P3.13-037 Deep Learning System for Lung Nodule Detection
نویسندگان
چکیده
منابع مشابه
Lung nodule detection by using Deep Learning
Lung cancer is one of the most common types of cancer worldwide. It is also one of the deadliest types of cancer. However, research indicates that early detection of lung cancer significantly improves chances of survival. Using computed tomography scans of the human lungs, radiologists can detect dangerous nodules in early stages. When more people adopting for these scans, the workload on the r...
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Lung cancer is one of the most common types of cancer worldwide. It is also one of the deadliest types of cancer. However, research indicates that early detection of lung cancer significantly improves chances of survival. Using computed tomography scans of the human lungs, radiologists can detect dangerous nodules in early stages. When more people adopting for these scans, the workload on the r...
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The Existing approach consist of CAD scheme with Virtual Dual Energy. CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs) To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacit...
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The detection of lung-related disease for radiologists is a tedious and time-consuming task. For this reason, automatic computer-aided diagnosis (CADs) systems were developed by using digital CT scan images of lungs. The detection of lung nodule patterns is an important step for the automatic development of CAD system. Currently, the patterns of lung nodule are detected through domain-expert kn...
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This study uses a revolutionary image recognition method, deep learning, for the classification of potentially malignant pulmonary nodules. Deep learning is based on deep neural networks. We report results of our initial findings and compare performance of deep neural nets using a combination of different network topologies and optimization parameters. Classification accuracy, sensitivity and s...
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ژورنال
عنوان ژورنال: Journal of Thoracic Oncology
سال: 2017
ISSN: 1556-0864
DOI: 10.1016/j.jtho.2017.09.1772