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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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Bibliografiset tiedot
Julkaisussa:J Med Imaging (Bellingham)
Päätekijät: 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
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Society of Photo-Optical Instrumentation Engineers 2018
Aiheet:
Linkit: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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