Publications related to BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Related publications (42)

Lamellar Schwann Cells in the Pacinian Corpuscle Potentiate Vibration Perception

Graham Knott, Mary-Claude Croisier-Coeytaux, Jérôme Blanc, Stéphanie Clerc

Pacinian corpuscles are among the most sensitive mechanoreceptors found in vertebrates, and they are tuned to vibrations in the highest perceptible frequency range (100 to 2000 Hz). One of their anatomical hallmarks is the onion-like cell layers surroundin ...

AMER ASSOC ADVANCEMENT SCIENCE2025

Exploiting Covalent Chemical Labeling with Self-Labeling Proteins

Kai Johnsson

The visualization and manipulation of proteins in live cells are critical for studying complex biological processes. Self-labeling proteins do so by enabling the specific and covalent attachment of synthetic probes, offering unprecedented flexibility in th ...

Annual Reviews2025

Bioanode engineering for living solar cells

Charlotte Elisabeth Marie Roullier

Whole-cell biophotovoltaic (BPV) devices leverage photoautotrophic microorganisms like cyanobacteria to convert sunlight and water into bioelectricity. They are capable of growing on sequestered carbon dioxide (CO2), eliminating the need to add exogenous o ...

EPFL2025

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Experimental and computational analysis of REM sleep distributed cortical activity in mice

Sylvain Crochet

Although classically Rapid-Eye Movement (REM) sleep was thought to generate desynchronized activity similar to wakefulness, it was found that some brain regions could express Slow Wave activity (SWA), a pattern which was normally typical of slow-wave sleep ...

American Physiological Society2025

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

CORTEX experiments – Part I: Modulation campaigns in AKR-2 & CROCUS for the validation of neutron noise codes

Andreas Pautz, Vincent Pierre Lamirand, Mathieu Hursin, Oskari Ville Pakari, Pavel Frajtag, Axel Guy Marie Laureau, Fanny Vitullo, Adolfo Rais, Thomas Jean-François Ligonnet, Nicolas Weiss, Daniel Godat, Klemen Ambrozic

We present the experimental campaigns – namely, three per facility – carried out between 2018 and 2021 in the AKR–2 and CROCUS zero power reactors within the framework of the Horizon 2020 European project CORTEX. Their purpose was to produce high-quality a ...

2025

Towards Trustworthy Deep Learning for Image Reconstruction

Alexis Marie Frederic Goujon

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Liying Lu, Raphaël Wan-Li Marc Achddou, Sabine Süsstrunk

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

2025

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

A Multiscale Bayesian Approach to Quantification and Denoising of Energy-dispersive X-ray Data

Cécile Hébert, Duncan Thomas Lindsay Alexander, Pau Torruella Besa

Energy dispersive x-ray (EDX) spectrum imaging yields compositional information with a spatial resolution down to the atomic level. However, experimental limitations often produce extremely sparse and noisy EDX spectra. Under such conditions, every detecte ...

IOP Publishing Ltd2025

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Engineering Symmetry Breaking Interfaces by Nanoscale Structural-Energetics in Orthorhombic Perovskite Thin Films

Duncan Thomas Lindsay Alexander, Bernat Mundet

The atomic configuration of phases and their interfaces is fundamental to materials design and engineering. Here, we unveil a transition metal oxide interface, whose formation is driven by energetic influences─epitaxial tensile strain versus oxygen octahed ...

2025

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Veronica Lily Ravano

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

EPFL2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Human self and Neurosurgery: Advances and insights from Geneva

Olaf Blanke, Bruno Herbelin

Introduction: The preservation of the human self—a fundamental yet underexplored aspect of neurosurgical practice—has gained increasing attention in recent years. Research question: How can neural correlates of self-consciousness be identified, monitored, ...

2025

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Ismail Nejjar

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear Structures

Jiancheng Yang

Accurate segmentation of anatomical substructures within 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm development and evaluation. In this pape ...

2025

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024