AI Medical Compendium Topic:
Lung

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Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume.

International journal of computer assisted radiology and surgery
PURPOSE: Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3...

Unsupervised class labeling of diffuse lung diseases using frequent attribute patterns.

International journal of computer assisted radiology and surgery
PURPOSE: For realizing computer-aided diagnosis (CAD) of computed tomography (CT) images, many pattern recognition methods have been applied to automatic classification of normal and abnormal opacities; however, for the learning of accurate classifie...

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network.

IEEE transactions on medical imaging
Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep l...

Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines.

IEEE transactions on medical imaging
The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning m...

Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity.

BioMed research international
The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) s...

Neural hypernetwork approach for pulmonary embolism diagnosis.

BMC research notes
BACKGROUND: Hypernetworks are based on topological simplicial complexes and generalize the concept of two-body relation to many-body relation. Furthermore, Hypernetworks provide a significant generalization of network theory, enabling the integration...

Histopathological Image Classification Using Discriminative Feature-Oriented Dictionary Learning.

IEEE transactions on medical imaging
In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an aut...

Capnodynamic assessment of effective lung volume during cardiac output manipulations in a porcine model.

Journal of clinical monitoring and computing
A capnodynamic calculation of effective pulmonary blood flow includes a lung volume factor (ELV) that has to be estimated to solve the mathematical equation. In previous studies ELV correlated to reference methods for functional residual capacity (FR...

Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU.

Respiratory care
BACKGROUND: Twenty-five to 40% of patients pass a spontaneous breathing trial (SBT) but fail to wean from mechanical ventilation. There is no single appropriate and convenient predictor or method that can help clinicians to accurately predict weaning...

Detection of abnormalities in ultrasound lung image using multi-level RVM classification.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
The classification of abnormalities in ultrasound images is the monitoring tool of fluid to air passage in the lung. In this study, the adaptive median filtering technique is employed for the preprocessing step. The preprocessed image is then extract...