Laurène Donati

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GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems

Michaël Unser, Laurène Donati, Michael Thompson McCann, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez

We present a unifying framework for the development of state-of-the-art reconstruction algorithms in computational optics with a clear separation between the physical (forward model) and signal-related (regularization, incorporation of prior constraints) a ...

OSA2017

DeconvolutionLab2: An Open-Source Software for Deconvolution Microscopy

Michaël Unser, Daniel Sage, Cédric René Jean Vonesch, Laurène Donati, Ferréol Arnaud Marie Soulez, Denis Fortun, Guillaume Schmit

Images in fluorescence microscopy are inherently blurred due to the limit of diffraction of light. The purpose of deconvolution microscopy is to compensate numerically for this degradation. Deconvolution is widely used to restore fine details of 3D biologi ...

2017

Compressed sensing for STEM tomography

Michaël Unser, Masih Nilchian, Laurène Donati

A central challenge in scanning transmission electron microscopy (STEM) is to reduce the electron radiation dosage required for accurate imaging of 3D biological nano-structures. Methods that permit tomographic reconstruction from a reduced number of STEM ...

2017

Compressed Sensing for Dose Reduction in STEM Tomography

Michaël Unser, Laurène Donati, Masih Nilchian

We designed a complete acquisition-reconstruction framework to reduce the radiation dosage in 3D scanning transmission electron microscopy (STEM). Projection measurements are acquired by randomly scanning a subset of pixels at every tilt-view (i.e., random ...

IEEE2017

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