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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Détails bibliographiques
Publié dans:J Med Imaging (Bellingham)
Auteurs principaux: 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
Format: Artigo
Langue:Inglês
Publié: Society of Photo-Optical Instrumentation Engineers 2018
Sujets:
Quantitative Imaging Methods and Translational Developments–Honoring the Memory of Dr. Larry Clarke
Accès en ligne: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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