AIMC Topic: Lung Neoplasms

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Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research Aug 21, 2017
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...
Male Middle Aged Case-Control Studies Aged Adult Pulmonary Disease, Chronic Obstructive Healthy Volunteers Breath Tests Exhalation Electronic Nose Lung Neoplasms Support Vector Machine Neoplasm Staging Humans Female
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Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering Aug 9, 2017
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...
Sensitivity and Specificity Solitary Pulmonary Nodule Algorithms Diagnosis, Computer-Assisted Radiography, Thoracic ROC Curve Humans Deep Learning Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Software Reproducibility of Results Lung Neoplasms
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An Automatic Detection System of Lung Nodule Based on Multigroup Patch-Based Deep Learning Network.

IEEE journal of biomedical and health informatics Jul 14, 2017
High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung cancer. It is a significant and challenging task to quickly locate the exact positions of lung nodules. Extensive work has been done by researchers around t...
Tomography, X-Ray Computed Lung Deep Learning Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Humans Algorithms
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Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

Medical image analysis Jun 30, 2017
Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and the...
Diagnosis, Computer-Assisted Lung Neoplasms Machine Learning Humans Tomography, X-Ray Computed Neural Networks, Computer Sensitivity and Specificity
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Robotic versus thoracoscopic thymectomy: The current evidence.

The international journal of medical robotics + computer assisted surgery : MRCAS Jun 29, 2017
BACKGROUND: The purpose of this study was to analyze all relevant comparative studies comparing robot-assisted minimally invasive thymectomy (RATS) and video-assisted thoracic surgery thymectomy (VATS) in terms of surgical and short-term outcomes.
Thymectomy Minimally Invasive Surgical Procedures Robotic Surgical Procedures Thoracic Surgery, Video-Assisted Video Recording Thoracic Surgical Procedures Sternotomy Treatment Outcome Operative Time Robotics Postoperative Complications Length of Stay Lung Neoplasms Humans Adult Middle Aged Retrospective Studies Hospitalization
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Feature fusion for lung nodule classification.

International journal of computer assisted radiology and surgery Jun 16, 2017
PURPOSE: This article examines feature-based nodule description for the purpose of nodule classification in chest computed tomography scanning.
Tomography, X-Ray Computed ROC Curve Lung Neoplasms Humans Algorithms Support Vector Machine Solitary Pulmonary Nodule
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Fully automatic detection of lung nodules in CT images using a hybrid feature set.

Medical physics Jun 16, 2017
PURPOSE: The aim of this study was to develop a novel technique for lung nodule detection using an optimized feature set. This feature set has been achieved after rigorous experimentation, which has helped in reducing the false positives significantl...
Algorithms Tomography, X-Ray Computed Sensitivity and Specificity Diagnosis, Computer-Assisted Humans Radiographic Image Interpretation, Computer-Assisted Lung Neoplasms Support Vector Machine Solitary Pulmonary Nodule
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Deep monocular 3D reconstruction for assisted navigation in bronchoscopy.

International journal of computer assisted radiology and surgery May 15, 2017
PURPOSE: In bronchoschopy, computer vision systems for navigation assistance are an attractive low-cost solution to guide the endoscopist to target peripheral lesions for biopsy and histological analysis. We propose a decoupled deep learning architec...
Bronchoscopy Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Neoplasms Humans Artificial Intelligence
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Pulmonary nodule classification with deep residual networks.

International journal of computer assisted radiology and surgery May 13, 2017
UNLABELLED: PURPOSE  : Lung cancer has the highest death rate among all cancers in the USA. In this work we focus on improving the ability of computer-aided diagnosis (CAD) systems to predict the malignancy of nodules from cropped CT images of lung n...
Humans Neural Networks, Computer Lung Neoplasms Solitary Pulmonary Nodule Algorithms Diagnosis, Computer-Assisted Multidetector Computed Tomography
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Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data.

Medical engineering & physics May 13, 2017
Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with...
Movement Image Processing, Computer-Assisted Lung Neoplasms Robotics Tomography, X-Ray Computed Equipment Design Electromagnetic Phenomena Image-Guided Biopsy Signal-To-Noise Ratio Phantoms, Imaging Biopsy, Needle Needles
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