title: Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.
abstract: Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts.
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA. Electronic address: metin.gurcan@osumc.edu.
authors.forename: Metin N
authors.initials: MN
authors.lastname: Gurcan
authors.affiliation: Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY 14214, USA.
authors.forename: John
authors.initials: J
authors.lastname: Tomaszewski
authors.affiliation: Knocean Inc., Toronto, Ontario M6P 2T3, Canada.
authors.forename: James A
authors.initials: JA
authors.lastname: Overton
authors.affiliation: Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY 14214, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Doyle
authors.affiliation: School of Dental Medicine, University at Buffalo, Buffalo NY, 14214, USA.
authors.forename: Alan
authors.initials: A
authors.lastname: Ruttenberg
authors.affiliation: Department of Philosophy, University at Buffalo, Buffalo, NY 14260, USA.
authors.forename: Barry
authors.initials: B
authors.lastname: Smith
mesh_terms: D064229:Biological Ontologies; D006653:Histology; D006801:Humans; D010336:Pathology; D015203:Reproducibility of Results
keywords: Breast cancer; Histopathology imaging; Hot spot; Image analysis; Ontology