AIMC Topic: Lung

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A hybrid inception-dilated-ResNet architecture for deep learning-based prediction of COVID-19 severity.

Scientific reports Feb 22, 2025
Chest computed tomography (CT) scans are essential for accurately assessing the severity of the novel Coronavirus (COVID-19), facilitating appropriate therapeutic interventions and monitoring disease progression. However, determining COVID-19 severit...
SARS-CoV-2 Male Lung Severity of Illness Index Deep Learning COVID-19 Tomography, X-Ray Computed Female Humans Neural Networks, Computer
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An 8-point scale lung ultrasound scoring network fusing local detail and global features.

Scientific reports Feb 17, 2025
Manual lung ultrasound (LUS) scoring is influenced by clinicians' subjective interpretation, leading to potential inconsistencies and misdiagnoses due to varying levels of experience. To improve monitoring of pulmonary ventilation and support early d...
Ultrasonography Lung Diseases Image Interpretation, Computer-Assisted Neural Networks, Computer Lung Deep Learning Humans
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Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Computers in biology and medicine Feb 8, 2025
Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and monitoring treatment progression. High-performance segmentation methods rely heavily on fully annotated, large-scale training datasets. However, manua...
Deep Learning Imaging, Three-Dimensional Humans Tomography, X-Ray Computed Lung
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images.

Scientific reports Feb 8, 2025
Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classification of cancer types are crucial for effective treatment. Imaging tests on different image modalitie...
Humans Lung Neoplasms Lung Genetic Algorithms Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Facing Differences of Similarity: Intra- and Inter-Correlation Unsupervised Learning for Chest X-Ray Anomaly Detection.

IEEE transactions on medical imaging Feb 4, 2025
Anomaly detection can significantly aid doctors in interpreting chest X-rays. The commonly used strategy involves utilizing the pre-trained network to extract features from normal data to establish feature representations. However, when a pre-trained...
Unsupervised Machine Learning Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Humans Algorithms Databases, Factual Lung
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Deep Learning-Assisted Computer-Aided Diagnosis System for Early Detection of Lung Cancer.

Journal of clinical ultrasound : JCU Jan 29, 2025
PURPOSE: The largest cause of cancer-related fatalities worldwide is lung cancer. The dimensions and positioning of the primary tumor, the presence of lesions, the type of lung cancer like malignant or benign, and the good mental health diagnosis all...
Humans Neural Networks, Computer Algorithms Deep Learning Lung Neoplasms Early Detection of Cancer Sensitivity and Specificity Lung Diagnosis, Computer-Assisted
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Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis.

Journal of X-ray science and technology Jan 28, 2025
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
Humans Algorithms Tomography, X-Ray Computed Imaging, Three-Dimensional Sensitivity and Specificity Lung Neoplasms Lung Radiographic Image Interpretation, Computer-Assisted Deep Learning
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Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.

Tomography (Ann Arbor, Mich.) Jan 27, 2025
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...
Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Middle Aged Lung Female Humans Imaging, Three-Dimensional Aged Deep Learning Tomography, X-Ray Computed Lung Neoplasms Male Solitary Pulmonary Nodule
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Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

PloS one Jan 27, 2025
In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. However, tr...
Humans Pandemics COVID-19 Image Processing, Computer-Assisted Lung Coronavirus Infections Deep Learning Algorithms False Positive Reactions Betacoronavirus Tomography, X-Ray Computed ROC Curve Pneumonia, Viral SARS-CoV-2 Particle Swarm Optimization
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Feature-targeted deep learning framework for pulmonary tumorous Cone-beam CT (CBCT) enhancement with multi-task customized perceptual loss and feature-guided CycleGAN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 26, 2025
Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation therapy (IGRT) to provide updated patient anatomy information for lung cancer treatments. However, CBCT images often suffer from streaking artifacts an...
Deep Learning Artifacts Humans Cone-Beam Computed Tomography Radiotherapy, Image-Guided Lung Lung Neoplasms Radiographic Image Enhancement
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