AIMC Topic: Solitary Pulmonary Nodule

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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.
Middle Aged Risk Assessment Deep Learning Lung Neoplasms Female Aged Male Uncertainty Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Retrospective Studies Tomography, X-Ray Computed
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Robust deep learning from incomplete annotation for accurate lung nodule detection.

Computers in biology and medicine Mar 26, 2024
Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of...
Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Humans Lung Deep Learning
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Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.

Journal of imaging informatics in medicine Mar 25, 2024
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...
Humans Neural Networks, Computer Algorithms Lung Neoplasms Tomography, X-Ray Computed Solitary Pulmonary Nodule Lung Radiographic Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted
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Socio-Economic Factors and Clinical Context Can Predict Adherence to Incidental Pulmonary Nodule Follow-up via Machine Learning Models.

Journal of the American College of Radiology : JACR Mar 8, 2024
OBJECTIVE: To quantify the relative importance of demographic, contextual, socio-economic, and nodule-related factors that influence patient adherence to incidental pulmonary nodule (IPN) follow-up visits and evaluate the predictive performance of ma...
Incidental Findings Socioeconomic Factors Solitary Pulmonary Nodule Patient Compliance Machine Learning Female Aged Humans Adult Male Middle Aged Lung Neoplasms
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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...
Humans Neural Networks, Computer Algorithms Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed 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.
Humans Prospective Studies Tomography, X-Ray Computed Solitary Pulmonary Nodule Middle Aged Female Radiographic Image Interpretation, Computer-Assisted Deep Learning Radiation Dosage Aged Lung Neoplasms Adult Multiple Pulmonary Nodules Male
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Overcoming the Challenge of Accurate Segmentation of Lung Nodules: A Multi-crop CNN Approach.

Journal of imaging informatics in medicine Feb 12, 2024
Lung nodules are generated based on the growth of small and round- or oval-shaped cells in the lung, which are either cancerous or non-cancerous. Accurate segmentation of these nodules is crucial for early detection and diagnosis of lung cancer. Howe...
Radiographic Image Interpretation, Computer-Assisted Lung Lung Neoplasms Solitary Pulmonary Nodule Humans Neural Networks, Computer Algorithms 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.
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Incidental Findings Risk Assessment Deep Learning Humans Aged Lung Neoplasms Tomography, X-Ray Computed Male Multiple Pulmonary Nodules Female Middle Aged
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Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

AJR. American journal of roentgenology Nov 22, 2023
Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule computer-aided detection (CAD) systems have been designed and studied primarily using adult training ...
Sensitivity and Specificity Lung Neoplasms Male Retrospective Studies Solitary Pulmonary Nodule Lung Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Female Deep Learning Humans Adolescent Adult Artificial Intelligence Child, Preschool Computers Child
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Robot-assisted thoracoscopic surgery resection of a ground-glass nodule in the right middle lobe.

Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia Nov 17, 2023
Humans Lung Lung Neoplasms Thoracoscopy Robotics Solitary Pulmonary Nodule Robotic Surgical Procedures Thoracic Surgery, Video-Assisted
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