Image Reconstruction in Third-Harmonic Generation Microscopy
Type: Master (semester project) Supervisor: Vasiliki Stergiopoulou (LCAV, Galatea) Contact: [email protected] Project Context: Third harmonic generation (THG) microscopy is a non-fluorescent multiphoton technique that enables three-dimensional imaging of refractive index differences. To obtain an accurate reconstruction, we tackle an optimization problem, minimizing a weighted combination of two terms. The first term ensures that reconstructions align (…)
Domain-Decomposition Deconvolution for Very Large 3D Microscopy Images
Contact: Dr. J. Rué Queralt, Dr. D. Sage (EPFL Center for Imaging), Dr. V. Stergiopoulou (LCAV, Galatea), Dr. E. Soubies (IRIT Toulouse) Synopsis: Modern fluorescent microscopes are capable of acquiring high-resolution 3D images of an entire specimen (e.g. light sheet microscopy). This generates very large, voluminous images that are difficult to process on a computer (…)
Local maxima estimation of gradients to speed up a convex optimization algorithm
Contact: Adrian Jarret (LCAV) Synopsis: Discover the Frank-Wolfe algorithm for convex optimization with sparse priors, contribute to the development of a fast polyatomic variant, find local maxima on a 2D image, simulate image reconstruction for radio astronomy. Level: Bachelor – Master (semester project) Sections: IC Description: The LASSO problem [1] is a convex optimization problem (…)
Fabricating optics for lensless imaging (Assistant Etudiant, Summer 2023)
Keywords: Computational imaging, hardware prototyping, 3D printing. GitHub project page: https://github.com/LCAV/LenslessPiCam Medium blog posts: https://go.epfl.ch/lenslesspicam Contact: Eric Bezzam Levels: Bachelor / Master Sections: IC, EE, ME, MT Description: Lensless imaging throws away centuries-old notions of taking pictures. By shifting the image formation from the lens to the digital post-processing, the constraints imposed by lenses (e.g. focusing (…)
Signal reconstruction using sparsity-promoting penalty over a redundant dictionary of wavelets
Contact: Adrian Jarret (LCAV) Synopsis: Comparison of analysis and synthesis formulations, solution of analysis formulation using cycle spinning with different wavelet basis, solution of synthesis formulation with adjoint of penalty operator and proximal gradient method, extension to weighted penalty. Level: Master (5-6 months) Sections: IC Description: Wavelet bases are known to produce sparse representations of (…)
Composite Reconstruction of Images in Radio Astronomy
Contact: Adrian Jarret (LCAV) Synopsis: Reconstruction of radio astronomy images as a sum of components from two dictionaries, using linear inverse problems with a composite penalty. Level: Master Sections: IC Description: One of the main challenges in radio astronomy is to reconstruct an image of the sky from noisy interferometric measurements of the radio waves (…)
Reconstruction of Sparse Images with a Variational Approach: a Numerical Comparison of LASSO Solvers
Contact: Adrian Jarret (LCAV) Synopsis: Comparison of different LASSO solvers for the reconstruction of sparse signals in simulated contexts inspired from radio astronomy. Level: Bachelor Sections: IC Description: The LASSO problem is an optimization problem broadly used nowadays to reconstruct sparse solutions to linear inverse problems. One of the most popular solvers for numerical applications (…)
Statistical Analysis of Sparse and Piecewise-linear Regression
Contact: Julien Fageot Levels: Master semester project, or Master thesis Sections: IC, EE, SMA Recent works have investigated the possibility of recovering continuous-domain signals from their discrete observations using sparsity-promoting variational methods. The resulting interpolation problem is then cast as a functional sparse inverse problem. In this project, we focus on piecewise-linear continuous-domain reconstruction, which is achieved by (…)
Analyze sparse and smooth signal components with optimization problems
Contact: Adrian Jarret (LCAV) Synopsis: Solving Inverse problem for Sparse-plus-Smooth composite signals Levels: Bachelor, Master Sections: IC Description: When performing experiences, researchers are rarely able to directly measure the data of interest, but rather side effects of the phenomenon, referred to as indirect measurements. The stereotypical examples are tomography (MRI imaging) that uses magnetic fields (…)
Scientific Computing Python Developer (Summer Student Assistant)
Supervisor: Matthieu Simeoni (LCAV) Contact: Matthieu Simeoni ([email protected]) Keywords: scientific computing, computational imaging, GPU computing, inverse problems, convex optimisation Description: Full-time summer student assistantship (July 1st to August 31st) as a Python developer. The student (which must be currently studying at EPFL) will be expected to help with the development of (…)