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Lung

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Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.

Journal of digital imaging
Remarkable progress has been made in image classification and segmentation, due to the recent study of deep convolutional neural networks (CNNs). To solve the similar problem of diagnostic lung nodule detection in low-dose computed tomography (CT) sc...

Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.

Journal of digital imaging
Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest chal...

Computer-Aided Diagnosis of Pulmonary Fibrosis Using Deep Learning and CT Images.

Investigative radiology
OBJECTIVES: The objective of this study is to assess the performance of a computer-aided diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution computed tomography images into 4 radiological diagnostic categories a...

Lung Nodule Classification using A Novel Two-stage Convolutional Neural Networks Structure'.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lung cancer is one of the most fatal cancers in the world. If the lung cancer can be diagnosed at an early stage, the survival rate of patients post treatment increases dramatically. Computed Tomography (CT) diagram is an effective tool to detect lun...

Classification of radiographic lung pattern based on texture analysis and machine learning.

Journal of veterinary science
This study evaluated the feasibility of using texture analysis and machine learning to distinguish radiographic lung patterns. A total of 1200 regions of interest (ROIs) including four specific lung patterns (normal, alveolar, bronchial, and unstruct...

Deep Learning Applications in Chest Radiography and Computed Tomography: Current State of the Art.

Journal of thoracic imaging
Deep learning is a genre of machine learning that allows computational models to learn representations of data with multiple levels of abstraction using numerous processing layers. A distinctive feature of deep learning, compared with conventional ma...

Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.

Journal of X-ray science and technology
BACKGROUND: Deep learning has made spectacular achievements in analysing natural images, but it faces challenges for medical applications partly due to inadequate images.

Improving Detection of Early Chronic Obstructive Pulmonary Disease.

Annals of the American Thoracic Society
Despite being a major cause of morbidity and mortality, chronic obstructive pulmonary disease (COPD) is frequently undiagnosed. Yet the burden of disease among the undiagnosed is significant, as these individuals experience symptoms, exacerbations, a...

Pulmonary functional parameters and blood cotinine level in chronic obstructive pulmonary disease.

Tuberkuloz ve toraks
INTRODUCTION: Smoking is the leading cause of chronic obstructive pulmonary disease (COPD) and cotinine is reliable marker of tobacco exposure. We aimed to investigate the relationship between pulmonary function tests (FVC%, FEV1, FEV1/FVC and FEF25-...