Title :
Osteoporosis classification using fuzzy rule based and neural networks
Author :
Badawi, Ahmed M.
Author_Institution :
Fac. of Eng., Cairo Univ.
Abstract :
Most bone densitometry ultrasound devices measure only single predefined peripheral skeletal site. We propose a classification system to study the ability of combining speed of sound (SOS) measured at multiple bone sites to differentiate subjects with osteoporosis fractures from normal subjects based on fuzzy logic and neural networks systems. Classification rates were found to be 100% for training set and 97% for testing set for a dataset of 66 subjects
Keywords :
biomedical ultrasonics; bone; densitometry; image classification; medical image processing; neural nets; ultrasonic imaging; bone densitometry ultrasound devices; classification rates; fuzzy logic; fuzzy rule; neural networks; osteoporosis classification; osteoporosis fracture; peripheral skeletal site; sound speed; Bones; Density measurement; Fuzzy logic; Fuzzy neural networks; Neural networks; Osteoporosis; Testing; Ultrasonic imaging; Ultrasonic variables measurement; Velocity measurement;
Conference_Titel :
Circuits and Systems, 2003 IEEE 46th Midwest Symposium on
Conference_Location :
Cairo
Print_ISBN :
0-7803-8294-3
DOI :
10.1109/MWSCAS.2003.1562304
