AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions.

Japanese journal of radiology Oct 10, 2020
PURPOSE: To determine the image quality improvement including vascular structures using deep learning reconstruction (DLR) for ultra-high-resolution CT (UHR-CT) and area-detector CT (ADCT) compared to a commercially available hybrid-iterative reconst...
Kidney Abdomen Radiographic Image Interpretation, Computer-Assisted Quality Improvement Kidney Neoplasms Male Middle Aged Deep Learning In Vitro Techniques Carcinoma, Renal Cell Arteries Algorithms Tomography, X-Ray Computed Female Humans
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Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning-based computer-assisted detection.

Neuroradiology Oct 6, 2020
PURPOSE: To elucidate the effect of deep learning-based computer-assisted detection (CAD) on the performance of different-level physicians in detecting intracranial haemorrhage using CT.
Diagnosis, Computer-Assisted Deep Learning Radiographic Image Interpretation, Computer-Assisted Intracranial Hemorrhages Computers Retrospective Studies Tomography, X-Ray Computed Sensitivity and Specificity Humans
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The Clinical Application of the Deep Learning Technique for Predicting Trigger Origins in Patients With Paroxysmal Atrial Fibrillation With Catheter Ablation.

Circulation. Arrhythmia and electrophysiology Oct 6, 2020
BACKGROUND: Non-pulmonary vein (NPV) trigger has been reported as an important predictor of recurrence post-atrial fibrillation ablation. Elimination of NPV triggers can reduce the recurrence of postablation atrial fibrillation. Deep learning was app...
Risk Assessment Deep Learning Time Factors Treatment Outcome Action Potentials Aged Adult Male Middle Aged Catheter Ablation Recurrence Computed Tomography Angiography Phlebography Pulmonary Veins Female Predictive Value of Tests Reproducibility of Results Risk Factors Humans Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Atrial Fibrillation Heart Rate
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Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.

JAMA network open Oct 1, 2020
IMPORTANCE: Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with automated preliminary read assistants could help expedite their workflows, improve accuracy, and redu...
Algorithms ROC Curve Area Under Curve Radiography Radiographic Image Interpretation, Computer-Assisted Humans Artificial Intelligence Quality of Health Care Thorax Internship and Residency
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Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

Physics in medicine and biology Sep 28, 2020
We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation t...
Weight Loss Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Radiotherapy, Intensity-Modulated Acute-Phase Reaction Aged, 80 and over Humans Adult Male Middle Aged Machine Learning Retrospective Studies Algorithms Tomography, X-Ray Computed Female Aged
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Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence.

Radiology Sep 24, 2020
Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more challenging to differentiate coronavirus disease 2019 (COVID-19) pneumonia from non-COVID-19 pneumonia o...
Young Adult Adult Sensitivity and Specificity Male Artificial Intelligence Humans Radiography, Thoracic COVID-19 Female Middle Aged Retrospective Studies SARS-CoV-2 Lung Aged Adolescent Aged, 80 and over Radiographic Image Interpretation, Computer-Assisted
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The use of artificial intelligence in computed tomography image reconstruction - A literature review.

Journal of medical imaging and radiation sciences Sep 24, 2020
BACKGROUND AND PURPOSE: The use of AI in the process of CT image reconstruction may improve image quality of resultant images and therefore facilitate low-dose CT examinations.
Humans Artificial Intelligence Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted
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Convolutional neural networks versus radiologists in characterization of small hypoattenuating hepatic nodules on CT: a critical diagnostic challenge in staging of colorectal carcinoma.

Scientific reports Sep 17, 2020
Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional neural networks (CNN) to radiologists in characterizing small hypoattenuating hepatic nodules (SHHN) in colorectal carcinoma (CRC) on CT scans. Retrosp...
Diagnosis, Computer-Assisted Liver Neoplasms Liver Neoplasm Staging Adult Humans Observer Variation Female Radiologists Colorectal Neoplasms Expert Testimony Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Aged Male Retrospective Studies Aged, 80 and over Middle Aged Tomography, X-Ray Computed Young Adult
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Contrastive Cross-Site Learning With Redesigned Net for COVID-19 CT Classification.

IEEE journal of biomedical and health informatics Sep 10, 2020
The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous growth of new infections, developing automated tools for COVID-19 identification with CT image is highl...
Humans Radiographic Image Interpretation, Computer-Assisted Coronavirus Infections COVID-19 Testing Deep Learning Betacoronavirus Tomography, X-Ray Computed Clinical Laboratory Techniques Computer Systems Pneumonia, Viral Machine Learning Pandemics Computational Biology SARS-CoV-2 COVID-19 Databases, Factual
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Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Aug 31, 2020
Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to growing demands for rapid and accurate diagnostic reporting. In modern breast imaging centers, full-fiel...
Image Interpretation, Computer-Assisted Mammography Humans Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Ultrasonography, Mammary Female Breast Breast Neoplasms
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