AIMC Topic: Lung
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Lung Nodule Detection from Feature Engineering to Deep Learning in Thoracic CT Images: a Comprehensive Review.
Journal of digital imaging
Jun 1, 2020
This paper presents a systematic review of the literature focused on the lung nodule detection in chest computed tomography (CT) images. Manual detection of lung nodules by the radiologist is a sequential and time-consuming process. The detection is ...
Machine Learning/Deep Neuronal Network: Routine Application in Chest Computed Tomography and Workflow Considerations.
Journal of thoracic imaging
May 1, 2020
The constantly increasing number of computed tomography (CT) examinations poses major challenges for radiologists. In this article, the additional benefits and potential of an artificial intelligence (AI) analysis platform for chest CT examinations i...
Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers.
Journal of thoracic imaging
May 1, 2020
OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Globa...
Pulmonary Disease, Chronic Obstructive
Male
Middle Aged
Aged, 80 and over
Young Adult
Adult
Pulmonary Emphysema
Radiography, Thoracic
Smokers
Lung
Severity of Illness Index
Radiographic Image Interpretation, Computer-Assisted
Humans
Artificial Intelligence
Female
Aged
Retrospective Studies
Tomography, X-Ray Computed
Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases.
Fa yi xue za zhi
Apr 1, 2020
Objective To discuss the application of artificial intelligence automatic diatom identification system in practical cases, to provide reference for quantitative diatom analysis using the system and to validate the deep learning model incorporated int...
Classification of CT Scan Images of Lungs Using Deep Convolutional Neural Network with External Shape-Based Features.
Journal of digital imaging
Feb 1, 2020
In this paper, a simplified yet efficient architecture of a deep convolutional neural network is presented for lung image classification. The images used for classification are computed tomography (CT) scan images obtained from two scientifically use...
Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography.
Current medical imaging
Jan 1, 2020
OBJECTIVE: False-positive nodule reduction is a crucial part of a computer-aided detection (CADe) system, which assists radiologists in accurate lung nodule detection. In this research, a novel scheme using multi-level 3D DenseNet framework is propos...
AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images.
IEEE pulse
Jan 1, 2020
Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantitative analysis makes radiology reporting much more comprehensive. To that end, several research group...
Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.
Journal of X-ray science and technology
Jan 1, 2020
OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease.
Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.
Journal of X-ray science and technology
Jan 1, 2020
OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated dete...
Deep learning-based CAD schemes for the detection and classification of lung nodules from CT images: A survey.
Journal of X-ray science and technology
Jan 1, 2020
BACKGROUND: Lung cancer is the most common cancer in the world. Computed tomography (CT) is the standard medical imaging modality for early lung nodule detection and diagnosis that improves patient's survival rate. Recently, deep learning algorithms,...
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