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

Aggregating Spatial and Photometric Context for Photometric Stereo

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

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

Martin Weigert

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

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

The multimodality cell segmentation challenge: toward universal solutions

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

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

Enabling Uncertainty Estimation in Iterative Neural Networks

Pascal Fua, Doruk Oner, Nikita Durasov, Minh Hieu Lê

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

Curran Associates2024

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

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

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 ...

EPFL2024

Small-scale robotic devices for medical interventions in the brain

Lorenzo Francesco John Noseda, Mahmut Selman Sakar

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

2024

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Fabian Fischer, Ardemis Anoush Boghossian, Charlotte Elisabeth Marie Roullier, Melania Reggente, Mohammed Mouhib, Patricia Brandl, Hanxuan Wang

Living photovoltaics are microbial electrochemical devices that use whole cell–electrode interactions to convert solar energy to electricity. The bottleneck in these technologies is the limited electron transfer between the microbe and the electrode surfac ...

2024

Label-Free Techniques for Probing Biomolecular Condensates

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

White adipose tissue distribution and amount are associated with increased white matter connectivity

Jean-Philippe Thiran, Elda Fischi Gomez, Gabriel Girard, Philipp Johannes Koch, Liana Okudzhava

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

Wiley2024

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

Ghost imaging using two SPAD array detectors: a parameter study towards the realization of a 3D quantum microscope

Claudio Bruschini, Edoardo Charbon, Paul Mos, Yang Lin

Quantum ghost imaging can be an important tool in making optical measurements. One of the most useful aspects of ghost imaging is the unique ability to correlate two sets of independently collected information. We aim to use the principles of ghost imaging ...

Spie-Int Soc Optical Engineering2024

Revealing the Mechanism Underlying 3D-AFM Imaging of Suspended Structures by Experiments and Simulations

Marcos Penedo Garcia

The invention of 3D atomic force microscopy (3D-AFM) has enabled visualizing subnanoscale 3D hydration structures. Meanwhile, its applications to imaging flexible molecular chains have started to be experimentally explored. However, the validity and princi ...

Wiley-V C H Verlag Gmbh2024

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

Sahand Jamal Rahi, Kseniia Korchagina

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 ...

Nature Portfolio2023

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

Gulnaz Ganeeva

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 ...

EPFL2023

Digital reconstruction of the mammalian spinal cord: from anatomical reference volume to cell type atlas of the mouse spinal cord

Ihor Kuras

The spinal cord is an elongated nervous structure that together with the brain forms the central nervous system. It relays sensory and motor information between the brain and the body, thus controlling most somatic and autonomic body functions. In recent y ...

EPFL2023

Axonal projections from mouse whisker-related sensory cortex

Yanqi Liu

Neurons primarily communicate through release of neurotransmitter from presynaptic specialisations along their axonal arborisations. In order to understand the functional role of a specific neuron, it is therefore of great interest to know the structure of ...

EPFL2023

Deep Learning for 3D Surface Modelling and Reconstruction

Benoît Alain René Guillard

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 ...

EPFL2023