AIMC Topic: Multiple Pulmonary Nodules
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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...
Comparison of Short-Term Outcomes Between Robot-Assisted and Video-Assisted Segmentectomy for Small Pulmonary Nodules: A Propensity Score-Matching Study.
Annals of surgical oncology
Feb 11, 2023
BACKGROUND: Our study aimed to compare the short-term outcomes between robot-assisted segmentectomy (RAS) and video-assisted segmentectomy (VAS) for small pulmonary nodules.
ASO Author Reflections: Which Technique is Superior for Segmentectomy of Small Pulmonary Nodules: Robot-Assisted or Video-Assisted?
Annals of surgical oncology
Feb 10, 2023
Ultra-low-dose CT lung screening with artificial intelligence iterative reconstruction: evaluation via automatic nodule-detection software.
Clinical radiology
Feb 3, 2023
AIM: To test the feasibility of ultra-low-dose (ULD) computed tomography (CT) combined with an artificial intelligence iterative reconstruction (AIIR) algorithm for screening pulmonary nodules using computer-assisted diagnosis (CAD).
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...
Reducing uncertainty in cancer risk estimation for patients with indeterminate pulmonary nodules using an integrated deep learning model.
Computers in biology and medicine
Sep 29, 2022
OBJECTIVE: Patients with indeterminate pulmonary nodules (IPN) with an intermediate to a high probability of lung cancer generally undergo invasive diagnostic procedures. Chest computed tomography image and clinical data have been in estimating the p...
Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.
Japanese journal of radiology
Sep 19, 2022
PURPOSE: To evaluate the performance of a deep learning-based computer-aided detection (CAD) software for detecting pulmonary nodules, masses, and consolidation on chest radiographs (CRs) and to examine the effect of readers' experience and data char...
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.
Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/masses.
European radiology
Jun 25, 2022
OBJECTIVES: To compare the performance of radiologists in characterizing and diagnosing pulmonary nodules/masses with and without deep learning (DL)-based computer-aided diagnosis (CAD).
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