Name
Abstract | ||
|---|---|---|
•A semiotics-driven framework for understanding knowledge-driven interaction in medical image segmentation is proposed.•This framework is grounded in Peircean semiotics in order to structure and characterize how particular interactions are interpreted by both the user and the computer.•Using the notion of interface metaphors, this framework shows how metaphor quality metrics can be used to analyze interaction and improve ease-of-use in communicating complex anatomical knowledge. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.media.2017.11.007 | Medical Image Analysis |
Keywords | Field | DocType |
Medical image segmentation,Peircean semiotics,Human computer interaction,Interface metaphors | Computer vision,Semiosis,Symbol,Semiotics,Computer science,Schematic,Image segmentation,Artificial intelligence,Interface metaphor | Journal |
Volume | ISSN | Citations |
44 | 1361-8415 | 0 |
PageRank | References | Authors |
0.34 | 49 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John S. H. Baxter | 1 | 74 | 14.67 |
| Eli Gibson | 2 | 188 | 23.91 |
| Roy Eagleson | 3 | 81 | 18.74 |
| Terry M. Peters | 4 | 1335 | 181.71 |