AIMC Topic: Lung Neoplasms

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[Pulmonary nodule detection method based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2019
A method was proposed to detect pulmonary nodules in low-dose computed tomography (CT) images by two-dimensional convolutional neural network under the condition of fine image preprocessing. Firstly, CT image preprocessing was carried out by image cl...
Tomography, X-Ray Computed Lung Neoplasms Multiple Pulmonary Nodules Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms
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A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.

Clinical nuclear medicine Dec 1, 2019
PURPOSE: We sought to distinguish lung adenocarcinoma (ADC) from squamous cell carcinoma using a machine-learning algorithm with PET-based radiomic features.
Aged Male Middle Aged Retrospective Studies Female Carcinoma, Squamous Cell Area Under Curve Bayes Theorem Positron Emission Tomography Computed Tomography ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Humans Machine Learning
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Investigation of Low-Dose CT Lung Cancer Screening Scan "Over-Range" Issue Using Machine Learning Methods.

Journal of digital imaging Dec 1, 2019
Low-dose computed tomography (CT) lung cancer screening is recommended by the US Preventive Services Task Force for high lung cancer-risk populations. In this study, we investigated an important factor affecting the CT dose-the scan length, for this ...
Humans Radiation Dosage Lung Machine Learning Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Middle Aged
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Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.

Journal of digital imaging Dec 1, 2019
Remarkable progress has been made in image classification and segmentation, due to the recent study of deep convolutional neural networks (CNNs). To solve the similar problem of diagnostic lung nodule detection in low-dose computed tomography (CT) sc...
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Databases, Factual Lung Lung Neoplasms Tomography, X-Ray Computed Humans Neural Networks, Computer
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Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.

Journal of digital imaging Dec 1, 2019
Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest chal...
Lung Neoplasms Multiple Pulmonary Nodules Machine Learning Solitary Pulmonary Nodule Databases, Factual Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Humans Tomography, X-Ray Computed Sensitivity and Specificity Lung
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[Computer instruments for the management of isolated pulmonary nodule. Detectability and prediction of malignancy].

Revue medicale suisse Nov 13, 2019
Lung cancer remains the most common cause of cancer deaths in the world, but its mortality can be significantly reduced by diagnosis and early detection. Computerized resources were developed to assist radiologists in their management of the large vo...
Sensitivity and Specificity Diagnosis, Computer-Assisted Lung Neoplasms Humans Multiple Pulmonary Nodules Artificial Intelligence
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Discussion.

The Journal of thoracic and cardiovascular surgery Nov 1, 2019
Robotics Robotic Surgical Procedures Propensity Score Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans
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Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer.

Korean journal of radiology Oct 1, 2019
OBJECTIVE: To retrospectively assess the effect of CT slice thickness on the reproducibility of radiomic features (RFs) of lung cancer, and to investigate whether convolutional neural network (CNN)-based super-resolution (SR) algorithms can improve t...
Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Male Radiometry Middle Aged Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Lung Neoplasms Algorithms
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DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Mathematical biosciences and engineering : MBE Sep 30, 2019
Copy number variations (CNVs) play an important role in many types of cancer. With the rapid development of next generation sequencing (NGS) techniques, many methods for detecting CNVs of a single sample have emerged: (i) require genome-wide data of ...
Genome, Human Genome-Wide Association Study Proto-Oncogene Proteins c-met False Positive Reactions Reproducibility of Results ROC Curve Carcinoma, Non-Small-Cell Lung Exons Humans Lung Neoplasms DNA Copy Number Variations Sensitivity and Specificity Algorithms Area Under Curve Databases, Factual Deep Learning High-Throughput Nucleotide Sequencing In Situ Hybridization, Fluorescence Receptor, ErbB-2
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Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases.

Science translational medicine Sep 11, 2019
Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary metastases or a second squamous cell carcinoma of the lung (LUSC). Differentiating pulmonary metastases from primary lung cancers is of high clinical i...
Lung Neoplasms Head and Neck Neoplasms DNA Methylation Humans Algorithms Machine Learning Carcinoma, Squamous Cell Reproducibility of Results Cohort Studies
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