Title :
Image analysis using iconic fuzzy sets
Author_Institution :
Philips GmbH Forschunglab. Hamburg, West Germany
Abstract :
A formalism is presented for the iconic representation of knowledge in a semantic net. Nodes are represented as fuzzy sets, relations as functions over fuzzy sets. Moreover, the author demonstrates a consistent framework for the transition from the symbolic to the iconic level. He also defines a procedure for the explication, fuzzyfication and operationalization of natural language description predicates. This concept has successfully been used for a model-driven image analysis approach in the domain of MRI (magnetic resonance imaging) brain slices. The concept also has the potential for a data-driven approach. Measurements of features of fuzzy image structures can be represented in the semantic net as fuzzy assertions. Possible faults (pathologies) can be incorporated by using information form other sources (neurological studies) as (fuzzy) assertions.<>
Keywords :
biomedical NMR; computerised picture processing; fuzzy set theory; knowledge representation; medical computing; MRI; brain slices; iconic fuzzy sets; knowledge representation; magnetic resonance imaging; model-driven image analysis; natural language description predicates; semantic net; symbolic-iconic transition;
Conference_Titel :
Engineering in Medicine and Biology Society, 1988. Proceedings of the Annual International Conference of the IEEE
Conference_Location :
New Orleans, LA, USA
Print_ISBN :
0-7803-0785-2
DOI :
10.1109/IEMBS.1988.94554