Format

Send to:

Choose Destination
See comment in PubMed Commons below
Conf Proc IEEE Eng Med Biol Soc. 2011;2011:87-90. doi: 10.1109/IEMBS.2011.6089903.

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

Author information

  • 1Emory University, Center for Comprehensive Informatics, Atlanta, GA 30322, USA. jun.kong@emory.edu

Abstract

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 computerized 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.

PMID:
22254257
[PubMed - indexed for MEDLINE]
PMCID:
PMC3292262
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for IEEE Engineering in Medicine and Biology Society Icon for PubMed Central
    Loading ...
    Write to the Help Desk