Publications de Virginie Sophie Uhlmann

A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices

Daniel Sage, Virginie Sophie Uhlmann, Laurène Donati

The variety of bioimage data and their quality have dramatically increased over the last decade. In parallel, the number of proposed deep learning (DL) models for their analysis grows by the day. Yet, the adequate reuse of published tools by practitioners ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Dictionary Learning for Two-Dimensional Kendall Shapes

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot, Anna You-Lai Song

We propose a novel sparse dictionary learning method for planar shapes in the sense of Kendall, namely configurations of landmarks in the plane considered up to similitudes. Our shape dictionary method provides a good trade-off between algorithmic simplici ...

SIAM PUBLICATIONS2020

Gaussian and sparse processes are limits of generalized Poisson processes

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot

The theory of sparse stochastic processes offers a broad class of statistical models to study signals, far beyond the more classical class of Gaussian processes. In this framework, signals are represented as realizations of random processes that are soluti ...

2020

Support and approximation properties of Hermite splines

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot, Shayan Aziznejad

In this paper, we formally investigate two mathematical aspects of Hermite splines that are relevant to practical applications. We first demonstrate that Hermite splines are maximally localized, in the sense that the size of their support is minimal among ...

2020

Multimodal imaging and high-throughput image-processing for drug screening on living organisms on-chip

Martinus Gijs, Michaël Unser, Virginie Sophie Uhlmann, Johan Auwerx, Matteo Cornaglia, Laurent Mouchiroud, Daniel Migliozzi

A major step for the validation of medical drugs is the screening on whole organisms, which gives the systemic information that is missing when using cellular models. Caenorhabditis elegans is a soil worm that catches the interest of researchers who study ...

SPIE Society of Photo-optical Instrumentation Engineers2019

Supervised learning to quantify amyloidosis in whole brains of an Alzheimer's disease mouse model acquired with optical projection tomography

Theo Lasser, Dimitri Nestor Alice Van De Ville, Aleksandra Radenovic, Paul James Marchand, Virginie Sophie Uhlmann, David Nguyen, Arielle Louise Planchette

Alzheimer's disease (AD) is characterized by amyloidosis of brain tissues. This phenomenon is studied with genetically-modified mouse models. We propose a method to quantify amyloidosis in whole 5xFAD mouse brains, a model of AD. We use optical projection ...

2019

DiversePathsJ: diverse shortest paths for bioimage analysis

Michaël Unser, Virginie Sophie Uhlmann

2018

Multiresolution Subdivision Snakes

Michaël Unser, Daniel Andreas Schmitter, Virginie Sophie Uhlmann, Anaïs Laure Marie-Thérèse Badoual

We present a new family of snakes that satisfy the property of multiresolution by exploiting subdivision schemes. We show in a generic way how to construct such snakes based on an admissible subdivision mask. We derive the necessary energy formulations and ...

2017

General Surface Energy for Spinal Cord and Aorta Segmentation

Michaël Unser, Daniel Andreas Schmitter, Virginie Sophie Uhlmann, Harshit Gupta

We present a new surface energy potential for the segmentation of cylindrical objects in 3D medical imaging using parametric spline active contours (a.k.a. spline-snakes). Our energy formulation is based on an optimal steerable surface detector. Thus, we c ...

IEEE2017

FlyLimbTracker: An Active Contour Based Approach for Leg Segment Tracking in Unmarked, Freely Behaving Drosophila

Michaël Unser, Virginie Sophie Uhlmann, Ricard Delgado Gonzalo

Understanding the biological underpinnings of movement and action requires the development of tools for quantitative measurements of animal behavior. Drosophila melanogaster provides an ideal model for developing such tools: the fly has unparalleled geneti ...

2017

Diverse M-Best Solutions by Dynamic Programming

Michaël Unser, Virginie Sophie Uhlmann

Many computer vision pipelines involve dynamic programming primitives such as finding a shortest path or the minimum energy solution in a tree-shaped probabilistic graphical model. In such cases, extracting not merely the best, but the set of M-best soluti ...

Springer2017

Landmark Active Contours for Bioimage Analysis : A Tale of Points and Curves

Virginie Sophie Uhlmann

The problem of identifying the outline of objects in images can be approached from two starting points, either by considering localized features (landmarks, keypoints or regions), or by searching for global contours. Features are regions or points of int ...

EPFL2017

User-Friendly Image-Based Segmentation and Analysis of Chromosomes

Florian Maria Wurm, Michaël Unser, Lucia Baldi Unser, Virginie Sophie Uhlmann, Ricard Delgado Gonzalo

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 pr ...

IEEE2016

CP-CHARM: Segmentation-Free Image Classification Made Accessible

Virginie Sophie Uhlmann

Background: Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed ...

2016

Hermite Snakes with Control of Tangents

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot

We introduce a new model of parametric contours defined in a continuous fashion. Our curve model relies on Hermite spline interpolation and can easily generate curves with sharp discontinuities; it also grants direct access to the tangent at each location. ...

IEEE2016

Maximally Localized Radial Profiles for Tight Steerable Wavelet Frames

Michaël Unser, Virginie Sophie Uhlmann, Pedram Pad

A crucial component of steerable wavelets is the radial profile of the generating function in the frequency domain. In this paper, we present an infinite-dimensional optimization scheme that helps us find the optimal profile for a given criterion over the ...

IEEE2016

Statistical Optimality of Hermite Splines

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot, Harshit Gupta

Hermite splines are commonly used for interpolating data when samples of the derivative are available, in a scheme called Hermite interpolation. Assuming a suitable statistical model, we demonstrate that this method is actually optimal for reconstructing r ...

IEEE2015

Efficient Shape Priors for Spline-Based Snakes

Michaël Unser, Daniel Andreas Schmitter, Virginie Sophie Uhlmann, Ricard Delgado Gonzalo

Parametric active contours are an attractive approach for image segmentation, thanks to their computational efficiency. They are driven by application-dependent energies that reflect the prior knowledge on the object to be segmented. We propose an energy i ...

2015

Tip-Seeking Active Contours for Bioimage Segmentation

Michaël Unser, Virginie Sophie Uhlmann

In the present paper, we address the problem of segmenting biological objects featuring corners. The main ingredients of our approach are automated feature-detection methods and mechanisms for introducing kinks in parametric spline snakes. We formulate a n ...

IEEE2015

Design of Steerable Wavelets to Detect Multifold Junctions

Michaël Unser, Cédric René Jean Vonesch, Virginie Sophie Uhlmann, Zsuzsanna Püspöki

We propose a framework for the detection of junctions in images. Although the detection of edges and key points is a well examined and described area, the multiscale detection of junction centers, especially for odd orders, poses a challenge in pattern ana ...

IEEE2015