Study of Medical Image Processing techniques applied to Lung Cancer

Lung cancer is the leading cause of death from cancer worldwide. Medical images are essential in the diagnosis and prognosis of lung cancer. Medical image processing techniques such as Radiomics allow extracting information from these images that it is not accessible without computational means, and...

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Autores:
Moreno, Silvia
Bonfante, Mario
Zurek, Eduardo
San Juan, Homero
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/3702
Acceso en línea:
https://hdl.handle.net/20.500.12442/3702
Palabra clave:
Lung Cancer
Medical Image Processing
Radiomics
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License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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network_acronym_str USIMONBOL2
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dc.title.eng.fl_str_mv Study of Medical Image Processing techniques applied to Lung Cancer
title Study of Medical Image Processing techniques applied to Lung Cancer
spellingShingle Study of Medical Image Processing techniques applied to Lung Cancer
Lung Cancer
Medical Image Processing
Radiomics
title_short Study of Medical Image Processing techniques applied to Lung Cancer
title_full Study of Medical Image Processing techniques applied to Lung Cancer
title_fullStr Study of Medical Image Processing techniques applied to Lung Cancer
title_full_unstemmed Study of Medical Image Processing techniques applied to Lung Cancer
title_sort Study of Medical Image Processing techniques applied to Lung Cancer
dc.creator.fl_str_mv Moreno, Silvia
Bonfante, Mario
Zurek, Eduardo
San Juan, Homero
dc.contributor.author.none.fl_str_mv Moreno, Silvia
Bonfante, Mario
Zurek, Eduardo
San Juan, Homero
dc.subject.eng.fl_str_mv Lung Cancer
Medical Image Processing
Radiomics
topic Lung Cancer
Medical Image Processing
Radiomics
description Lung cancer is the leading cause of death from cancer worldwide. Medical images are essential in the diagnosis and prognosis of lung cancer. Medical image processing techniques such as Radiomics allow extracting information from these images that it is not accessible without computational means, and may be useful in the detection and treatment of cancer. This article presents the state of the art of image processing techniques applied in the study of lung cancer, emphasizing in two main tasks: segmentation of nodules or tumors, and extraction of useful features for classification and prognosis of tumor evolution using Radiomics.
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2019-08-13T13:59:14Z
dc.date.available.none.fl_str_mv 2019-08-13T13:59:14Z
dc.date.issued.none.fl_str_mv 2019-07
dc.type.eng.fl_str_mv article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.identifier.isbn.none.fl_str_mv 9789899843493
dc.identifier.issn.none.fl_str_mv 21660727
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/3702
identifier_str_mv 9789899843493
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url https://hdl.handle.net/20.500.12442/3702
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
dc.publisher.eng.fl_str_mv IEEE
dc.source.eng.fl_str_mv IEEE Xplore Digital Library
2019 14th Iberian Conference on Information Systems and Technologies (CISTI)
institution Universidad Simón Bolívar
dc.source.uri.eng.fl_str_mv https://ieeexplore.ieee.org/document/8760888
bitstream.url.fl_str_mv https://bonga.unisimon.edu.co/bitstreams/6c00434e-c3d1-49a2-9f5e-d47dbc48f538/download
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spelling Moreno, Silviafdbaaeb0-3b4f-4fb1-aa77-ebcfe2658250Bonfante, Mario5b91ad34-74dc-42ed-be44-06beeaf401dcZurek, Eduardof76fa751-7944-4c11-819b-3dae164a6215San Juan, Homero24d53aba-87c5-47ac-9a37-6a67c6f3177b2019-08-13T13:59:14Z2019-08-13T13:59:14Z2019-07978989984349321660727https://hdl.handle.net/20.500.12442/3702Lung cancer is the leading cause of death from cancer worldwide. Medical images are essential in the diagnosis and prognosis of lung cancer. Medical image processing techniques such as Radiomics allow extracting information from these images that it is not accessible without computational means, and may be useful in the detection and treatment of cancer. This article presents the state of the art of image processing techniques applied in the study of lung cancer, emphasizing in two main tasks: segmentation of nodules or tumors, and extraction of useful features for classification and prognosis of tumor evolution using Radiomics.engIEEEAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2IEEE Xplore Digital Library2019 14th Iberian Conference on Information Systems and Technologies (CISTI)https://ieeexplore.ieee.org/document/8760888Lung CancerMedical Image ProcessingRadiomicsStudy of Medical Image Processing techniques applied to Lung Cancerarticlehttp://purl.org/coar/resource_type/c_6501Cancer Research UK, “Worldwide cancer statistics.” [Online]. Available: http://www.cancerresearchuk.org/health-professional/cancerstatistics/ worldwide-cancer. [Accessed: 17-Nov-2017].P. Lambin, E. Rios-Velazquez, R. Leijenaar, S. Carvalho, R. G. P. M. Van Stiphout, P. Granton, C. M. L. Zegers, R. Gillies, R. Boellard, A. Dekker, and H. J. W. L. Aerts, “Radiomics: Extracting more information from medical images using advanced feature analysis,” Eur. J. Cancer, vol. 48, no. 4, pp. 441–446, 2012.G. Niranjana, “A Review on Image Processing Methods in Detecting Lung Cancer Using CT Images - IEEE Conference Publication,” 2017.G. Lee, H. Y. Lee, H. Park, M. L. Schiebler, E. J. R. van Beek, Y. Ohno, J. B. Seo, and A. Leung, “Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art,” Eur. J. Radiol., vol. 86, pp. 297–307, 2017.A. Kulkarni and A. Panditrao, “Classification of lung cancer stages on CT scan images using image processing,” 2014 IEEE Int. Conf. Adv. Commun. Control Comput. Technol., no. 978, pp. 1384–1388, 2014.Y. Gu, V. Kumar, L. O. Hall, D. B. Goldgof, C. Y. Li, R. Korn, C. Bendtsen, E. R. Velazquez, A. Dekker, H. Aerts, P. Lambin, X. Li, J. Tian, R. A. 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SPIE, vol. 9785, pp. 1–7, 2016.CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://bonga.unisimon.edu.co/bitstreams/6c00434e-c3d1-49a2-9f5e-d47dbc48f538/download4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8368https://bonga.unisimon.edu.co/bitstreams/71f7dae0-0954-45fd-b145-050462aab966/download3fdc7b41651299350522650338f5754dMD5320.500.12442/3702oai:bonga.unisimon.edu.co:20.500.12442/37022024-08-14 21:51:52.447http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacionalmetadata.onlyhttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.coPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj48aW1nIGFsdD0iTGljZW5jaWEgQ3JlYXRpdmUgQ29tbW9ucyIgc3R5bGU9ImJvcmRlci13aWR0aDowIiBzcmM9Imh0dHBzOi8vaS5jcmVhdGl2ZWNvbW1vbnMub3JnL2wvYnktbmMvNC4wLzg4eDMxLnBuZyIgLz48L2E+PGJyLz5Fc3RhIG9icmEgZXN0w6EgYmFqbyB1bmEgPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj5MaWNlbmNpYSBDcmVhdGl2ZSBDb21tb25zIEF0cmlidWNpw7NuLU5vQ29tZXJjaWFsIDQuMCBJbnRlcm5hY2lvbmFsPC9hPi4=