AIMC Topic: Diagnostic Imaging

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The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Emergency radiology Jul 8, 2020
Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly disc...
Artificial Intelligence United States Triage Humans Radiology United States Food and Drug Administration Emergency Service, Hospital Diagnostic Imaging
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Neural networks-based regularization for large-scale medical image reconstruction.

Physics in medicine and biology Jul 6, 2020
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Learning methods using iterative neural networks (NNs) and cascaded NNs ha...
Neural Networks, Computer Cone-Beam Computed Tomography Humans Radiation Dosage Image Processing, Computer-Assisted Signal-To-Noise Ratio Phantoms, Imaging Diagnostic Imaging Artifacts
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Radiomics in liver diseases: Current progress and future opportunities.

Liver international : official journal of the International Association for the Study of the Liver Jul 2, 2020
Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have become an increasingly significant health problem worldwide. Noninvasive imaging plays a critical role in the clinical workflow of liver diseases, but conventional ima...
Diagnostic Imaging Humans Machine Learning Forecasting Liver Neoplasms Algorithms
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Current Landscape of Imaging and the Potential Role for Artificial Intelligence in the Management of COVID-19.

Current problems in diagnostic radiology Jun 27, 2020
The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging m...
Diagnostic Imaging Image Interpretation, Computer-Assisted Humans COVID-19 Artificial Intelligence SARS-CoV-2
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Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis.

Medical image analysis Jun 20, 2020
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However, the impact of label noise has not received sufficient attention. Rec...
Machine Learning Deep Learning Humans Observer Variation Image Processing, Computer-Assisted Diagnostic Imaging
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Local rotation invariance in 3D CNNs.

Medical image analysis Jun 20, 2020
Locally Rotation Invariant (LRI) image analysis was shown to be fundamental in many applications and in particular in medical imaging where local structures of tissues occur at arbitrary rotations. LRI constituted the cornerstone of several breakthro...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Diagnostic Imaging
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Optical techniques, computed tomography and deep learning role in the diagnosis of COVID-19 pandemic towards increasing the survival rate of vulnerable populations.

Photodiagnosis and photodynamic therapy Jun 17, 2020
• Severe lung complications can be explored using computed tomography during COVID-19 pandemic. • Ultra-low dose CT can enhance COVID-19 infected patients diagnostic capability. • Optically monitored CT along with deep learning is the best solution f...
Severe Acute Respiratory Syndrome Pneumonia, Viral COVID-19 Tomography, X-Ray Computed Quality Improvement Optical Devices Role Male Humans Coronavirus Infections Female Clinical Laboratory Techniques Vulnerable Populations Deep Learning COVID-19 Testing Pandemics Radiographic Image Enhancement Diagnostic Imaging Survival Analysis
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Concept attribution: Explaining CNN decisions to physicians.

Computers in biology and medicine Jun 17, 2020
Deep learning explainability is often reached by gradient-based approaches that attribute the network output to perturbations of the input pixels. However, the relevance of input pixels may be difficult to relate to relevant image features in some ap...
Diagnostic Imaging Neural Networks, Computer Physicians Humans
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Artificial intelligence: improving the efficiency of cardiovascular imaging.

Expert review of medical devices Jun 16, 2020
INTRODUCTION: Artificial intelligence (AI) describes the use of computational techniques to mimic human intelligence. In healthcare, this typically involves large medical datasets being used to predict a diagnosis, identify new disease genotypes or p...
Precision Medicine Cardiovascular Diseases Machine Learning Software Diagnostic Imaging Humans Artificial Intelligence
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Introduction to deep learning: minimum essence required to launch a research.

Japanese journal of radiology Jun 15, 2020
In the present article, we provide an overview on the basics of deep learning in terms of technical aspects and steps required to launch a deep learning research. Deep learning is a branch of artificial intelligence, which has been attracting interes...
Machine Learning Deep Learning Diagnostic Imaging Humans Artificial Intelligence
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