AIMC Topic: Multiple Pulmonary Nodules
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Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.
Academic radiology
Feb 29, 2024
RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLIR) on the image quality and quantitative analysis of pulmonary nodules under ultra-low dose lung CT conditions.
Diagnostic value of artificial intelligence based on computed tomography (CT) density in benign and malignant pulmonary nodules: a retrospective investigation.
PeerJ
Jan 2, 2024
OBJECTIVE: To evaluate the diagnostic value of artificial intelligence (AI) in the detection and management of benign and malignant pulmonary nodules (PNs) using computed tomography (CT) density.
Deep learning for malignancy risk estimation of incidental sub-centimeter pulmonary nodules on CT images.
European radiology
Dec 20, 2023
OBJECTIVES: To establish deep learning models for malignancy risk estimation of sub-centimeter pulmonary nodules incidentally detected by chest CT and managed in clinical settings.
ASO Author Reflections: Should We Prefer Robotic over Thoracoscopic Surgery for Sublobar Resection in Octogenarians with Pulmonary Nodules ≤ 2 cm?
Annals of surgical oncology
Dec 6, 2023
Development of a novel artificial intelligence algorithm to detect pulmonary nodules on chest radiography.
Fukushima journal of medical science
Oct 17, 2023
BACKGROUND: In this study, we aimed to develop a novel artificial intelligence (AI) algorithm to support pulmonary nodule detection, which will enable physicians to efficiently interpret chest radiographs for lung cancer diagnosis.
Development and Validation of a Deep Learning Radiomics Model to Predict High-Risk Pathologic Pulmonary Nodules Using Preoperative Computed Tomography.
Academic radiology
Oct 5, 2023
RATIONALE AND OBJECTIVES: To accurately identify the high-risk pathological factors of pulmonary nodules, our study constructed a model combined with clinical features, radiomics features, and deep transfer learning features to predict high-risk path...
Imaging of Solid Pulmonary Nodules.
Clinics in chest medicine
Sep 19, 2023
Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, o...
A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.
European radiology
Sep 2, 2023
OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN ...
Deep learning-based automatic detection for pulmonary nodules on chest radiographs: The relationship with background lung condition, nodule characteristics, and location.
European journal of radiology
Jul 22, 2023
PURPOSE: Computer-aided diagnosis (CAD), which assists in the interpretation of chest radiographs, is becoming common. However, few studies have evaluated the benefits and pitfalls of CAD in the real world. This study aimed to evaluate the independen...
A systematic approach to deep learning-based nodule detection in chest radiographs.
Scientific reports
Jun 21, 2023
Lung cancer is a serious disease responsible for millions of deaths every year. Early stages of lung cancer can be manifested in pulmonary lung nodules. To assist radiologists in reducing the number of overseen nodules and to increase the detection a...
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