Publications associées à Automated segmentation of multiple red blood cells with digital holographic microscopy

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

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 ...

Nature Portfolio2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

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 ...

EPFL2024

The multimodality cell segmentation challenge: toward universal solutions

Sahand Jamal Rahi, Vojislav Gligorovski, Marco Labagnara, Jun Ma, Maxime Emmanuel Scheder, Xin Yang, Yao Zhang, Bo Wang, Yixin Wang, Lin Han

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 ...

Nature Portfolio2024

Compact and effective photon-resolved image scanning microscope

Giorgio Tortarolo

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 ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

3D printed large amplitude torsional microactuators powered by ultrasound

Mahmut Selman Sakar, Mehdi Ali Gadiri, Junsun Hwang, Amit Yedidia Dolev

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

2024

Label-Free Techniques for Probing Biomolecular Condensates

Aleksandra Radenovic, Wayne Yang Wen Wei, Khalid Ashraf Mohie Ibrahim, Helena Miljkovic, Akhil Sai Naidu

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and e ...

Amer Chemical Soc2024

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

Tangentially viewing phase contrast imaging for turbulence measurements in toroidal fusion devices

Stefano Coda

Phase contrast imaging (PCI) is an established and powerful technique for measuring density fluctuations in plasmas and has been successfully applied to several fusion devices. Rooted in a concept first developed for microscopy, PCI belongs to the category ...

2024

In vitro-transfusional model for red-blood-cell study: the advantage of lowering hematocrit

Gerardo Turcatti, Manon Sandra Bardyn, David Crettaz, Michel Prudent

Background - Thequalityof red blood cells (RBCs) stored in red cell concentrates (RCCs) is influenced by processing, storage and donor characteristics, and can have a clinical impact on transfused patients. To evaluate RBC properties and their potential im ...

Simtipro Srl2023

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

Martin Weigert, Benjamin Tobias Gallusser, Max Stieber

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 ...

Springer International Publishing Ag2023