruction framework for coherent imaging24 Jan 2017

Ferréol Soulez
EPFL STI LIB

BPConvNet for compressed sensing recovery in bioimaging10 Jan 2017

Kyong Jin
EPFL STI LIB

Steerable template detection based on maximum correlation: preliminary results13 Dec 2016

Adrien Depeursinge
EPFL STI LIB

Opportunities in Computational Imaging for Biomicroscopy06 Dec 2016

Prof. Michael Leibling
Idap Research Institute

A multiple scattering approach to diffraction tomography30 Nov 2016

Luc Zeng
EPFL STI LIB

Learning Optimal Shrinkage Splines for ADMM Algorithms22 Nov 2016

Ha Nguyen
EPFL STI LIB

SIGGRAPH ASIA 201601 Nov 2016

Daniel Schmitter
EPFL STI LIB

Lévy's Persian summers18 Oct 2016

Julien Fageot
EPFL STI LIB

High-quality parallel-ray X-ray CT back projection using optimized interpolation11 Oct 2016

Mike McCann
EPFL STI LIB

Algorithmic Aspects of Compressive Sensing03 Oct 2016

Verner Vlacic
Cambridge University

ICIP 201620 Sep 2016

Anaïs Badoual
EPFL STI LIB

Machine Vision forum in Heidelberg17 Aug 2016

Virginie Uhlmann
EPFL STI LIB

K-space interpolation using CV(complex valued)-CNN & sparse and low-rank model of ALOHA09 Aug 2016

Kyong Jin
EPFL STI LIB

Complete Compressed Sensing Framework for STEM Tomography19 Jul 2016

Laurène Donati
EPFL STI LIB

Trainable shrinkage splines: inverse problems meet deep learning28 Jun 2016

Ha Nguyen
EPFL STI LIB

A reconstruction framework for coherent imaging31 May 2016

Ferréol Soulez
EPFL STI LIB

Shape-Constrained Tracking with Active Contours17 May 2016

Virginie Uhlmann
EPFL STI LIB

Steerable Wavelet Machines (SWM): Learning Moving Frames for Texture Classification / Some results on MA-TIRF reconstruction and exact continuous penalties for l2-l0 minimization03 May 2016

Adrien Depeursinge, Emmanuel Soubies
EPFL STI LIB

Learning-Based approach in Single Molecule localization microscopy19 Apr 2016

Silvia Colabrese
Italian Institute of Technology, Genova, Italy

ISBI 201606 Apr 2016

Michael Unser, Denis Fortun

Title 1: User-Friendly Image-Based Segmentation and Analysis of Chromosomes Presenter: Prof. Unser Abstract 1: We designed two efficient and user-friendly tools for the segmentation and analysis of images containing chromosomes or, more generally, rod-shaped elements that are spread on microscopic slides. The segmentation tool allows to automatically extract the profile of each chromosome and to sort the collection of profiles in a karyotype image. The analysis tool is interactive and allows to extract quantitative measurements and annotate the relative position of the centromere to the chromosome extremities in a fast and reproducible way. The two methods rely on custom variants of parametric active contours. Both have been designed as user-friendly plug-ins for the open-source software ImageJ. Title 2: Isotropic resolution in fluorescence imaging by single particle reconstruction Presenter: Denis Abstract 2: Low axial resolution is a major limitation of fluorescence imaging modalities. We propose a methodology to achieve high isotropic resolution by reconstructingfluorescence volumes from observations of multiple particle replicates with different orientations. The challenge is to conciliate high reconstruction accuracy, requiring a large amount of input 3D data, with computational tractability. We achieve this goal by designing an iterative joint deconvolution and multiview reconstruction algorithm with an efficient augmented-Lagrangian based optimization. The computational cost is limited to only two FFTs per iterations, regardless of the number of input particles. We also adopt the nuclear norm of the Hessian as regularizer to avoid the usual staircase artifacts of the more standard total-variation. Experimental validation on realistic simulated data demonstrate the efficiency and accuracy of our method.

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ICASSP 201615 Mar 2016

Pedram Pad
EPFL STI LIB

Fast 3D Reconstruction Method for Differential Phase Contrast X-ray CT08 Mar 2016

Mike McCann

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Sparsity and the optimality of splines for inverse problems: Deterministic vs. statistical justifications23 Feb 2016

Michael Unser
EPFL STI LIB

Decoding Epileptogenesis: A Dynamical System Approach09 Feb 2016

Prof. Francois Meyer
University of Colorado at Boulder

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