NeuroMorph: A Software Toolset for 3D Analysis of Neurite Morphology and Connectivity

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In computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several cha ...

Fuzz testing a software library requires developers to write fuzz drivers, specialized programs exercising the library. Given a driver, fuzzers generate interesting inputs that trigger the library’s bugs. Writing fuzz drivers manually is a cumbersome proce ...

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Information is transmitted between brain regions through the release of neurotransmitters from long-range projecting axons. Understanding how the activity of such long-range connections contributes to behavior requires efficient methods for reversibly mani ...

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

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 ...

Software is going through a trust crisis. Privileged code is no longer trusted and processes insufficiently protect user code from unverified libraries. While usually treated separately, confidential computing and program compartmentalization are both symp ...

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolut ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

NeuroMorph: A Software Toolset for 3D Analysis of Neurite Morphology and Connectivity

Chattez avec Graph Search

PLUMED Tutorials: A collaborative, community-driven learning ecosystem

Liberating Libraries through Automated Fuzz Driver Generation: Striking a Balance without Consumer Code

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Aggregating Spatial and Photometric Context for Photometric Stereo

The multimodality cell segmentation challenge: toward universal solutions

Incorporating Projective Geometry into Deep Learning

A bistable inhibitory optoGPCR for multiplexed optogenetic control of neural circuits

Compact and effective photon-resolved image scanning microscope

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Creating Trust by Abolishing Hierarchies

Robust Collaborative Learning with Linear Gradient Overhead

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Principles of Network Plasticity in Neocortical Microcircuits

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Deep Learning for 3D Surface Modelling and Reconstruction

Multi-site, Multi-domain Airway Tree Modeling

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy