Publications related to General Surface Energy for Spinal Cord and Aorta Segmentation

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

Excited State-Specific CASSCF Theory for the Torsion of Ethylene

State-specific complete active space self-consistent field (SS-CASSCF) theory has emerged as a promising route to accurately predict electronically excited energy surfaces away from molecular equilibria. However, its accuracy and practicality for chemical ...

Amer Chemical Soc2024

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

Inverse Problems in Pulse-Echo Ultrasound: Exploiting Coherence for Image Enhancement and Quantitative Imaging

Samuel Denys Beuret

Whereas pulse-echo ultrasound imaging relied on focused acoustic waves since its inception, the last two decades have seen the development of techniques based on unfocused waves, including ultrafast ultrasound imaging. In large part due to the emergence of ...

EPFL2024

Quantified interface chemistry and biophysics via water imaging

Sylvie Roke

High throughput wide-field second harmonic imaging enables the label-free imaging of interfacial (< 3 nm thick) water, with a spatial resolution of similar to 370 nm using similar to 100 ms acquisition times per image. The obtained interfacial orientationa ...

Spie-Int Soc Optical Engineering2024

Targeted regeneration of spinal cord neurons across a complete injury restores walking

Marco Milano

Spinal cord injury (SCI) interrupts axonal connections between the brain and the spinal cord, and is characterized by a spectrum of sensorimotor and autonomic impairments. While spontaneous recovery is limited, recent studies have shown that functional imp ...

EPFL2023

Functional neuroimaging options for tinnitus

Patrick Karl Alois Neff

Background: The pathophysiology behind tinnitus is still not well understood. Different imaging methods help in the understanding of the complex relationships that lead to the perception of tinnitus.Objective: Herein, different functional imaging methods t ...

SPRINGER2023

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

Berend Smit, Senja Dominique Barthel, Amber Kashan Mace

We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion ...

Amer Chemical Soc2023

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Seyedbehzad Bozorgtabar, Devavrat Tomar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

IEEE2023

Correlated-photon imaging at 10 volumetric images per second

Claudio Bruschini, Edoardo Charbon, Arin Can Ülkü, Paul Mos

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing s ...

Nature Portfolio2023

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

Brain-controlled spinal cord stimulation to restore mobility after spinal cord injury

Carmina Andrea Galvez Solano

Spinal Cord Injury (SCI) affects almost 500,000 people every year, causing complete paralysis of both legs in severe cases, with no current treatment perspective. However, new neuroengineering technologies, such as the Brain Spine Interface (BSI), have eme ...

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

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

Confidence Matters: Applications to Semantic Segmentation

Prabhu Teja Sivaprasad

The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...

EPFL2023

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets

Olga Fink, Mina Montazeri

Finding optimal bidding strategies for generation units in electricity markets would result in higher profit. However, it is a challenging problem due to the system uncertainty which is due to the lack of knowledge of the strategies of other generation uni ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging

Tom Hilbert

Rationale and objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 ...

CELL PRESS2023

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Kevin Rossi

Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...

AMER PHYSICAL SOC2023