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Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT

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Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices (ICBHI 2019)

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Abstract

Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.

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Correspondence to Tsu-Chi Cheng .

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Cheng, TC., Chiu, NT., Fang, YH. (2020). Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. In: Lin, KP., Magjarevic, R., de Carvalho, P. (eds) Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices. ICBHI 2019. IFMBE Proceedings, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-030-30636-6_20

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  • DOI: https://doi.org/10.1007/978-3-030-30636-6_20

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-30636-6

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