AIMC Topic: Lung

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An effective approach for CT lung segmentation using mask region-based convolutional neural networks.

Artificial intelligence in medicine Jan 8, 2020
Computer vision systems have numerous tools to assist in various medical fields, notably in image diagnosis. Computed tomography (CT) is the principal imaging method used to assist in the diagnosis of diseases such as bone fractures, lung cancer, hea...
Image Processing, Computer-Assisted Lung Neoplasms Support Vector Machine Bayes Theorem Machine Learning Tomography, X-Ray Computed Lung Humans Neural Networks, Computer
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Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.

Medical physics Jan 1, 2020
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...
Humans Tomography, X-Ray Computed Lung Deep Learning Image Processing, Computer-Assisted Signal-To-Noise Ratio Spleen Thorax Dose-Response Relationship, Radiation Radiography, Dual-Energy Scanned Projection Kidney Abdomen Models, Theoretical Liver
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Semi-Supervised Learning for Semantic Segmentation of Emphysema With Partial Annotations.

IEEE journal of biomedical and health informatics Dec 31, 2019
Segmentation and quantification of each subtype of emphysema is helpful to monitor chronic obstructive pulmonary disease. Due to the nature of emphysema (diffuse pulmonary disease), it is very difficult for experts to allocate semantic labels to ever...
Humans Tomography, X-Ray Computed Female Supervised Machine Learning Male Emphysema Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted
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Survey on deep learning for pulmonary medical imaging.

Frontiers of medicine Dec 16, 2019
As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and d...
Lung Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging Humans Artificial Intelligence
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Deep segmentation networks predict survival of non-small cell lung cancer.

Scientific reports Nov 21, 2019
Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography/comp...
Neoplasm Staging Radiopharmaceuticals Datasets as Topic Radiosurgery Middle Aged Aged Lung Aged, 80 and over Deep Learning Survival Rate Carcinoma, Non-Small-Cell Lung Image Processing, Computer-Assisted Male Predictive Value of Tests Lung Neoplasms Humans Positron Emission Tomography Computed Tomography Prognosis Treatment Outcome Retrospective Studies Female
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A fast and scalable method for quality assurance of deformable image registration on lung CT scans using convolutional neural networks.

Medical physics Nov 19, 2019
PURPOSE: To develop and evaluate a method to automatically identify and quantify deformable image registration (DIR) errors between lung computed tomography (CT) scans for quality assurance (QA) purposes.
Humans Quality Control Four-Dimensional Computed Tomography Neural Networks, Computer Lung Time Factors Image Processing, Computer-Assisted
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CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms.

International journal of computer assisted radiology and surgery Nov 13, 2019
PURPOSE: As some of the most important factors for treatment decision of lung cancer (which is the deadliest neoplasm) are staging and histology, this work aimed to associate quantitative contrast-enhanced computed tomography (CT) features from malig...
Predictive Value of Tests Neoplasm Staging Humans Biopsy Machine Learning Neoplasm Metastasis Male Retrospective Studies Middle Aged Female Tomography, X-Ray Computed Lung ROC Curve Aged Lung Neoplasms Aged, 80 and over Adult
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Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.

Radiology Nov 12, 2019
Background Multicenter studies are required to validate the added benefit of using deep convolutional neural network (DCNN) software for detecting malignant pulmonary nodules on chest radiographs. Purpose To compare the performance of radiologists in...
Reproducibility of Results Aged Young Adult Adult Middle Aged Lung Lung Neoplasms Sensitivity and Specificity Male Humans Neural Networks, Computer Retrospective Studies Female Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic
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Prediction of pulmonary pressure after Glenn shunts by computed tomography-based machine learning models.

European radiology Nov 8, 2019
OBJECTIVES: This study aimed to develop non-invasive machine learning classifiers for predicting post-Glenn shunt patients with low and high risks of a mean pulmonary arterial pressure (mPAP) > 15 mmHg based on preoperative cardiac computed tomograph...
Pulmonary Artery Heart Septal Defects Univentricular Heart Pulmonary Atresia Tricuspid Atresia Cardiac Catheterization Transposition of Great Vessels Child Logistic Models Support Vector Machine Blood Pressure Double Outlet Right Ventricle Fontan Procedure Heart Defects, Congenital Bayes Theorem Infant Discriminant Analysis Lung Algorithms Adolescent Tomography, X-Ray Computed Prognosis Child, Preschool Female Retrospective Studies Young Adult Humans Male Machine Learning
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Novelties in imaging in pulmonary fibrosis and nodules. A narrative review.

Pulmonology Nov 7, 2019
In recent months two major fields of interest in pulmonary imaging have stood out: pulmonary fibrosis and pulmonary nodules. New guidelines have been released to define pulmonary fibrosis and subsequent studies have proved the value of these changes....
Lung Humans Lung Neoplasms Artificial Intelligence Multiple Pulmonary Nodules Algorithms Pulmonary Fibrosis Tomography, X-Ray Computed
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