AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Deep learning applied to automatic disease detection using chest X-rays.
Journal of medical imaging and radiation oncology
Jul 6, 2021
Deep learning (DL) has shown rapid advancement and considerable promise when applied to the automatic detection of diseases using CXRs. This is important given the widespread use of CXRs across the world in diagnosing significant pathologies, and the...
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.
The Lancet. Digital health
Jul 1, 2021
BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretati...
ROC Curve
Thoracic Neoplasms
Mass Screening
Middle Aged
Deep Learning
Adolescent
Models, Biological
Radiography, Thoracic
Infections
X-Rays
Area Under Curve
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
Humans
Adult
Female
Aged, 80 and over
Artificial Intelligence
Aged
Male
Young Adult
Thoracic Injuries
Artificial intelligence in medical imaging: implications for patient radiation safety.
The British journal of radiology
Jun 23, 2021
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic ...
Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.
Journal of applied clinical medical physics
Jun 23, 2021
PURPOSE: In an ultrahigh-resolution CT (U-HRCT), deep learning-based reconstruction (DLR) is expected to drastically reduce image noise without degrading spatial resolution. We assessed a new algorithm's effect on image quality at different radiation...
Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.
European radiology
Jun 15, 2021
OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images rec...
Effect of deep learning image reconstruction in the prediction of resectability of pancreatic cancer: Diagnostic performance and reader confidence.
European journal of radiology
Jun 11, 2021
OBJECTIVE: To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT) using a new deep learning image reconstruction (DLIR) algorithm.
A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification.
The British journal of radiology
Jun 11, 2021
OBJECTIVES: To compare the diagnostic performance of a newly developed artificial intelligence (AI) algorithm derived from the fusion of convolution neural networks (CNN) versus human observers in the estimation of malignancy risk in pulmonary nodule...
Dental enumeration and multiple treatment detection on panoramic X-rays using deep learning.
Scientific reports
Jun 11, 2021
In this paper, a new powerful deep learning framework, named as DENTECT, is developed in order to instantly detect five different dental treatment approaches and simultaneously number the dentition based on the FDI notation on panoramic X-ray images....
Clinical evaluation of a phantom-based deep convolutional neural network for whole-body-low-dose and ultra-low-dose CT skeletal surveys.
Skeletal radiology
Jun 10, 2021
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.
COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.
PloS one
Jun 7, 2021
Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrained environments, and a computer-aided detection system (CAD) that can identify pneumonia on CXR may help the triage of patients in those environment ...
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