AIMC Topic: Tomography, X-Ray Computed

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A machine-learning based approach to quantify fine crackles in the diagnosis of interstitial pneumonia: A proof-of-concept study.

Medicine Feb 19, 2021
Fine crackles are frequently heard in patients with interstitial lung diseases (ILDs) and are known as the sensitive indicator for ILDs, although the objective method for analyzing respiratory sounds including fine crackles is not clinically availabl...
Aged Aged, 80 and over Male Middle Aged Algorithms Tomography, X-Ray Computed Female Lung Diseases, Interstitial Radiography, Thoracic Auscultation Respiratory Sounds Disease Progression Lung Idiopathic Pulmonary Fibrosis Humans Machine Learning
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Integrity of clinical information in radiology reports documenting pulmonary nodules.

Journal of the American Medical Informatics Association : JAMIA Jan 15, 2021
OBJECTIVE: Quantify the integrity, measured as completeness and concordance with a thoracic radiologist, of documenting pulmonary nodule characteristics in CT reports and assess impact on making follow-up recommendations.
Humans Retrospective Studies Solitary Pulmonary Nodule Natural Language Processing Documentation Radiology Information Systems Radiography, Thoracic Aged Tomography, X-Ray Computed Middle Aged Male Electronic Health Records Multiple Pulmonary Nodules Female
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[Effect of Automatic Extraction Accuracy by Different Image Reconstruction Methods Using a Three-dimensional Image Analysis System for Pulmonary Segmentectomy Preoperative CT Angiography].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2021
This study aimed to determine the optimal image reconstruction method for preoperative computed tomography (CT) angiography for pulmonary segmentectomy. This study enrolled 20 patients who underwent contrast-enhanced CT examination for pulmonary segm...
Pneumonectomy Deep Learning Radiation Dosage Imaging, Three-Dimensional Computed Tomography Angiography Humans Angiography Radiographic Image Interpretation, Computer-Assisted Algorithms Vena Cava, Superior Tomography, X-Ray Computed
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[Forefront of AI Applications for COVID-19 Imaging Diagnosis].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics Jan 1, 2021
The intra- and inter-observer variability in diagnosis of thoracic CT images may affect the diagnosis of COVID-19. Therefore, several studies have been reported to develop artificial intelligence (AI) approaches using deep learning (DL) and radiomics...
Deep Learning Humans Artificial Intelligence COVID-19 Tomography, X-Ray Computed SARS-CoV-2
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Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery.

Technology in cancer research & treatment Jan 1, 2021
The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a deep learning algorithm for Gamma Knife (GK) stereotactic radiosurgery (SRS). The Monte Carlo (MC) m...
Humans Radiosurgery Monte Carlo Method Neural Networks, Computer Prognosis Radiotherapy Planning, Computer-Assisted Magnetic Resonance Imaging Deep Learning Retrospective Studies Radiotherapy Dosage Organs at Risk Phantoms, Imaging Image Processing, Computer-Assisted Tomography, X-Ray Computed Radiotherapy, Intensity-Modulated Neoplasms
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Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.

Journal of X-ray science and technology Jan 1, 2021
OBJECTIVE: To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with usi...
Algorithms Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Image Processing, Computer-Assisted Liver Humans
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Differentiation of Intrahepatic Cholangiocarcinoma and Hepatic Lymphoma Based on Radiomics and Machine Learning in Contrast-Enhanced Computer Tomography.

Technology in cancer research & treatment Jan 1, 2021
This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). A total of 28 patients with HL and 101 patients with ICCA were...
Cholangiocarcinoma Male Radiographic Image Enhancement Middle Aged Neoplasm Grading ROC Curve Tumor Burden Contrast Media Bile Duct Neoplasms Diagnosis, Differential Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed Lymphoma Machine Learning Female Algorithms Reproducibility of Results Aged
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Analysis of segmentation of lung parenchyma based on deep learning methods.

Journal of X-ray science and technology Jan 1, 2021
Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to detail...
Deep Learning Image Processing, Computer-Assisted Thorax Tomography, X-Ray Computed Lung
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Clinical Target Volume Auto-Segmentation of Esophageal Cancer for Radiotherapy After Radical Surgery Based on Deep Learning.

Technology in cancer research & treatment Jan 1, 2021
Radiotherapy plays an important role in controlling the local recurrence of esophageal cancer after radical surgery. Segmentation of the clinical target volume is a key step in radiotherapy treatment planning, but it is time-consuming and operator-de...
Automation Image Processing, Computer-Assisted Esophageal Neoplasms Radiotherapy Planning, Computer-Assisted Tomography, X-Ray Computed Deep Learning Humans Neural Networks, Computer
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Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Advances in experimental medicine and biology Jan 1, 2021
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into...
Humans COVID-19 Retrospective Studies Deep Learning Iran Tomography, X-Ray Computed SARS-CoV-2 Lung
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