Results 31 to 40 of about 63,711 (218)

Feasibility study of 2D Dixon-Magnetic Resonance Fingerprinting (MRF) of breast cancer

open access: yesEuropean Journal of Radiology Open, 2022
Purpose: Application of MRF to evaluate the feasibility of 2D Dixon blurring-corrected MRF (2DDb-cMRF) to differentiate breast cancer (BC) from normal fibroglandular tissue (FGT).
Eloisa Zanderigo   +10 more
doaj   +1 more source

Posterior Mean Super-Resolution with a Compound Gaussian Markov Random Field Prior

open access: yes, 2012
This manuscript proposes a posterior mean (PM) super-resolution (SR) method with a compound Gaussian Markov random field (MRF) prior. SR is a technique to estimate a spatially high-resolution image from observed multiple low-resolution images. A compound
Inoue, Masato, Katsuki, Takayuki
core   +1 more source

Bayesian Reconstruction of Missing Observations [PDF]

open access: yes, 2015
We focus on an interpolation method referred to Bayesian reconstruction in this paper. Whereas in standard interpolation methods missing data are interpolated deterministically, in Bayesian reconstruction, missing data are interpolated probabilistically ...
Kataoka, Shun   +2 more
core   +3 more sources

Light‐Driven Competitive Selection in a Protein‐Catalyzed Dissipative Peptide Replication

open access: yesAngewandte Chemie, EarlyView.
A structurally flexible protein catalyzes replication within a dissipative reaction network driven by UVA‐induced disulfide rearrangements. The protein accelerates templated autocatalytic cycles with replication emerging as the dominant pathway.
Éva Bartus   +12 more
wiley   +2 more sources

Enhancement of aerodynamic performance of H-Darrieus rotor using wraparound fairing system: A 2D CFD study

open access: yesInternational Journal of Renewable Energy Development
The aim of this article is to improve the aerodynamic performance of a three-bladed vertical axis H-Darrieus wind turbine, which is equipped with different types of fairings.
Douha Boulla   +5 more
doaj   +1 more source

A Review on Structural Configurations of Magnetorheological Fluid Based Devices Reported in 2018–2020

open access: yesFrontiers in Materials, 2021
Magnetorheological fluid (MRF) is a kind of smart materials with rheological behavior change by means of external magnetic field application, which has been widely adopted in many complex systems of different technical fields.
Dezheng Hua   +6 more
doaj   +1 more source

Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixel Measurement Models [PDF]

open access: yes, 2015
This paper proposes a method for fusing data acquired by a ToF camera and a stereo pair based on a model for depth measurement by ToF cameras which accounts also for depth discontinuity artifacts due to the mixed pixel effect.
Cortelazzo, GUIDO MARIA   +2 more
core   +1 more source

Influence of the Drive Plate with Different Surface Textures on the Property of Carbonyl Iron-Based Magnetorheological Fluid

open access: yesAdvances in Materials Science and Engineering, 2020
Aiming to study the effect of drive plate with different surface topographies on the wear property of magnetorheological fluid (MRF), some specific experiments are carried out and analyzed in this paper. Firstly, experiment materials and test methods for
He Lu   +5 more
doaj   +1 more source

A Self-Supervised Deep Learning Reconstruction for Shortening the Breathhold and Acquisition Window in Cardiac Magnetic Resonance Fingerprinting

open access: yesFrontiers in Cardiovascular Medicine, 2022
The aim of this study is to shorten the breathhold and diastolic acquisition window in cardiac magnetic resonance fingerprinting (MRF) for simultaneous T1, T2, and proton spin density (M0) mapping to improve scan efficiency and reduce motion artifacts ...
Jesse I. Hamilton, Jesse I. Hamilton
doaj   +1 more source

Markov Network Structure Learning via Ensemble-of-Forests Models [PDF]

open access: yes, 2013
Real world systems typically feature a variety of different dependency types and topologies that complicate model selection for probabilistic graphical models.
Arvaniti, Eirini, Claassen, Manfred
core  

Home - About - Disclaimer - Privacy