AIMC Topic: Lung

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Machine vision analysis on abnormal respiratory conditions of mice inhaling particles containing cadmium.

Ecotoxicology and environmental safety Dec 18, 2018
Inhalable environmental toxicants can induce pulmonary malfunction resulting abnormal respiratory conditions. The traditional methods currently available to detect the respiratory condition of animals rely on differential pressure transducers and sig...
Male Lung Mice Machine Learning Animals Mice, Inbred Strains Cadmium Video Recording Respiration Inhalation Exposure Respiratory Function Tests Aerosols Particle Size Air Pollutants Particulate Matter Occupational Exposure Models, Theoretical Dose-Response Relationship, Drug
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Unsupervised pathology detection in medical images using conditional variational autoencoders.

International journal of computer assisted radiology and surgery Dec 12, 2018
PURPOSE: Pathology detection in medical image data is an important but a rather complicated task. In particular, the big variability of the pathologies is a challenge to automatic detection methods and even to machine learning methods. Supervised alg...
Algorithms Brain Neoplasms Lung Humans Machine Learning Area Under Curve Phantoms, Imaging Pathology Imaging, Three-Dimensional Image Processing, Computer-Assisted Glioblastoma
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Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

PloS one Dec 5, 2018
Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ult...
Child, Preschool Male Humans Image Processing, Computer-Assisted Child Infant Neural Networks, Computer Ultrasonography Pneumonia Lung
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High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains.

Medical physics Nov 28, 2018
PURPOSE: Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventional CT. In general, iterative reconstruction techniques have been applied to sparsely sampled CT to re...
Image Processing, Computer-Assisted Quality Control Radiation Dosage Tomography, X-Ray Computed Lung Deep Learning Wavelet Analysis Humans
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Convolutional neural network evaluation of over-scanning in lung computed tomography.

Diagnostic and interventional imaging Nov 27, 2018
INTRODUCTION: The purpose of this study was to develop a convolutional neural network (CNN) to determine the extent of over-scanning in the Z-direction associated with lung computed tomography (CT) examinations.
Lung Humans Machine Learning Neural Networks, Computer Tomography, X-Ray Computed Artificial Intelligence Sensitivity and Specificity
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Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs.

Radiology Nov 13, 2018
Purpose To assess the ability of convolutional neural networks (CNNs) to enable high-performance automated binary classification of chest radiographs. Materials and Methods In a retrospective study, 216 431 frontal chest radiographs obtained between ...
Humans Neural Networks, Computer Retrospective Studies Female Radiologists Male Radiographic Image Interpretation, Computer-Assisted Lung Radiography, Thoracic ROC Curve
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Wheeze type classification using non-dyadic wavelet transform based optimal energy ratio technique.

Computers in biology and medicine Nov 10, 2018
BACKGROUND AND OBJECTIVE: Wheezes in pulmonary sounds are anomalies which are often associated with obstructive type of lung diseases. The previous works on wheeze-type classification focused mainly on using fixed time-frequency/scale resolution base...
Wavelet Analysis Respiratory Sounds Support Vector Machine Signal Processing, Computer-Assisted Lung Diseases Humans Lung
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3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT.

IEEE journal of biomedical and health informatics Nov 9, 2018
Deep two-dimensional (2-D) convolutional neural networks (CNNs) have been remarkably successful in producing record-breaking results in a variety of computer vision tasks. It is possible to extend CNNs to three dimensions using 3-D kernels to make th...
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Lung Imaging, Three-Dimensional Lung Neoplasms
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A Lightweight Multi-Section CNN for Lung Nodule Classification and Malignancy Estimation.

IEEE journal of biomedical and health informatics Nov 6, 2018
The size and shape of a nodule are the essential indicators of malignancy in lung cancer diagnosis. However, effectively capturing the nodule's structural information from CT scans in a computer-aided system is a challenging task. Unlike previous mod...
Lung ROC Curve Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans
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Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks.

IEEE transactions on medical imaging Oct 26, 2018
Deformable image registration can be time consuming and often needs extensive parameterization to perform well on a specific application. We present a deformable registration method based on a 3-D convolutional neural network, together with a framewo...
Lung Neural Networks, Computer Imaging, Three-Dimensional Humans Algorithms Supervised Machine Learning Tomography, X-Ray Computed
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