Name
Abstract | ||
|---|---|---|
We present both a high-level symbolic model of the human brain, and a method of using this model to aid in the recognition of objects from medical images. The model is stored as a frame based semantic network consisting of three coexisting graphs (a spatial adjacency graph; a part hierarchy; and an inheritance graph). We propose a method similar to assumption-based truth maintenance systems for the collating and reasoning processes required in the labelling of input images. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1016/0262-8856(94)90003-5 | Image and Vision Computing |
Keywords | Field | DocType |
medical images,model-based recognition,anatomical objects,object centred,representation,medical image interpretation,semantic network | Adjacency list,Computer vision,Graph,Pattern recognition,Computer science,Semantic network,Frame based,Artificial intelligence,Voronoi diagram,Hierarchy,Truth maintenance | Journal |
Volume | Issue | ISSN |
12 | 8 | Image and Vision Computing |
ISBN | Citations | PageRank |
3-540-56800-X | 12 | 6.19 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Glynn P. Robinson | 1 | 43 | 14.26 |
| Alan C. F. Colchester | 2 | 634 | 250.27 |
| Lewis D. Griffin | 3 | 381 | 45.96 |