Title :
A New Approach for Bacillus Colonies Recognition: Application of Intuitionistic Fuzzy Sets Theory
Author_Institution :
Tarbiat Modares Univ., Tehran
Abstract :
This paper proposes a new approach for medical diagnosis based on laboratory empirical data using fuzzy set theory. The presented approach is based on intuitionistic fuzzy set (IFSs) theory as a special kind of fuzzy set using two new distance measures between intuitionistic fuzzy sets as a tool in pattern recognition. We will apply them in a part of progress of medical diagnosis in order to recognize Bacillus colonies and then we compare its results with similar measures in regular fuzzy. Numerical results show that the proposed measures are more applicable in medical diagnosis than the similar measures in regular fuzzy ones.
Keywords :
fuzzy set theory; medical diagnostic computing; microorganisms; patient diagnosis; pattern recognition; Bacillus colonies; fuzzy sets theory; laboratory empirical data; medical diagnosis; pattern recognition; Biomedical measurements; Fuzzy set theory; Fuzzy sets; Laboratories; Medical diagnosis; Medical diagnostic imaging; Microscopy; Pattern recognition; Shape; Uncertainty; Bacillus Recognition; Distance Measure; Intuitionistic Fuzzy Sets; Medical Diagnosis;
Conference_Titel :
BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-0-7695-3118-2
DOI :
10.1109/BMEI.2008.281