AIMC Topic: Solitary Pulmonary Nodule

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Deep-learning based electromagnetic navigation system for transthoracic percutaneous puncture of small pulmonary nodules.

Scientific reports Jan 20, 2025
Percutaneous transthoracic puncture of small pulmonary nodules is technically challenging. We developed a novel electromagnetic navigation puncture system for the puncture of sub-centimeter lung nodules by combining multiple deep learning models with...
Electromagnetic Phenomena Phantoms, Imaging Tomography, X-Ray Computed Animals Male Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Punctures Humans
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Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow-up.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Jan 17, 2025
OBJECTIVES: For emergency department (ED) patients, lung cancer may be detected early through incidental lung nodules (ILNs) discovered on chest CTs. However, there are significant errors in the communication and follow-up of incidental findings on E...
Humans Retrospective Studies Tomography, X-Ray Computed Lung Neoplasms Solitary Pulmonary Nodule Natural Language Processing Emergency Service, Hospital Female Aged Male Middle Aged Incidental Findings
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Development of a clinical prediction model for benign and malignant pulmonary nodules with a CTR ≥ 50% utilizing artificial intelligence-driven radiomics analysis.

BMC medical imaging Jan 17, 2025
OBJECTIVE: In clinical practice, diagnosing the benignity and malignancy of solid-component-predominant pulmonary nodules is challenging, especially when 3D consolidation-to-tumor ratio (CTR) ≥ 50%, as malignant ones are more invasive. This study aim...
Diagnosis, Differential Logistic Models Multiple Pulmonary Nodules Solitary Pulmonary Nodule Aged Adult Radiomics Male Middle Aged ROC Curve Lung Neoplasms Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Humans Female
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Deep learning-based image domain reconstruction enhances image quality and pulmonary nodule detection in ultralow-dose CT with adaptive statistical iterative reconstruction-V.

European radiology Jan 10, 2025
OBJECTIVES: To evaluate the image quality and lung nodule detectability of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) post-processed using a deep learning image reconstruction (DLIR)-based image domain comp...
Middle Aged Tomography, X-Ray Computed Deep Learning Female Image Processing, Computer-Assisted Multiple Pulmonary Nodules Humans Lung Neoplasms Aged Solitary Pulmonary Nodule Retrospective Studies Male Radiographic Image Interpretation, Computer-Assisted Radiation Dosage
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Malignancy risk stratification for pulmonary nodules: comparing a deep learning approach to multiparametric statistical models in different disease groups.

European radiology Jan 2, 2025
OBJECTIVES: Incidentally detected pulmonary nodules present a challenge in clinical routine with demand for reliable support systems for risk classification. We aimed to evaluate the performance of the lung-cancer-prediction-convolutional-neural-netw...
Female Aged Adult Male Humans Retrospective Studies Tomography, X-Ray Computed Multiple Pulmonary Nodules Middle Aged Solitary Pulmonary Nodule Risk Assessment Models, Statistical Deep Learning Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms
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Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection.

Computers in biology and medicine Dec 30, 2024
Artificial Intelligence (AI) models may fail or suffer from reduced performance when applied to unseen data that differs from the training data distribution, referred to as dataset shift. Automatic detection of out-of-distribution (OOD) data contribu...
Humans Lung Neoplasms Tomography, X-Ray Computed Deep Learning Solitary Pulmonary Nodule
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Fusion-driven semi-supervised learning-based lung nodules classification with dual-discriminator and dual-generator generative adversarial network.

BMC medical informatics and decision making Dec 24, 2024
BACKGROUND: The detection and classification of lung nodules are crucial in medical imaging, as they significantly impact patient outcomes related to lung cancer diagnosis and treatment. However, existing models often suffer from mode collapse and po...
Tomography, X-Ray Computed Humans Lung Neoplasms Solitary Pulmonary Nodule Neural Networks, Computer Supervised Machine Learning
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Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay.

Current problems in diagnostic radiology Dec 10, 2024
In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms ar...
Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Diagnostic Errors Lung Neoplasms Solitary Pulmonary Nodule Humans Machine Learning Algorithms
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Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Accurate lung lesion segmentation from computed tomography (CT) images is crucial to the analysis and diagnosis of lung diseases, such as COVID-19 and lung cancer. However, the smallness and variety of lung nodules and the lack of high-quality labeli...
Humans Neural Networks, Computer COVID-19 Algorithms Databases, Factual Tomography, X-Ray Computed SARS-CoV-2 Solitary Pulmonary Nodule Lung Radiographic Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Supervised Machine Learning Lung Neoplasms
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External validation of the performance of commercially available deep-learning-based lung nodule detection on low-dose CT images for lung cancer screening in Japan.

Japanese journal of radiology Nov 30, 2024
PURPOSE: Artificial intelligence (AI) algorithms for lung nodule detection have been developed to assist radiologists. However, external validation of its performance on low-dose CT (LDCT) images is insufficient. We examined the performance of the co...
Radiation Dosage Early Detection of Cancer Male Female Humans Middle Aged Radiographic Image Interpretation, Computer-Assisted Aged Lung Retrospective Studies Deep Learning Japan Aged, 80 and over Tomography, X-Ray Computed Sensitivity and Specificity Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule
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