Deep learning-assisted fluorescence spectroscopy for food quality and safety analysis
Y Yuan, Z Ji, Y Fan, Q Xu, C Shi, J Lyu… - Trends in Food Science & …, 2024 - Elsevier
Background Fluorescence spectroscopy has been widely employed in the quality
assessment of food and agricultural products due to its rapid and accurate measurement …
assessment of food and agricultural products due to its rapid and accurate measurement …
Dedicated convolutional neural network for noise reduction in ultra-high-resolution photon-counting detector computed tomography
Objective. To develop a convolutional neural network (CNN) noise reduction technique for
ultra-high-resolution photon-counting detector computed tomography (UHR-PCD-CT) that …
ultra-high-resolution photon-counting detector computed tomography (UHR-PCD-CT) that …
Dual-contrast biphasic liver imaging with iodine and gadolinium using photon-counting detector computed tomography: an exploratory animal study
Purpose The aims of this study were to develop a single-scan dual-contrast protocol for
biphasic liver imaging with 2 intravenous contrast agents (iodine and gadolinium) and to …
biphasic liver imaging with 2 intravenous contrast agents (iodine and gadolinium) and to …
Pie‐Net: Prior‐information‐enabled deep learning noise reduction for coronary CT angiography acquired with a photon counting detector CT
S Chang, NR Huber, JF Marsh, EK Koons… - Medical …, 2023 - Wiley Online Library
Background Photon‐counting‐detector CT (PCD‐CT) enables the production of virtual
monoenergetic images (VMIs) at a high spatial resolution (HR) via simultaneous acquisition …
monoenergetic images (VMIs) at a high spatial resolution (HR) via simultaneous acquisition …
The impact of Bayesian optimization on feature selection
K Yang, L Liu, Y Wen - Scientific Reports, 2024 - nature.com
Feature selection is an indispensable step for the analysis of high-dimensional molecular
data. Despite its importance, consensus is lacking on how to choose the most appropriate …
data. Despite its importance, consensus is lacking on how to choose the most appropriate …
Clinical evaluation of a phantom-based deep convolutional neural network for whole-body-low-dose and ultra-low-dose CT skeletal surveys
Objective This study evaluated the clinical utility of a phantom-based convolutional neural
network noise reduction framework for whole-body-low-dose CT skeletal surveys. Materials …
network noise reduction framework for whole-body-low-dose CT skeletal surveys. Materials …
[HTML][HTML] Automated MRI quantification of pediatric abdominal adipose tissue using convolutional neural networks and novel total intensity maps
Objective Childhood obesity is a significant global health concern. Visceral adipose tissue
(VAT) is more closely linked to the development of metabolic and cardiovascular diseases …
(VAT) is more closely linked to the development of metabolic and cardiovascular diseases …
A novel normalization algorithm to facilitate pre-assessment of Covid-19 disease by improving accuracy of CNN and its FPGA implementation
COVID-19 is still a fatal disease, which has threatened all people by affecting the human
lungs. Chest X-Ray or computed tomography imaging is commonly used to make a fast and …
lungs. Chest X-Ray or computed tomography imaging is commonly used to make a fast and …
[HTML][HTML] Very short-term wind power forecasting for real-time operation using hybrid deep learning model with optimization algorithm
This paper proposes a new hybrid deep learning model to enhance the accuracy of
forecasting very short-term wind power generation. The proposed model comprises a …
forecasting very short-term wind power generation. The proposed model comprises a …
Development of Artificial Intelligence for Determining Major Depressive Disorder Based on Resting-State EEG and Single-Pulse Transcranial Magnetic Stimulation …
Depression is the disorder with the greatest socioeconomic burdens. Its diagnosis is still
based on an operational diagnosis derived from symptoms, and no objective diagnostic …
based on an operational diagnosis derived from symptoms, and no objective diagnostic …