Publication

NeuroMorph: A Toolset for the Morphometric Analysis and Visualization of 3D Models Derived from Electron Microscopy Image Stacks

Related publications (29)

Correlative light and volume electron microscopy to study brain development

Recent advances in volume electron microscopy (EM) have been driving our thorough understanding of the brain architecture. Volume EM becomes increasingly powerful when cells and their subcellular structures that are imaged in light microscopy are correlate ...

OXFORD UNIV PRESS2023

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

Max Stieber, Martin Weigert, Benjamin Tobias Gallusser

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

Automated image-based generation of finite element models for masonry buildings

Radhakrishna Achanta, Katrin Beyer, Bryan German Pantoja Rosero

To predict the response of masonry buildings to various types of loads, engineers use finite element models, specifically solid-element and macro-element models. For predicting masonry responses to seismic events in particular, equivalent frame models-a su ...

SPRINGER2023

Cortical alterations after very preterm birth and the association with socio-emotional abilities from childhood to early adolescence

Jean-Philippe Thiran, Elda Fischi Gomez, Vanessa Siffredi

Very preterm birth (VPT;

2023

Tissue clearing applications in memory engram research

Johannes Gräff, Kwok Yui Reymond Yip

A memory engram is thought to be the physical substrate of the memory trace within the brain, which is generally depicted as a neuronal ensemble activated by learning to fire together during encoding and retrieval. It has been postulated that engram cell e ...

FRONTIERS MEDIA SA2023

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Devis Tuia, Zifu Wang

Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, where some objects occupy more pixels than others. This causes traditional eva ...

2023

Practical computational imaging by use of spatiotemporal light modulation: from simulations to applications in biological microscopy

François Thierry M Marelli

Optical microscopy is an essential tool for biologists, who are often faced with the need to overcome the spatial and temporal resolution limitations of their devices to capture finer details. As upgrading imaging hardware is expensive, computational metho ...

EPFL2023

Revealing the complexity of ultra-soft hydrogel re-swelling inside the brain

Stéphanie Lacour, Michael Shur, John Martin Kolinski, Outman Akouissi, Olivier Didier Christian Rizzo

The brain is an ultra-soft viscoelastic matrix. Sub-kPa hydrogels match the brain's mechanical properties but are challenging to manipulate in an implantable format. We propose a simple fabrication and processing sequence, consisting of de-hydration, patte ...

2023

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023