Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Satrajit Basu"'
Autor:
Samuel H. Hawkins, John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Virendra Kumar, Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies
Publikováno v:
IEEE Access, Vol 2, Pp 1418-1426 (2014)
Nonsmall cell lung cancer is a prevalent disease. It is diagnosed and treated with the help of computed tomography (CT) scans. In this paper, we apply radiomics to select 3-D features from CT images of the lung toward providing prognostic information
Externí odkaz:
https://doaj.org/article/99f387dd1c2f4bbb929129a89909dc2f
Autor:
Satrajit Basu, Robert A. Gatenby, Samuel H. Hawkins, John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Lawrence O. Hall, Robert J. Gillies, Virendra Kumar, Dmitry B. Goldgof
Publikováno v:
IEEE Access, Vol 2, Pp 1418-1426 (2014)
Nonsmall cell lung cancer is a prevalent disease. It is diagnosed and treated with the help of computed tomography (CT) scans. In this paper, we apply radiomics to select 3-D features from CT images of the lung toward providing prognostic information
Autor:
Virendra Kumar, Lawrence H. Schwartz, Ying Liu, Hua Wang, Jongphil Kim, Lawrence O. Hall, Dmitry B. Goldgof, Binsheng Zhao, Satrajit Basu, Yoganand Balagurunathan, Robert J. Gillies, Yuhua Gu, Rene Korn, Robert A. Gatenby, Steven A. Eschrich
Publikováno v:
Journal of digital imaging. 27(6)
Quantitative size, shape, and texture features derived from computed tomographic (CT) images may be useful as predictive, prognostic, or response biomarkers in non-small cell lung cancer (NSCLC). However, to be useful, such features must be reproduci
Autor:
Yuhua Gu, Robert A. Gatenby, David Fenstermacher, Steven A. Eschrich, Yoganand Balagurunathan, Lawrence O. Hall, Satrajit Basu, Matthew B. Schabath, Andre Dekker, Virendra Kumar, Hugo J.W.L. Aerts, Kenneth M. Forster, Anders Berglund, Philippe Lambin, Robert J. Gillies, Dmitry B. Goldgof
“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with computed tomography (CT), positron emission tomography (PET) or magnetic resonance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de68579dd197045ce0b9cec2fe5372f8
https://europepmc.org/articles/PMC3563280/
https://europepmc.org/articles/PMC3563280/
Autor:
Lawrence O. Hall, Satrajit Basu, Jung Choi, Yuhua Gu, Dmitry B. Goldgof, Robert J. Gillies, Virendra Kumar, Robert A. Gatenby
Publikováno v:
SMC
A CT-scan is a vital tool for the diagnosis of lung cancer via tumor detection. Developing a classifier to make use of the information in CT-scan images could provide a non-invasive alternative to histopathological techniques such as needle biopsy to