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Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

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Comparison of 2D simultaneous multi-slice and 3D GRASE readout schemes for pseudo-continuous arterial spin labeling of cerebral perfusion at 3 T

Tobias Kober, Bénédicte Marie Maréchal, Tom Hilbert

Objective In this perfusion magnetic resonance imaging study, the performances of different pseudo-continuous arterial spin labeling (PCASL) sequences were compared: two-dimensional (2D) single-shot readout with simultaneous multislice (SMS), 2D single-sho ...

SPRINGER2021

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Mihai Adrian Ionescu, Francesco Bellando, Junrui Zhang

Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power i ...

2021

Extracting Maya Glyphs from Degraded Ancient Documents via Image Segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Rui Hu

We present a system for automatically extracting hieroglyph strokes from images of degraded ancient Maya codices. Our system adopts a region-based image segmentation framework. Multi-resolution super-pixels are first extracted to represent each image. A Su ...

Association for Computing Machinery2017

Transverse Noise, Decoherence, and Landau Damping in High-Energy Hadron Colliders

Sondre Vik Furuseth

High-energy hadron colliders are designed to generate particle collisions within specialized detectors. A higher number of collisions is achieved with high-quality beams of low transverse emittances, meaning a small transverse cross-section, and high inten ...

EPFL2021

Applications of Approximate Learning and Inference for Probabilistic Models

Young Jun Ko

We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

EPFL2017

Noise Analysis For Environmental Loading Effect On Gps Position Time Series

Jean-Philippe Lucien Montillet

This paper focusses on the impact of environment mass loading on GPS time-series of position changes and noise characteristic. We make use of position time series of 206 GPS station ranging from 2001 to 2013 globally distributed. Firstly, we investigate th ...

Institute of Rock Structure and Mechanics, AS CR2017

A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

Jean-Philippe Thiran, Fabian Braun, Martin Proença

Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Volkan Cevher

The estimation of a random vector with independent components passed through a linear transform followed by a componentwise (possibly nonlinear) output map arises in a range of applications. Approximate message passing (AMP) methods, based on Gaussian appr ...

2016

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

Object segmentation and ground truth in 3D embryonic imaging

Andrew Charles Oates

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Her ...

2016

Evaluating the potential of hyperpolarised [1-13C] L-lactate as a neuroprotectant metabolic biosensor for stroke

Mor-Miri Mishkovsky, Jean-Noël Hyacinthe, Lara Buscemi Estefanell, Thanh Phong Kevin Lê, Mario Gaetano Lepore

Cerebral metabolism, which can be monitored by magnetic resonance spectroscopy (MRS), changes rapidly after brain ischaemic injury. Hyperpolarisation techniques boost (13)C MRS sensitivity by several orders of magnitude, thereby enabling in vivo monitoring ...

Nature Research2020

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Mateusz Kozinski, Leonardo Citraro, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

Design of a Distributed Quantized Luenberger Filter for Bounded Noise

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This paper addresses the problem of distributed state estimation for linear systems with process and measurement noise, in the case of limited communication data rate, where the data exchanged between agents is quantized. We propose a linear distributed Lu ...

Ieee2016

Learning Structured Models for Segmentation of 2D and 3D Imagery

Pascal Fua, Graham Knott, Carlos Joaquin Becker, Kevin Smith, Aurélien Lucchi, Pablo Marquez Neila, Yunpeng Li

Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal perfo ...

Institute of Electrical and Electronics Engineers2015

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

2020

Normalized Gaussian path integrals

Giulio Corazza

Path integrals play a crucial role in describing the dynamics of physical systems subject to classical or quantum noise. In fact, when correctly normalized, they express the probability of transition between two states of the system. In this work, we show ...

AMER PHYSICAL SOC2020

Expectation Propagation for Rectified Linear Poisson Regression

Matthias Seeger, Young Jun Ko

The Poisson likelihood with rectified linear function as non-linearity is a physically plausible model to discribe the stochastic arrival process of photons or other particles at a detector. At low emission rates the discrete nature of this process leads t ...

2015