AIMC Topic: Solitary Pulmonary Nodule

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Evaluation of a novel deep learning-based classifier for perifissural nodules.

European radiology Dec 2, 2020
OBJECTIVES: To evaluate the performance of a novel convolutional neural network (CNN) for the classification of typical perifissural nodules (PFN).
Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Netherlands Humans Deep Learning
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Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation.

European radiology Nov 21, 2020
OBJECTIVE: To explore the natural history of pulmonary subsolid nodules (SSNs) with different pathological types by deep learning-assisted nodule segmentation.
Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed Retrospective Studies Deep Learning Lung Neoplasms Multiple Pulmonary Nodules
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A bilinear convolutional neural network for lung nodules classification on CT images.

International journal of computer assisted radiology and surgery Nov 2, 2020
PURPOSE: Lung cancer is the most frequent cancer worldwide and is the leading cause of cancer-related deaths. Its early detection and treatment at the stage of a lung nodule improve the prognosis. In this study was proposed a new classification appro...
Tomography, X-Ray Computed Lung Diagnosis, Computer-Assisted Lung Neoplasms Humans Neural Networks, Computer Support Vector Machine Solitary Pulmonary Nodule
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The detection of lung cancer using massive artificial neural network based on soft tissue technique.

BMC medical informatics and decision making Oct 31, 2020
BACKGROUND: A proposed computer aided detection (CAD) scheme faces major issues during subtle nodule recognition. However, radiologists have not noticed subtle nodules in beginning stage of lung cancer while a proposed CAD scheme recognizes non subtl...
Humans Image Interpretation, Computer-Assisted Lung Lung Neoplasms Neural Networks, Computer Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity
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Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

JAMA network open Sep 1, 2020
IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.
Lung Deep Learning Lung Neoplasms Solitary Pulmonary Nodule Sensitivity and Specificity Male Middle Aged Tumor Burden Radiography, Thoracic Radiographic Image Enhancement Early Detection of Cancer Predictive Value of Tests Radiologists Humans Artificial Intelligence Algorithms Female Reproducibility of Results Aged
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Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

PloS one Aug 26, 2020
A new computer-aided detection scheme is proposed, the 3D U-Net convolutional neural network, based on multiscale features of transfer learning to automatically detect pulmonary nodules from the thoracic region containing background and noise. The te...
Algorithms Humans Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Lung Machine Learning Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Early Detection of Cancer
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Development and clinical application of deep learning model for lung nodules screening on CT images.

Scientific reports Aug 12, 2020
Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and ...
Early Detection of Cancer Image Processing, Computer-Assisted Humans Lung Neoplasms Artificial Intelligence Multiple Pulmonary Nodules Algorithms Solitary Pulmonary Nodule Middle Aged Retrospective Studies Deep Learning Tomography, X-Ray Computed China Female Male
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A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.

Computational and mathematical methods in medicine Aug 1, 2020
BACKGROUND: The differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonar...
Carcinoma, Non-Small-Cell Lung Multiple Pulmonary Nodules Solitary Pulmonary Nodule Diagnosis, Differential Tomography, X-Ray Computed Deep Learning Adenocarcinoma of Lung Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Humans Expert Systems Artificial Intelligence Expert Testimony Databases, Factual
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A robust convolutional neural network for lung nodule detection in the presence of foreign bodies.

Scientific reports Jul 31, 2020
Lung cancer is a major cause of death worldwide. As early detection can improve outcome, regular screening is of great interest, especially for certain risk groups. Besides low-dose computed tomography, chest X-ray is a potential option for screening...
Foreign Bodies Lung Solitary Pulmonary Nodule False Positive Reactions Humans Neural Networks, Computer Tomography, X-Ray Computed
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Discrimination between transient and persistent subsolid pulmonary nodules on baseline CT using deep transfer learning.

European radiology Jul 21, 2020
OBJECTIVES: To develop and validate a deep learning model to discriminate transient from persistent subsolid nodules (SSNs) on baseline CT.
Female Reproducibility of Results Aged Adult Male Middle Aged Lung Humans Retrospective Studies Tomography, X-Ray Computed Calibration Deep Learning Solitary Pulmonary Nodule Image Processing, Computer-Assisted Area Under Curve Lung Neoplasms Radiology Radiologists
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