AIMC Topic: Radiography, Thoracic

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Deep Learning for Detection of Elevated Pulmonary Artery Wedge Pressure Using Standard Chest X-Ray.

The Canadian journal of cardiology Feb 18, 2021
BACKGROUND: To accurately diagnose and control heart failure (HF), it is important to carry out a simple assessment of elevated pulmonary arterial wedge pressure (PAWP). The aim of this study was to develop and validate an objective method for detect...
Humans Algorithms Prospective Studies Female Radiography, Thoracic Deep Learning Aged Cardiac Catheterization Datasets as Topic Pulmonary Wedge Pressure Natriuretic Peptide, Brain Male Echocardiography
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DON: Deep Learning and Optimization-Based Framework for Detection of Novel Coronavirus Disease Using X-ray Images.

Interdisciplinary sciences, computational life sciences Feb 15, 2021
In the hospital, a limited number of COVID-19 test kits are available due to the spike in cases every day. For this reason, a rapid alternative diagnostic option should be introduced as an automated detection method to prevent COVID-19 spreading amon...
Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Deep Learning Decision Trees Predictive Value of Tests Lung Diagnosis, Computer-Assisted Humans COVID-19 Reproducibility of Results
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Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study.

Journal of medical Internet research Feb 10, 2021
BACKGROUND: COVID-19 has spread very rapidly, and it is important to build a system that can detect it in order to help an overwhelmed health care system. Many research studies on chest diseases rely on the strengths of deep learning techniques. Alth...
Humans SARS-CoV-2 Deep Learning Radiography, Thoracic Neural Networks, Computer COVID-19 Algorithms Thorax Thoracic Diseases
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Unsupervised Deep Anomaly Detection in Chest Radiographs.

Journal of digital imaging Feb 8, 2021
The purposes of this study are to propose an unsupervised anomaly detection method based on a deep neural network (DNN) model, which requires only normal images for training, and to evaluate its performance with a large chest radiograph dataset. We u...
Radiologists Radiography, Thoracic Middle Aged ROC Curve Radiography Humans Neural Networks, Computer Female Male
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COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network.

IEEE journal of biomedical and health informatics Feb 5, 2021
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread rapidly since December 2019. Real-time reverse transcription polymerase chain reaction (rRT-PCR) and chest computed tomography (CT) imaging both play an important role ...
Humans Lung COVID-19 Tomography, X-Ray Computed Deep Learning SARS-CoV-2 Radiography, Thoracic
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Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.

European radiology experimental Feb 2, 2021
BACKGROUND: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (CXR) on a cohort of subjects from two hospitals in Lombardy, Italy.
Radiography, Thoracic X-Rays Lung Italy Radiographic Image Interpretation, Computer-Assisted Female Reproducibility of Results SARS-CoV-2 Machine Learning Aged COVID-19 Humans Male Retrospective Studies Middle Aged
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Discriminative Feature Learning for Thorax Disease Classification in Chest X-ray Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Feb 1, 2021
This paper focuses on the thorax disease classification problem in chest X-ray (CXR) images. Different from the generic image classification task, a robust and stable CXR image analysis system should consider the unique characteristics of CXR images....
Radiographic Image Interpretation, Computer-Assisted Humans Lung Diseases Deep Learning Radiography, Thoracic
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Extracting and Learning Fine-Grained Labels from Chest Radiographs.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Chest radiographs are the most common diagnostic exam in emergency rooms and intensive care units today. Recently, a number of researchers have begun working on large chest X-ray datasets to develop deep learning models for recognition of a handful o...
Radiographic Image Interpretation, Computer-Assisted Machine Learning Humans Diagnosis, Computer-Assisted Pattern Recognition, Automated Thorax Neural Networks, Computer Deep Learning Radiography, Thoracic
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Artificial Intelligence-assisted chest X-ray assessment scheme for COVID-19.

European radiology Jan 20, 2021
OBJECTIVES: To study whether a trained convolutional neural network (CNN) can be of assistance to radiologists in differentiating Coronavirus disease (COVID)-positive from COVID-negative patients using chest X-ray (CXR) through an ambispective clinic...
Radiography, Thoracic COVID-19 X-Rays Tomography, X-Ray Computed Humans SARS-CoV-2 Artificial Intelligence
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Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs.

Academic radiology Jan 18, 2021
RATIONALE AND OBJECTIVES: Radiographic findings of COVID-19 pneumonia can be used for patient risk stratification; however, radiologist reporting of disease severity is inconsistent on chest radiographs (CXRs). We aimed to see if an artificial intell...
Severity of Illness Index Humans Retrospective Studies Radiologists Artificial Intelligence SARS-CoV-2 Radiography, Thoracic COVID-19 Lung
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