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Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets
BackgroundLow-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning...
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A semantic fidelity interpretable-assisted decision model for lung nodule classification
PurposeEarly diagnosis of lung nodules is important for the treatment of lung cancer patients, existing capsule network-based assisted diagnostic...
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A novel fusion algorithm for benign-malignant lung nodule classification on CT images
The accurate recognition of malignant lung nodules on CT images is critical in lung cancer screening, which can offer patients the best chance of...
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Lung CT stabilization with high-frequency non-invasive ventilation (HF-NIV) and breath-hold (BH) in lung nodule assessment by PET/CT
PurposeTo evaluate the effect of lung stabilization using high-frequency non-invasive ventilation (HF-NIV) and breath-hold (BH) techniques on lung...
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Risk factors of pneumothorax in computed tomography guided lung nodule marking using autologous blood: a retrospective study
BackgroundTo investigate the risk factors of pneumothorax of using computed tomography (CT) guidance to inject autologous blood to locate isolated...
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The association between obstructive sleep apnea and lung nodule, carcinoembryonic antigen
PurposeThe association between obstructive sleep apnea (OSA) and cancer risks gaining more and more attention. Data on the association between OSA...
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Clinical application of CT-assisted body surface localization combined with intraoperative stereotactic anatomical localization in thoracoscopic lung nodule resection: a single-centre retrospective study
BackgroundToday, the detection rate of lung nodules is increasing. Some of these nodules may become malignant. Thus, timely resection of potentially...
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An Improved Convolution Neural Network and Modified Regularized K-Means-Based Automatic Lung Nodule Detection and Classification
If lung cancer is not detected in its initial phases, it can be fatal. However, because of the quantity and structure of its nodules, lung cancer is...
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Pricing and cost-saving potential for deep-learning computer-aided lung nodule detection software in CT lung cancer screening
ObjectiveAn increasing number of commercial deep learning computer-aided detection (DL-CAD) systems are available but their cost-saving potential is...
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Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT
BackgroundEmphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by...
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Lung nodule pre-diagnosis and insertion path planning for chest CT images
Medical image processing has proven to be effective and feasible for assisting oncologists in diagnosing lung, thyroid, and other cancers, especially...
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CT imaging features of lung ground-glass nodule patients with upgraded intraoperative frozen pathology
PurposeIntraoperative frozen section pathology (FS) is widely used to guide surgical strategies while the accuracy is relatively low. Underestimating...
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Calcific pulmonary nodule, is it wandering?
Wandering pulmonary nodule is defined as a nodule with morphologically identical features found in different regions of the lung on different imaging...
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Development and performance evaluation of a deep learning lung nodule detection system
BackgroundLung cancer is the leading cause of cancer-related deaths throughout the world. Chest computed tomography (CT) is now widely used in the...
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The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule
BackgroundThe deep learning-based nodule detection (DLD) system improves nodule detection performance of observers on chest radiographs (CXRs)....
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Develo** an understanding of artificial intelligence lung nodule risk prediction using insights from the Brock model
ObjectivesTo determine if predictions of the Lung Cancer Prediction convolutional neural network (LCP-CNN) artificial intelligence (AI) model are...
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Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness....
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Multi-scale dense selective network based on border modeling for lung nodule segmentation
PurposeAccurate quantification of pulmonary nodules helps physicians to accurately diagnose and treat lung cancer. We try to improve the segmentation...
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Pulmonary Nodule Classification Using a Multiview Residual Selective Kernel Network
Lung cancer is one of the leading causes of death worldwide and early detection is crucial to reduce the mortality. A reliable computer-aided...
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TiCNet: Transformer in Convolutional Neural Network for Pulmonary Nodule Detection on CT Images
Lung cancer is the leading cause of cancer death. Since lung cancer appears as nodules in the early stage, detecting the pulmonary nodules in an...
