A heterogeneous GRA-CBR-based multi-attribute emergency decision-making model considering weight optimization with dual information correlation
W Chen, X Wang, W Wang, Y Zhu, Z Cai… - Expert Systems with …, 2021 - Elsevier
The emergency response in an engineering operating entails a heterogeneous multi-
attribute emergency decision-making (HMAEDM) problem containing crisp, interval …
attribute emergency decision-making (HMAEDM) problem containing crisp, interval …
[HTML][HTML] Worker-centric heat strain analysis: Integrating physiological signals with ensemble learning and domain adaptation
Despite advances in utilizing physiological sensors and machine learning (ML) algorithms,
accurately and consistently monitoring heat strain levels of field workers on job sites remains …
accurately and consistently monitoring heat strain levels of field workers on job sites remains …
Image-domain material decomposition for spectral CT using a generalized dictionary learning
The spectral computed tomography (CT) has huge advantages by providing accurate
material information. Unfortunately, due to the instability or overdetermination of the material …
material information. Unfortunately, due to the instability or overdetermination of the material …
Contactless monitoring of heart rate variability during respiratory maneuvers
Heart rate variability (HRV) is a noninvasive marker for the cardiovascular system and the
substantial influence of this system on the autonomous nervous system (ANS). Contact and …
substantial influence of this system on the autonomous nervous system (ANS). Contact and …
Spectral calibration of photon‐counting detectors at high photon flux
EY Sidky, ER Paul, T Gilat‐Schmidt, X Pan - Medical physics, 2022 - Wiley Online Library
Background Calibration of photon‐counting detectors (PCDs) is necessary for quantitatively
accurate spectral computed tomography (CT), but the calibration process can be …
accurate spectral computed tomography (CT), but the calibration process can be …
Improved material decomposition with a two-step regularization for spectral CT
One of the advantages of spectral computed tomography (CT) is it can achieve accurate
material components using the material decomposition methods. The image-based material …
material components using the material decomposition methods. The image-based material …
Addressing CT metal artifacts using photon‐counting detectors and one‐step spectral CT image reconstruction
TG Schmidt, BA Sammut, RF Barber, X Pan… - Medical …, 2022 - Wiley Online Library
Purpose The constrained one‐step spectral CT image reconstruction (cOSSCIR) algorithm
with a nonconvex alternating direction method of multipliers optimizer is proposed for …
with a nonconvex alternating direction method of multipliers optimizer is proposed for …
Virtual computed-tomography system for deep-learning-based material decomposition
D Fujiwara, T Shimomura, W Zhao, KW Li… - Physics in Medicine …, 2022 - iopscience.iop.org
Objective. Material decomposition (MD) evaluates the elemental composition of human
tissues and organs via computed tomography (CT) and is indispensable in correlating …
tissues and organs via computed tomography (CT) and is indispensable in correlating …
X-ray energy spectrum estimation based on a virtual computed tomography system
T Higuchi, A Haga - Biomedical Physics & Engineering Express, 2023 - iopscience.iop.org
This paper presents a method for estimating the x-ray energy spectrum for computed
tomography (CT) in the diagnostic energy range from the reconstructed CT image itself. To …
tomography (CT) in the diagnostic energy range from the reconstructed CT image itself. To …
Taming numerical imprecision by adapting the KL divergence to negative probabilities
Abstract The Kullback–Leibler (KL) divergence is frequently used in data science. For
discrete distributions on large state spaces, approximations of probability vectors may result …
discrete distributions on large state spaces, approximations of probability vectors may result …