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A Simple Method to Detection the Lung Cancer Tumor using CT images on Deep Learning
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dc.contributor.author Park, Young-Jin -
dc.contributor.author Cho, Hui-Sup -
dc.date.accessioned 2023-12-26T18:43:09Z -
dc.date.available 2023-12-26T18:43:09Z -
dc.date.created 2021-10-26 -
dc.date.issued 2021-10-21 -
dc.identifier.isbn 9781665423830 -
dc.identifier.issn 2162-1241 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/46890 -
dc.description.abstract This study proposes a method for lung cancer tumor detection by first pre-processing DICOM files, then separating the lung and soft tissue areas of these files via a linear combination, and finally analyzing the CT images more clearly. The image processing method used in this study achieved a sensitivity of 97.96%, precision of 99.23% of, and F1-score of 98.56%. In addition, because of its higher performance in comparison with the reference dataset, it can be concluded that this image processing method has an effect on the learning result of the neural network. © 2021 IEEE. -
dc.language English -
dc.publisher 한국통신학회 (The Korean Institute of Communications and Information Sciences, KICS) -
dc.title A Simple Method to Detection the Lung Cancer Tumor using CT images on Deep Learning -
dc.type Conference Paper -
dc.identifier.doi 10.1109/ICTC52510.2021.9620857 -
dc.identifier.scopusid 2-s2.0-85122966549 -
dc.identifier.bibliographicCitation Park, Young-Jin. (2021-10-21). A Simple Method to Detection the Lung Cancer Tumor using CT images on Deep Learning. International Conference on Information and Communication Technology Convergence, ICTC 2021, 1510–1512. doi: 10.1109/ICTC52510.2021.9620857 -
dc.identifier.url https://journal-home.s3.ap-northeast-2.amazonaws.com/site/ictc2022/archieve/ICTC+2021+Final+Program_v16.pdf -
dc.citation.conferencePlace KO -
dc.citation.conferencePlace 제주 -
dc.citation.endPage 1512 -
dc.citation.startPage 1510 -
dc.citation.title International Conference on Information and Communication Technology Convergence, ICTC 2021 -
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