AIMC Topic: Lung
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Three-stage segmentation of lung region from CT images using deep neural networks.
BMC medical imaging
Jul 15, 2021
BACKGROUND: Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the accuracy i...
Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning.
European radiology
Jul 13, 2021
OBJECTIVES: Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI...
Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans.
Scientific reports
Jul 8, 2021
COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives of several people. Although potential vaccines are being tested and supplied around the world, it will take a long time to reach every human being, mo...
Bayesian convolutional neural network estimation for pediatric pneumonia detection and diagnosis.
Computer methods and programs in biomedicine
Jul 7, 2021
BACKGROUND AND OBJECTIVES: Pneumonia is a disease that affects the lungs, making breathing difficult. Nowadays, pneumonia is the disease that kills the most children under the age of five in the world, and if no action is taken, pneumonia is estimate...
Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform.
Analytica chimica acta
Jul 2, 2021
Multivariate statistical analysis methods have an important role in spectrochemical analyses to rapidly identify and diagnose cancer and the subtype. However, utilizing these methods to analyze lager amount spectral data is challenging, and poses a m...
Artificial Intelligence for Interstitial Lung Disease Analysis on Chest Computed Tomography: A Systematic Review.
Academic radiology
Jul 1, 2021
RATIONALE AND OBJECTIVES: High-resolution computed tomography (HRCT) is paramount in the assessment of interstitial lung disease (ILD). Yet, HRCT interpretation of ILDs may be hampered by inter- and intra-observer variability. Recently, artificial in...
Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia.
Clinical imaging
Jul 1, 2021
PURPOSE: Comparison of deep learning algorithm, radiomics and subjective assessment of chest CT for predicting outcome (death or recovery) and intensive care unit (ICU) admission in patients with severe acute respiratory syndrome coronavirus 2 (SARS-...
Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation.
Chinese medical journal
Jul 1, 2021
BACKGROUND: Prenatal evaluation of fetal lung maturity (FLM) is a challenge, and an effective non-invasive method for prenatal assessment of FLM is needed. The study aimed to establish a normal fetal lung gestational age (GA) grading model based on d...
Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 29, 2021
As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-19 Pneumonia (PN) in this epidemic. By virtue of lung ultrasound scores (LUSS), lung ultrasound (LUS...
scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics.
Nature communications
Jun 22, 2021
Single-cell omics is the fastest-growing type of genomics data in the literature and public genomics repositories. Leveraging the growing repository of labeled datasets and transferring labels from existing datasets to newly generated datasets will e...
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