Quantitative phase imaging in biomedicine

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Molecular medical imaging is intended to increase the accuracy of diagnosis, particularly in cardiovascular and cancer-related diseases, where early detection could significantly increase the treatment success rate. In this study, we present mixed micelles ...

We introduce a lock-in method to increase the phase contrast in incoherent differential phase contrast (DPC) imaging. This method improves the phase sensitivity by the analog removal of the background. The use of a smart pixel detector with in-pixel signal ...

Among the medical imaging modalities, ultrasound (US) imaging is one of the safest, most widespread, and least expensive method used in medical diagnosis. In the past decades, several technological advances enabled the advent of ultrafast US imaging, an ac ...

The present invention is related to an endoscopic system for phase imaging, comprising a multicore waveguide (080), an optical system comprising at least one first light source (002), for illuminating the sample to be examined, a first camera (010) that is ...

We introduce a lock-in method to increase the phase contrast in incoherent Differential Phase Contrast (DPC) imaging. The use of a smart pixel detector with in-pixel signal demodulation, paired with synchronized illumination, provides the basis of a bit-ef ...

The high longitudinal and lateral coherence of synchrotron X-rays sources radically transformed radiography. Before them, the image contrast was almost only based on absorption. Coherent synchrotron sources transformed radiography into a multi-faceted tool ...

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) h ...

Polarization of light has been widely used as a contrast mechanism in two-dimensional (2D) microscopy and also in some three-dimensional (3D) imaging modalities. In this paper, we report the 3D tomographic reconstruction of the refractive index (RI) tensor ...

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hi ...

A first-principles scaling law, based on turbulent transport considerations, and a multimachine database of density limit discharges from the ASDEX Upgrade, JET, and TCV tokamaks, show that the increase of the boundary turbulent transport with the plasma c ...

Background Currently, multi-parametric prostate MRI (mpMRI) consists of a qualitative T-2, diffusion weighted, and dynamic contrast enhanced imaging. Quantification of T-2 imaging might further standardize PCa detection and support artificial intelligence ...

Recently a joint project has been carried out between the Paul Scherrer Institut, the Ecole Polytechnique Federale de Lausanne and swissnuclear, an industrial partner, in order to determine the axial void distribution in a channel installed in the reflecto ...

Machine learning has become the state of the art for the solution of the diverse inverse problems arising from computer vision and medical imaging, e.g. denoising, super-resolution, de-blurring, reconstruction from scanner data, quantitative magnetic reson ...

High-throughput synchrotron-based tomographic microscopy at third generation light sources allows to probe cm-sized samples at micrometer-resolution. In this work, we present an approach to image a full mouse brain. With Indian-ink as a contrast agent, it ...

In this thesis, we study the 3 challenges described above. First, we study different reconstruction techniques and assess the fidelity of each reconstruction results by means of structured illumination and phase conjugation. By reconstructing the 3D refrac ...

Magnetic resonance resonance (MRI) is a widely used modality to obtain in vivo tissue information. Clinical applications are near countless, and almost all body parts can be examined using an MR scanner. As the method is non invasive, does not use ionizing ...

Quantitative phase imaging in biomedicine

Chat with Graph Search

Vascular-targeted micelles as a specific MRI contrast agent for molecular imaging of fibrin clots and cancer cells

Lock-in incoherent differential phase contrast imaging

Ultrasound Imaging: From Physical Modeling to Deep Learning

Multicore fiber endoscope for phase imaging based on intensity recording using deep neural networks

Lock-in amplified differential phase contrast

Imaging with Coherent X-rays: From the Early Synchrotron Tests to SYNAPSE

BMAT: An open-source BIDS managing and analysis tool

Polarization-sensitive optics diffraction tomography

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

First-Principles Density Limit Scaling in Tokamaks Based on Edge Turbulent Transport and Implications for ITER

Value of T-2 Mapping MRI for Prostate Cancer Detection and Classification

Validation of axial void profile measured by neutron noise techniques in CROCUS

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

Brain micro-vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high-resolution phase-contrast X-ray tomography

Advanced Techniques in Optical Diffraction Tomography

Fat navigators based retrospective motion correction strategies for brain magnetic resonance imaging