Paper Info
Title
Fuzzy inference system for osteoporosis detection.
Abstract
The goal of this paper is to propose a fuzzy inference framework for diagnosis of osteoporosis disease in the field of medical imaging. The idea behind such a framework is to assist the physician to detect, control and treat various forms of osteoporosis in better way. The degree of disease is computed by fuzzy expert system and conventional X-ray image processing technique and a final decision is taken by combining both the results. Primary advantage of proposed algorithm is: (a) The fuzzy expert system performs as an expert to diagnosis and (I)) The X-ray imaging system calculates bone density. The use of different membership functions and extensive number of rules; in addition to the fuzzy edge directed image interpolation (FEDI) technique helps design an efficient osteoporosis detection framework. The extensive experiments conducted on 20 patients have demonstrated that the proposed algorithm can replace the existing, expensive and not readily available bone density calculation techniques in this field.
Year
Venue
Keywords
2016
IEEE Global Humanitarian Technology Conference Proceedings
fuzzy logic,image interpolation,membership functions,Osteoporosis,rules
Field
DocType
ISSN
Data mining,Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy logic,Image processing,Artificial intelligence,Adaptive neuro fuzzy inference system,Machine learning,Image scaling
Conference
2377-6919
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
C. Reshmalakshmi110.69
M. Sasikumar200.68