title: Automated, quantitative analysis of histopathological staining in nuclei.
abstract: Technological advances have allowed the generation of high-throughput imaging of tissue sections. However, the analysis of these samples is typically still performed manually by one or multiple pathologists. We present a novel statistical model for the automated, quantitative analysis of these images. Our approach requires minimal tuning and allows recapitulation of estimates of staining strength in the nuclei of tumor cells as estimated by the gold standard. Besides, it compares favorably to other quantitative approaches available in the public domain.
authors.affiliation: Duke University, Durham, NC.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Henao
authors.affiliation: Duke University, Durham, NC.
authors.forename: Joseph
authors.initials: J
authors.lastname: Geradts
authors.affiliation: Dartmouth College, Hanover, NH.
authors.forename: Manabu
authors.initials: M
authors.lastname: Kurokawa
authors.affiliation: Duke University, Durham, NC.
authors.forename: Sally
authors.initials: S
authors.lastname: Kornbluth
authors.affiliation: Quintiles, Durham, NC.
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Lucas