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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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Pubblicato in:J Med Imaging (Bellingham)
Autori principali: 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
Natura: Artigo
Lingua:Inglês
Pubblicazione: Society of Photo-Optical Instrumentation Engineers 2018
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Accesso online: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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