| Literature DB >> 30441386 |
Mousumi Roy, Fusheng Wang, George Teodoro, Jose Velazqeuz Vega, Daniel Brat, Jun Kong.
Abstract
Cellular phenotypic features derived from histopathology images are the basis of pathologic diagnosis and are thought to be related to underlying molecular profiles. Due to overwhelming cell numbers and population heterogeneity, it remains challenging to quantitatively compute and compare features of cells with distinct molecular signatures. In this study, we propose a self-reliant and efficient analysis framework that supports quantitative analysis of cellular phenotypic difference across distinct molecular groups. To demonstrate efficacy, we quantitatively analyze astrocytomas that are molecularly characterized as either Isocitrate Dehydrogenase (IDH) mutant (MUT) or wildtype (WT) using imaging data from The Cancer Genome Atlas database. Representative cell instances that are phenotypically different between these two groups are retrieved after segmentation, feature computation, data pruning, dimensionality reduction, and unsupervised clustering. Our analysis is generic and can be applied to a wide set of cell-based biomedical research.Entities:
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Year: 2018 PMID: 30441386 PMCID: PMC7363437 DOI: 10.1109/EMBC.2018.8513157
Source DB: PubMed Journal: Annu Int Conf IEEE Eng Med Biol Soc ISSN: 2375-7477