AIMC Topic: Solitary Pulmonary Nodule
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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...
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...
Enhancing Nodule Biopsy Through Technology Integration.
Innovations (Philadelphia, Pa.)
Feb 18, 2023
Technology in navigating to peripheral pulmonary nodules has improved in recent years. The recent integration of a robotic platform using shape-sensing technology and mobile cone-beam computed tomography imaging technology has enhanced confidence in ...
A Novel Deep Learning Model Based on Multi-Scale and Multi-View for Detection of Pulmonary Nodules.
Journal of digital imaging
Dec 21, 2022
Lung cancer manifests as pulmonary nodules in the early stage. Thus, the early and accurate detection of these nodules is crucial for improving the survival rate of patients. We propose a novel two-stage model for lung nodule detection. In the candid...
Multi-Perspective Hierarchical Deep-Fusion Learning Framework for Lung Nodule Classification.
Sensors (Basel, Switzerland)
Nov 18, 2022
Lung cancer is the leading cancer type that causes mortality in both men and women. Computer-aided detection (CAD) and diagnosis systems can play a very important role for helping physicians with cancer treatments. This study proposes a hierarchical ...
Applying a CT texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images in pulmonary nodule diagnosis.
Journal of applied clinical medical physics
Aug 23, 2022
OBJECTIVE: To investigate the feasibility and accuracy of applying a computed tomography (CT) texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images for classifying pulmonary nodules.
Hybrid U-Net-based deep learning model for volume segmentation of lung nodules in CT images.
Medical physics
Aug 17, 2022
OBJECTIVE: Accurate segmentation of the lung nodule in computed tomography images is a critical component of a computer-assisted lung cancer detection/diagnosis system. However, lung nodule segmentation is a challenging task due to the heterogeneity ...
Self-Supervised Transfer Learning Based on Domain Adaptation for Benign-Malignant Lung Nodule Classification on Thoracic CT.
IEEE journal of biomedical and health informatics
Aug 11, 2022
The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule objects hold richer discriminative information. However, for deep lea...
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