In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response

Jun Kong, Lee Cooper, Carlos Moreno, Fusheng Wang, Tahsin Kurc, Joel Saltz, Daniel Brat
2011 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
In this paper, we present a complete and novel workflow for quantitative nuclear feature analysis of glioblastoma using high-throughput whole-slide microscopy image processing as it relates to treatment response and patient survival. With a complete suite of computer algorithms, large numbers of micro-anatomical structures, in this case nuclei, are analyzed and represented efficiently from whole-slide digitized images with numerical features. With regard to endpoints of treatment response, the
more » ... omputerized analysis presents a better discrimination than traditional neuropathologic review. As a result, this analysis method shows potential to facilitate a better understanding of disease progression and patients' response to therapy for glioblastoma.
doi:10.1109/iembs.2011.6089903 pmid:22254257 pmcid:PMC3292262 dblp:conf/embc/KongCMWKSB11 fatcat:7exrpb4slzdshdps4inb5w2rla