AIMC Topic: Lung Neoplasms

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End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

Nature medicine May 20, 2019
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20-43% and is now included in US scree...
Mass Screening Imaging, Three-Dimensional Lung Neoplasms United States Algorithms Databases, Factual Retrospective Studies Humans Diagnosis, Computer-Assisted Neural Networks, Computer Deep Learning Tomography, X-Ray Computed Risk Factors
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Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

BMC cancer May 17, 2019
PURPOSE: To explore imaging biomarkers that can be used for diagnosis and prediction of pathologic stage in non-small cell lung cancer (NSCLC) using multiple machine learning algorithms based on CT image feature analysis.
Humans Machine Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Neoplasm Staging Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Female Male
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Automated pulmonary nodule detection in CT images using 3D deep squeeze-and-excitation networks.

International journal of computer assisted radiology and surgery Apr 26, 2019
PURPOSE: Pulmonary nodule detection has great significance for early treating lung cancer and increasing patient survival. This work presents a novel automated computer-aided detection scheme for pulmonary nodules based on deep convolutional neural n...
Solitary Pulmonary Nodule Lung Humans Imaging, Three-Dimensional Neural Networks, Computer Lung Neoplasms Tomography, X-Ray Computed
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Lung nodule classification using deep Local-Global networks.

International journal of computer assisted radiology and surgery Apr 24, 2019
PURPOSE: Lung nodules have very diverse shapes and sizes, which makes classifying them as benign/malignant a challenging problem. In this paper, we propose a novel method to predict the malignancy of nodules that have the capability to analyze the sh...
Humans Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Lung Neoplasms Solitary Pulmonary Nodule
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Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.

IEEE transactions on medical imaging Apr 23, 2019
Edges tend to be over-smoothed in total variation (TV) regularized under-sampled images. In this paper, symmetric residual convolutional neural network (SR-CNN), a deep learning based model, was proposed to enhance the sharpness of edges and detailed...
Image Processing, Computer-Assisted Lung Neoplasms Phantoms, Imaging Humans Lung Algorithms Deep Learning Cone-Beam Computed Tomography
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Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 22, 2019
PURPOSE: Tumors are continuously evolving biological systems, and medical imaging is uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking lesions over space and time may be trivial, the development of clinicall...
Carcinoma, Non-Small-Cell Lung Neoplasm Staging Positron-Emission Tomography Humans Neural Networks, Computer Image Processing, Computer-Assisted Neoplasm Metastasis Tomography, X-Ray Computed Algorithms Lung Neoplasms Kaplan-Meier Estimate Deep Learning Prognosis Treatment Outcome Time Factors
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Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist Apr 17, 2019
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...
Humans Neural Networks, Computer Middle Aged Lung Deep Learning Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Female ROC Curve Male Lung Neoplasms Algorithms Databases, Factual Retrospective Studies
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Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
Models, Statistical Radiotherapy Radiation Pneumonitis Male Middle Aged ROC Curve Lung Neoplasms Nomograms Carcinoma, Non-Small-Cell Lung Female Aged Biomarkers, Tumor Humans Machine Learning Cytokines Prospective Studies
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Lungs nodule detection framework from computed tomography images using support vector machine.

Microscopy research and technique Apr 11, 2019
The emergence of cloud infrastructure has the potential to provide significant benefits in a variety of areas in the medical imaging field. The driving force behind the extensive use of cloud infrastructure for medical image processing is the exponen...
Humans Tomography, X-Ray Computed Sensitivity and Specificity Support Vector Machine False Positive Reactions Lung Image Processing, Computer-Assisted Lung Neoplasms
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Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.

Medical physics Apr 8, 2019
PURPOSE: There has been burgeoning interest in applying machine learning methods for predicting radiotherapy outcomes. However, the imbalanced ratio of a large number of variables to a limited sample size in radiation oncology constitutes a major cha...
Humans Machine Learning Carcinoma, Non-Small-Cell Lung Lung Neoplasms Computational Biology Treatment Outcome
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