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Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth...

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Detalhes bibliográficos
Publicado no:J Med Imaging (Bellingham)
Main Authors: Davatzikos, Christos, Rathore, Saima, Bakas, Spyridon, Pati, Sarthak, Bergman, Mark, Kalarot, Ratheesh, Sridharan, Patmaa, Gastounioti, Aimilia, Jahani, Nariman, Cohen, Eric, Akbari, Hamed, Tunc, Birkan, Doshi, Jimit, Parker, Drew, Hsieh, Michael, Sotiras, Aristeidis, Li, Hongming, Ou, Yangming, Doot, Robert K., Bilello, Michel, Fan, Yong, Shinohara, Russell T., Yushkevich, Paul, Verma, Ragini, Kontos, Despina
Formato: Artigo
Idioma:Inglês
Publicado em: Society of Photo-Optical Instrumentation Engineers 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5764116/
https://ncbi.nlm.nih.gov/pubmed/29340286
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.5.1.011018
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