AIMC Topic: Thorax

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Coarse-to-fine airway segmentation using multi information fusion network and CNN-based region growing.

Computer methods and programs in biomedicine Jan 8, 2022
BACKGROUND AND OBJECTIVES: Automatic airway segmentation from chest computed tomography (CT) scans plays an important role in pulmonary disease diagnosis and computer-assisted therapy. However, low contrast at peripheral branches and complex tree-lik...
Lung Image Processing, Computer-Assisted Thorax Neural Networks, Computer Tomography, X-Ray Computed
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Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics.

Computer methods and programs in biomedicine Dec 20, 2021
BACKGROUND AND OBJECTIVE: To study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer.
Retrospective Studies Tomography, X-Ray Computed Image Processing, Computer-Assisted Humans Neural Networks, Computer Lung Neoplasms Thorax
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TBNet: a context-aware graph network for tuberculosis diagnosis.

Computer methods and programs in biomedicine Dec 16, 2021
Tuberculosis (TB) is an infectious bacterial disease. It can affect the human lungs, brain, bones, and kidneys. Pulmonary tuberculosis is the most common. This airborne bacterium can be transmitted with the droplets by coughing and sneezing. So far, ...
Tomography, X-Ray Computed Diagnosis, Computer-Assisted Humans Tuberculosis Neural Networks, Computer Thorax
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Deep multi-instance transfer learning for pneumothorax classification in chest X-ray images.

Medical physics Dec 7, 2021
PURPOSE: Pneumothorax is a life-threatening emergency that requires immediate treatment. Frontal-view chest X-ray images are typically used for pneumothorax detection in clinical practice. However, manual review of radiographs is time-consuming, labo...
Thorax X-Rays Pneumothorax Retrospective Studies Deep Learning Humans
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Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection.

Journal of healthcare engineering Nov 26, 2021
The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity convolution U-Net algorithm for patients with severe pulmonary infection. A new lung CT image segmentation algorithm (U-Net+ deep convolution (DC)) was...
Pneumonia Humans Thorax Lung Tomography, X-Ray Computed Deep Learning
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Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria.

International journal of computer assisted radiology and surgery Oct 26, 2021
PURPOSE: This study aims at exploiting artificial intelligence (AI) for the identification, segmentation and quantification of COVID-19 pulmonary lesions. The limited data availability and the annotation quality are relevant factors in training AI-me...
Lung Thorax Artificial Intelligence Humans COVID-19 SARS-CoV-2
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Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning.

International journal of computer assisted radiology and surgery Oct 15, 2021
PURPOSE: The three-dimensional (3D) voxel labeling of lesions requires significant radiologists' effort in the development of computer-aided detection software. To reduce the time required for the 3D voxel labeling, we aimed to develop a generalized ...
Deep Learning Magnetic Resonance Imaging Thorax Liver Humans Tomography, X-Ray Computed
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Artificial intelligence on COVID-19 pneumonia detection using chest xray images.

PloS one Oct 14, 2021
Recent studies show the potential of artificial intelligence (AI) as a screening tool to detect COVID-19 pneumonia based on chest x-ray (CXR) images. However, issues on the datasets and study designs from medical and technical perspectives, as well a...
Predictive Value of Tests Radiography, Thoracic Sensitivity and Specificity Pneumonia Artificial Intelligence Thorax Humans COVID-19
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Weakly supervised learning for classification of lung cytological images using attention-based multiple instance learning.

Scientific reports Oct 13, 2021
In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or mal...
Small Cell Lung Carcinoma Chromatin Pattern Recognition, Automated Thorax Humans Image Interpretation, Computer-Assisted Medical Informatics Deep Learning Image Processing, Computer-Assisted Adenocarcinoma Carcinoma, Squamous Cell Supervised Machine Learning Reproducibility of Results Lung Neoplasms Neural Networks, Computer Lung Retrospective Studies
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Detection and analysis of COVID-19 in medical images using deep learning techniques.

Scientific reports Oct 4, 2021
The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied to X-ray and CT-scan medical images for the detection of COVID-19. In this paper, we used four powerful pre-trained CNN models, VGG16, Dense...
Image Processing, Computer-Assisted Thorax X-Rays SARS-CoV-2 Deep Learning COVID-19 Tomography, X-Ray Computed Humans
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