AIMC Topic: Lung

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An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.

Computer methods and programs in biomedicine Jun 6, 2019
BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection and diagnosis of pulmonary diseases. A critical component in any computer-aided system, for either detection or diagnosis in digital CXR, is the auto...
Humans Neural Networks, Computer Algorithms Databases, Factual Image Processing, Computer-Assisted Tuberculosis, Pulmonary Pattern Recognition, Automated Radiography, Thoracic Reproducibility of Results Sensitivity and Specificity Lung Diagnosis, Computer-Assisted
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Neural network model of an amphibian ventilatory central pattern generator.

Journal of computational neuroscience May 22, 2019
The neuronal multiunit model presented here is a formal model of the central pattern generator (CPG) of the amphibian ventilatory neural network, inspired by experimental data from Pelophylax ridibundus. The kernel of the CPG consists of three pacema...
Neural Networks, Computer Animals Lung Metamorphosis, Biological Central Pattern Generators Motor Neurons Biological Clocks Neurons Synapses Acidosis Neural Inhibition Cheek Electrophysiological Phenomena Ganglia, Invertebrate Amphibians Ranidae
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Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society May 2, 2019
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...
Prognosis Child Tomography, X-Ray Computed Cystic Fibrosis Pediatrics Female Radiography, Thoracic Reproducibility of Results Male Lung Severity of Illness Index Deep Learning Humans Neural Networks, Computer Research Design
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Automated pulmonary nodule detection in CT images using 3D deep squeeze-and-excitation networks.

International journal of computer assisted radiology and surgery Apr 26, 2019
PURPOSE: Pulmonary nodule detection has great significance for early treating lung cancer and increasing patient survival. This work presents a novel automated computer-aided detection scheme for pulmonary nodules based on deep convolutional neural n...
Humans Lung Neoplasms Neural Networks, Computer Solitary Pulmonary Nodule Tomography, X-Ray Computed Lung Imaging, Three-Dimensional
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Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.

IEEE transactions on medical imaging Apr 23, 2019
Edges tend to be over-smoothed in total variation (TV) regularized under-sampled images. In this paper, symmetric residual convolutional neural network (SR-CNN), a deep learning based model, was proposed to enhance the sharpness of edges and detailed...
Lung Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Lung Neoplasms Phantoms, Imaging Humans Algorithms
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Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist Apr 17, 2019
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...
Humans Neural Networks, Computer Deep Learning Female ROC Curve Male Algorithms Lung Neoplasms Middle Aged Databases, Factual Radiographic Image Interpretation, Computer-Assisted Lung Retrospective Studies Tomography, X-Ray Computed
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Lungs nodule detection framework from computed tomography images using support vector machine.

Microscopy research and technique Apr 11, 2019
The emergence of cloud infrastructure has the potential to provide significant benefits in a variety of areas in the medical imaging field. The driving force behind the extensive use of cloud infrastructure for medical image processing is the exponen...
False Positive Reactions Image Processing, Computer-Assisted Lung Neoplasms Support Vector Machine Humans Tomography, X-Ray Computed Sensitivity and Specificity Lung
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Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study.

The Lancet. Respiratory medicine Apr 1, 2019
BACKGROUND: In the appropriate clinical setting, the diagnosis of idiopathic pulmonary fibrosis (IPF) requires a pattern of usual interstitial pneumonia to be present on high-resolution chest CT (HRCT) or surgical lung biopsy. A molecular usual inter...
Biopsy Lung Idiopathic Pulmonary Fibrosis Diagnosis, Differential Predictive Value of Tests Prospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Sensitivity and Specificity Male Middle Aged Humans Machine Learning Algorithms
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Application of deep learning-based computer-aided detection system: detecting pneumothorax on chest radiograph after biopsy.

European radiology Mar 26, 2019
OBJECTIVES: To retrospectively evaluate the diagnostic performance of a convolutional neural network (CNN) model in detecting pneumothorax on chest radiographs obtained after percutaneous transthoracic needle biopsy (PTNB) for pulmonary lesions.
Biopsy, Needle Female Lung Humans Diagnosis, Computer-Assisted Sensitivity and Specificity Drainage Pneumothorax Neural Networks, Computer Male Deep Learning Area Under Curve Retrospective Studies ROC Curve Middle Aged Radiography Image-Guided Biopsy
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Deep learning-based super-resolution in coherent imaging systems.

Scientific reports Mar 8, 2019
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and diffraction-lim...
Software Image Enhancement Papanicolaou Test Female Holography Vaginal Smears Humans Lung Equipment Design Neural Networks, Computer Microscopy Deep Learning
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