AIMC Topic: Observer Variation

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Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound.

Head & neck Feb 4, 2019
BACKGROUND: We designed a deep convolutional neural network (CNN) to diagnose thyroid malignancy on ultrasound (US) and compared the diagnostic performance of CNN with that of experienced radiologists.
Female Adult Sensitivity and Specificity Male Middle Aged Humans Neural Networks, Computer Databases, Factual Retrospective Studies Neoplasm Invasiveness Area Under Curve Neoplasm Staging Observer Variation Ultrasonography, Doppler Cohort Studies Thyroid Neoplasms Thyroid Nodule ROC Curve Image Processing, Computer-Assisted
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Automated analysis of cardiovascular magnetic resonance myocardial native T mapping images using fully convolutional neural networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jan 14, 2019
BACKGROUND: Cardiovascular magnetic resonance (CMR) myocardial native T mapping allows assessment of interstitial diffuse fibrosis. In this technique, the global and regional T are measured manually by drawing region of interest in motion-corrected T...
Automation Male Prospective Studies Cardiovascular Diseases Female Humans Middle Aged Reproducibility of Results Deep Learning Aged Magnetic Resonance Imaging Adult Predictive Value of Tests Myocardium Workflow Image Interpretation, Computer-Assisted Observer Variation
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Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network.

AJR. American journal of roentgenology Oct 9, 2018
OBJECTIVE: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.
Child Radiography Elbow Joint Observer Variation Elbow Injuries Neural Networks, Computer Retrospective Studies Female Young Adult Sensitivity and Specificity Male Infant Diagnosis, Computer-Assisted Adolescent Child, Preschool Humans
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Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

NeuroImage Oct 6, 2018
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...
Multiple Sclerosis Humans Spinal Cord Neural Networks, Computer Observer Variation Reproducibility of Results Pattern Recognition, Automated Sensitivity and Specificity Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Determination of mammographic breast density using a deep convolutional neural network.

The British journal of radiology Oct 1, 2018
OBJECTIVE: High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue a...
Humans Neural Networks, Computer Retrospective Studies Female Aged ROC Curve Image Processing, Computer-Assisted Mammography Switzerland Breast Adult Breast Neoplasms Middle Aged Deep Learning Cohort Studies Observer Variation Precancerous Conditions Breast Density
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Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Sep 14, 2018
BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction ...
Reproducibility of Results Aged Male Ventricular Function, Left Stroke Volume Humans Middle Aged Observer Variation Neural Networks, Computer Deep Learning Automation Databases, Factual Predictive Value of Tests Magnetic Resonance Imaging, Cine Female Heart Diseases Ventricular Function, Right Image Interpretation, Computer-Assisted Myocardial Contraction
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Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology Sep 12, 2018
OBJECTIVES: To describe and validate an artificial intelligence (AI)-driven structured reporting system by direct comparison of automatically generated reports to results from actual clinical reports generated by nuclear cardiology experts.
Humans Sensitivity and Specificity Artificial Intelligence Retrospective Studies Observer Variation Male Female Tomography, Emission-Computed, Single-Photon Middle Aged Aged Myocardial Perfusion Imaging Diagnosis, Computer-Assisted Coronary Artery Disease
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Live remote digital microscopy in peripheral blood smear evaluation: Intraobserver concordance and experience.

International journal of laboratory hematology Aug 14, 2018
INTRODUCTION: Peripheral blood smear (PBS) review is a routine laboratory test which requires pathologist's interpretation when abnormal indices, atypical cells, or critical findings are identified. Real-time remote digital microscopy (DM) can potent...
Blood Cells Image Processing, Computer-Assisted Robotics Microscopy Observer Variation Humans Female Male
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Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.

Neuroradiology Jul 31, 2018
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for det...
Female Male Humans Infarction, Middle Cerebral Artery Aged Machine Learning Middle Aged Aged, 80 and over Software Predictive Value of Tests Adult Brain Ischemia Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Observer Variation Stroke Alberta
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A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging Jul 21, 2018
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...
Aged Adult Male Middle Aged Deep Learning Neural Networks, Computer Databases, Factual Prospective Studies Retrospective Studies Observer Variation Female Fourier Analysis ROC Curve Humans Image Processing, Computer-Assisted Support Vector Machine Magnetic Resonance Imaging Signal Processing, Computer-Assisted
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