AIMC Topic: Multiple Pulmonary Nodules

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Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation.

European radiology Mar 27, 2024
OBJECTIVE: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.
Radiographic Image Interpretation, Computer-Assisted Uncertainty Male Middle Aged Risk Assessment Multiple Pulmonary Nodules Solitary Pulmonary Nodule Deep Learning Lung Neoplasms Tomography, X-Ray Computed Female Aged Humans Algorithms Retrospective Studies
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LGDNet: local feature coupling global representations network for pulmonary nodules detection.

Medical & biological engineering & computing Mar 2, 2024
Detection of suspicious pulmonary nodules from lung CT scans is a crucial task in computer-aided diagnosis (CAD) systems. In recent years, various deep learning-based approaches have been proposed and demonstrated significant potential for addressing...
Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Lung Diagnosis, Computer-Assisted Deep Learning
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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.
Aged Adult Male Prospective Studies Tomography, X-Ray Computed Female Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Middle Aged Deep Learning Lung Neoplasms Humans
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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.
Humans Artificial Intelligence Software Multiple Pulmonary Nodules Retrospective Studies Tomography, X-Ray Computed
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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.
Humans Radiographic Image Interpretation, Computer-Assisted Aged Lung Neoplasms Middle Aged Male Tomography, X-Ray Computed Incidental Findings Multiple Pulmonary Nodules Risk Assessment Female Solitary Pulmonary Nodule Deep Learning
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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
Thoracic Surgery, Video-Assisted Thoracoscopy Octogenarians Robotics Robotic Surgical Procedures Pneumonectomy Humans Lung Neoplasms Multiple Pulmonary Nodules Retrospective Studies Aged, 80 and over
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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.
Retrospective Studies Multiple Pulmonary Nodules Humans Radiography Deep Learning Artificial Intelligence Algorithms
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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...
Multiple Pulmonary Nodules Adenocarcinoma of Lung Radiomics Deep Learning Lung Neoplasms Humans Retrospective Studies Tomography, X-Ray Computed
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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...
Early Detection of Cancer Magnetic Resonance Imaging Positron Emission Tomography Computed Tomography Multiple Pulmonary Nodules Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed Lung Neoplasms
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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 ...
Radiographic Image Interpretation, Computer-Assisted Precancerous Conditions Overdiagnosis Lung Neoplasms Humans Algorithms Lung Multiple Pulmonary Nodules Deep Learning Solitary Pulmonary Nodule
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