AIMC Topic: Tomography, X-Ray Computed

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A New Approach for Automated Image Segmentation of Organs at Risk in Cervical Cancer.

Radiology. Imaging cancer Mar 27, 2020
Uterine Cervical Neoplasms Deep Learning Organs at Risk Humans Neural Networks, Computer Tomography, X-Ray Computed Female
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Deep learning-based attenuation map generation for myocardial perfusion SPECT.

European journal of nuclear medicine and molecular imaging Mar 26, 2020
PURPOSE: Attenuation correction using CT transmission scanning increases the accuracy of single-photon emission computed tomography (SPECT) and enables quantitative analysis. Current existing SPECT-only systems normally do not support transmission sc...
Perfusion Artifacts Tomography, Emission-Computed, Single-Photon Humans Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Automatic 3D landmarking model using patch-based deep neural networks for CT image of oral and maxillofacial surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS Mar 20, 2020
BACKGROUND: Manual landmarking is a time consuming and highly professional work. Although some algorithm-based landmarking methods have been proposed, they lack flexibility and may be susceptible to data diversity.
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Surgery, Oral
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Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

Clinical cancer research : an official journal of the American Association for Cancer Research Mar 20, 2020
PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of tumors to nivolumab, docetaxel, and gefitinib.
Disease Progression Lung Neoplasms Antineoplastic Combined Chemotherapy Protocols Carcinoma, Non-Small-Cell Lung Female Survival Rate Male Clinical Trials, Phase III as Topic Gefitinib Randomized Controlled Trials as Topic Clinical Trials, Phase II as Topic Nivolumab Docetaxel Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed
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Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning.

La Radiologia medica Mar 19, 2020
PURPOSE: To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cell renal cell carcinoma (ccRCC) grade.
Radiographic Image Interpretation, Computer-Assisted Female Kidney Neoplasms Male Humans Carcinoma, Renal Cell Middle Aged Machine Learning Neoplasm Grading Tomography, X-Ray Computed
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Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.

Radiology Mar 19, 2020
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to...
Pneumonia, Viral Aged Adult Community-Acquired Infections Diagnosis, Differential Sensitivity and Specificity Artificial Intelligence Humans Clinical Laboratory Techniques Pandemics Male Tomography, X-Ray Computed Betacoronavirus Middle Aged Radiographic Image Interpretation, Computer-Assisted COVID-19 Female Coronavirus Infections Deep Learning Retrospective Studies SARS-CoV-2 COVID-19 Testing ROC Curve Imaging, Three-Dimensional
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Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.

Medical physics Mar 18, 2020
PURPOSE: Multiview two-dimensional (2D) convolutional neural networks (CNNs) and three-dimensional (3D) CNNs have been successfully used for analyzing volumetric data in many state-of-the-art medical imaging applications. We propose an alternative mo...
Image Processing, Computer-Assisted Lung Neoplasms False Positive Reactions Radiography, Thoracic Humans Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity
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Artificial intelligence and machine learning in respiratory medicine.

Expert review of respiratory medicine Mar 17, 2020
: The application of artificial intelligence (AI) and machine learning (ML) in medicine and in particular in respiratory medicine is an increasingly relevant topic.: We aimed to identify and describe the studies published on the use of AI and ML in t...
Tomography, X-Ray Computed Pulmonary Disease, Chronic Obstructive Pulmonary Fibrosis Respiratory Tract Diseases Pulmonary Medicine Humans Artificial Intelligence Machine Learning
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Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

European radiology Mar 12, 2020
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Humans Machine Learning Fractional Flow Reserve, Myocardial Cohort Studies Disease Management Coronary Angiography Retrospective Studies Aged Cardiac Catheterization Percutaneous Coronary Intervention Tomography, X-Ray Computed Male Computed Tomography Angiography Coronary Artery Disease Female Middle Aged Coronary Stenosis Hemodynamics
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Artificial intelligence and radiomics enhance the positive predictive value of digital chest tomosynthesis for lung cancer detection within SOS clinical trial.

European radiology Mar 12, 2020
OBJECTIVE: To enhance the positive predictive value (PPV) of chest digital tomosynthesis (DTS) in the lung cancer detection with the analysis of radiomics features.
Machine Learning Algorithms Tomography, X-Ray Computed Reproducibility of Results Humans Neural Networks, Computer Logistic Models Artificial Intelligence Aged Early Detection of Cancer Middle Aged Radiology Image Processing, Computer-Assisted Semantics Lung Neoplasms
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