User-Friendly Image-Based Segmentation and Analysis of Chromosomes

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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 ...

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast vi ...

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

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 ...

Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often ...

This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects. S ...

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) h ...

In a recent article, we described the edxia framework, a user-friendly framework to analyse the microstructure of cementitious materials using SEM-EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific ques ...

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

In medical image segmentation, supervised deep networks' success comes at the cost of requiring abundant labeled data. While asking domain experts to annotate only one or a few of the cohort's images is feasible, annotating all available images is impracti ...

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

DeepImageJ offers a user-friendly solution in ImageJ to run trained deep learning models for biomedical image analysis. It includes guiding tools for reliable analyses, contributing to the democratization of deep learning in microscopy. ...

The RAPTOR suite of codes combines real-time model-based predictions of the plasma state with the available diagnostic measurements. Following the work on TCV and ASDEX-Upgrade, this paper presents the implementation of the RAPTOR suite for JET. This suite ...

Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recomme ...

Designing structures from reused elements is becoming an increasingly important design task for structural engineers as it has potential to significantly reduce adverse environmental impacts of building structures. To allow for a broad application of this ...

Modern histopathology workflows rely on the digitization of histology slides. The quality of the resulting digital representations, in the form of histology slide image mosaics, depends on various specific acquisition conditions and on the image processing ...

This study aimed to explore the value of synchrotron-based phase-contrast microcomputed tomography (micro-CT) in pulmonary vascular pathobiology. The microanatomy of the lung is complex with intricate branching patterns. Tissue sections are therefore diffi ...

Environmental management depends on high-quality monitoring and its meaningful interpretation. The combination of local weather dynamics, regional anthropogenic stresses and global environmental changes make the evaluation of monitoring information in dyna ...

User-Friendly Image-Based Segmentation and Analysis of Chromosomes

Chattez avec Graph Search

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

SoccerNet 2023 challenges results

Text-to-Microstructure Generation Using Generative Deep Learning

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

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

impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers

Latency Interfaces for Systems Code

BMAT: An open-source BIDS managing and analysis tool

Simple automation of SEM-EDS spectral maps analysis with Python and the edxia framework

Dynamic Personalized Ranking

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Development of the RAPTOR suite of codes towards real-time reconstruction of JET discharges

Multi-Step Critiquing User Interface for Recommender Systems

Computational tool for stock-constrained design of structures

HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue

Synchrotron-based phase-contrast micro-CT as a tool for understanding pulmonary vascular pathobiology and the 3-D microanatomy of alveolar capillary dysplasia

Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics