AIMC Topic: Lung

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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...
Pneumonia, Viral Particle Swarm Optimization Humans Pandemics Coronavirus Infections Lung False Positive Reactions COVID-19 Deep Learning ROC Curve Betacoronavirus Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed SARS-CoV-2
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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...
Radiographic Image Enhancement Cone-Beam Computed Tomography Humans Lung Neoplasms Lung Artifacts Deep Learning Radiotherapy, Image-Guided
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Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.

Respiratory research Jan 24, 2025
BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapidly evolving interstitial lung disease (ILD), driving its mortality. Specific imaging-based biomarkers associated with the evolution of lung disease are need...
Lung Diseases, Interstitial Respiratory Function Tests Scleroderma, Systemic Humans Artificial Intelligence Middle Aged Retrospective Studies Lung Tomography, X-Ray Computed Cohort Studies Female Predictive Value of Tests Aged Adult Male
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DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.

International journal of computer assisted radiology and surgery Jan 23, 2025
PURPOSE: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for se...
Anatomic Landmarks Heart Semantics Radiography, Thoracic Humans Neural Networks, Computer Lung Deep Learning Image Processing, Computer-Assisted
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Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Computers in biology and medicine Jan 22, 2025
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational r...
Humans Neural Networks, Computer COVID-19 Algorithms Radiography, Thoracic SARS-CoV-2 Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted
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Development of a machine learning tool to predict deep inspiration breath hold requirement for locoregional right-sided breast radiation therapy patients.

Biomedical physics & engineering express Jan 22, 2025
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...
Tomography, X-Ray Computed Female Aged Adult Radiotherapy Planning, Computer-Assisted Humans Inhalation Machine Learning Breath Holding Algorithms Unilateral Breast Neoplasms Retrospective Studies Breast Neoplasms Middle Aged Lung Logistic Models
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Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture.

International journal of computer assisted radiology and surgery Jan 20, 2025
PURPOSE: Pulmonary perfusion imaging is a key lung health indicator with clinical utility as a diagnostic and treatment planning tool. However, current nuclear medicine modalities face challenges like low spatial resolution and long acquisition times...
Humans Tomography, X-Ray Computed Female Supervised Machine Learning Male Perfusion Imaging Middle Aged Four-Dimensional Computed Tomography Lung Deep Learning
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Diagnostic accuracy of an automated classifier for the detection of pleural effusions in patients undergoing lung ultrasound.

The American journal of emergency medicine Jan 20, 2025
RATIONALE: Lung ultrasound, the most precise diagnostic tool for pleural effusions, is underutilized due to healthcare providers' limited proficiency. To address this, deep learning models can be trained to recognize pleural effusions. However, curre...
Humans Canada Female Algorithms Pleural Effusion Middle Aged Aged Retrospective Studies Sensitivity and Specificity Lung Male Deep Learning Ultrasonography
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Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.

International journal of chronic obstructive pulmonary disease Jan 20, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Prognosis Female Reproducibility of Results Aged Pulmonary Disease, Chronic Obstructive Male Middle Aged Disease Progression Humans Prospective Studies Speech Acoustics Speech Production Measurement Voice Quality Lung Severity of Illness Index Speech Time Factors Support Vector Machine Predictive Value of Tests Functional Status Respiratory Function Tests
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Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods.

NPJ systems biology and applications Jan 17, 2025
Classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) poses significant challenges for cytopathologists, often necessitating clinical tests and biopsies that delay treatment initiation. To address this, we developed a machine learni...
Machine Learning Algorithms Carcinoma, Squamous Cell Lung Lung Neoplasms Carcinoma, Non-Small-Cell Lung Discriminant Analysis Humans Microbiota
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