AIMC Topic: Lung
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Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.
European radiology
Jun 29, 2020
OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying emphysema using low-dose computed tomography (LDCT) and evaluated the efficiency of a deep learning-based kernel conversion technique in normalizing ker...
Efficiency of a computer-aided diagnosis (CAD) system with deep learning in detection of pulmonary nodules on 1-mm-thick images of computed tomography.
Japanese journal of radiology
Jun 26, 2020
PURPOSE: To evaluate the performance of a deep learning-based computer-aided diagnosis (CAD) system at detecting pulmonary nodules on CT by comparing radiologists' readings with and without CAD.
Male
Middle Aged
Lung
Diagnosis, Computer-Assisted
Young Adult
Adult
Sensitivity and Specificity
Radiographic Image Interpretation, Computer-Assisted
Deep Learning
Lung Neoplasms
Multiple Pulmonary Nodules
Solitary Pulmonary Nodule
Humans
Retrospective Studies
Tomography, X-Ray Computed
Female
Reproducibility of Results
Aged
Aged, 80 and over
Truncated inception net: COVID-19 outbreak screening using chest X-rays.
Physical and engineering sciences in medicine
Jun 25, 2020
Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is spreading rapidly. AI-driven tools are used to identify Coronavirus outbreaks as wel...
Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.
European journal of radiology
Jun 25, 2020
PURPOSE: Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the ...
Automated Lung Ultrasound B-Line Assessment Using a Deep Learning Algorithm.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 15, 2020
Shortness of breath is a major reason that patients present to the emergency department (ED) and point-of-care ultrasound (POCUS) has been shown to aid in diagnosis, particularly through evaluation for artifacts known as B-lines. B-line identificatio...
A preliminary study to quantitatively evaluate the development of maturation degree for fetal lung based on transfer learning deep model from ultrasound images.
International journal of computer assisted radiology and surgery
Jun 15, 2020
PURPOSE: The evaluation of fetal lung maturity is critical for clinical practice since the lung immaturity is an important cause of neonatal morbidity and mortality. For the evaluation of the development of fetal lung maturation degree, our study est...
Deep learning in interstitial lung disease-how long until daily practice.
European radiology
Jun 14, 2020
Interstitial lung diseases are a diverse group of disorders that involve inflammation and fibrosis of interstitium, with clinical, radiological, and pathological overlapping features. These are an important cause of morbidity and mortality among lung...
Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT.
Radiology
May 26, 2020
Background Deep learning may help to improve computer-aided detection of volume (CADv) measurement of pulmonary nodules at chest CT. Purpose To determine the efficacy of a deep learning method for improving CADv for measuring the solid and ground-gla...
Multi-channel lung sound classification with convolutional recurrent neural networks.
Computers in biology and medicine
May 23, 2020
In this paper, we present an approach for multi-channel lung sound classification, exploiting spectral, temporal and spatial information. In particular, we propose a frame-wise classification framework to process full breathing cycles of multi-channe...
Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound.
IEEE transactions on medical imaging
May 14, 2020
Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scan...
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