Name
Title | ||
|---|---|---|
Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem. |
Abstract | ||
|---|---|---|
•The Quantitative Histopathological Imaging Ontology (QHIO) is proposed.•QHIO facilitates interoperability between histopathology datasets and algorithms.•By enforcing data compatibility, QHIO enables large-scale collaborative studies.•Researchers can easily find data and algorithms to suit their experimental needs.•Designed with OBO principles, QHIO integrates with existing biomedical ontologies. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jbi.2016.12.006 | Journal of Biomedical Informatics |
Keywords | DocType | Volume |
Histopathology imaging,Image analysis,Hot spot,Ontology,Breast cancer | Journal | 66 |
ISSN | Citations | PageRank |
1532-0464 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Metin N Gurcan | 1 | 630 | 59.30 |
| John E. Tomaszewski | 2 | 198 | 18.60 |
| James A. Overton | 3 | 65 | 9.56 |
| Scott Doyle | 4 | 327 | 21.56 |
| Alan Ruttenberg | 5 | 589 | 50.24 |
| Barry Smith | 6 | 928 | 91.98 |