Results 181 to 190 of about 562,100 (312)

In vivo three-dimensional photoacoustic imaging based on a clinical matrix array ultrasound probe.

open access: yesJournal of Biomedical Optics, 2012
Yu Wang   +6 more
semanticscholar   +1 more source

Beyond Visual Scoring: Computational CT‐analysis for HRCT based quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

open access: yesArthritis Care &Research, Accepted Article.
Interstitial lung disease (IRD‐ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRD). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the non‐invasive assessment of ILD; however, its interpretation is constrained by substantial inter‐observer variability and ...
Alexander Pfeil   +7 more
wiley   +1 more source

Automated Hand Flexor Tendon Thickness Measurement in Systemic Sclerosis

open access: yesArthritis Care &Research, Accepted Article.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasound and measured manually, a time‐consuming process prone to inter‐observer variability.
Mark Greveling   +4 more
wiley   +1 more source

Demographic variation of styloid process morphology in panoramic radiography. [PDF]

open access: yesBMC Oral Health
Schuck O   +4 more
europepmc   +1 more source

Adaptive Observer for Coupled Wave PDE and Infinite ODE With Sampled Data and Unknown Input: Application to Brain Hemodynamics Estimation

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This article proposes a convergent adaptive observer for a damped wave PDE and an infinite‐dimensional ODE coupled in cascade using sampled‐in‐space ODE state measurements. The proposed observer estimates the distributed states of the PDE and ODE along with unknown PDE parameters and spatial input.
Zehor Belkhatir   +2 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +2 more
wiley   +1 more source

Home - About - Disclaimer - Privacy