Title :
On-line estimation of the stapes-bone thickness in stapedotomy by learning a linear association of the force and torque drilling profiles
Author :
Kaburlasos, Vassilis G. ; Petridis, Vassilios ; Brett, P. ; Baker, Dave
Author_Institution :
Aristotle Univ. of Thessaloniki, Greece
Abstract :
The paper reports on the successful application of novel learning, classification and feature extraction techniques to the stapedotomy surgical procedure. Estimation of the stapes bone thickness from force and torque data during drilling was achieved by learning a linear mapping of force features to torque features. Learning was attained by employing the two level fuzzy lattice (2L-FL) scheme for supervised clustering. Experimental results demonstrate that the thickness of a stapes bone can be specified online during drilling
Keywords :
bone; feature extraction; fuzzy set theory; learning (artificial intelligence); medical expert systems; medical image processing; surgery; feature extraction techniques; force features; learning; linear association; linear mapping; online estimation; stapedotomy; stapes bone thickness; supervised clustering; surgical procedure; torque data; torque drilling profiles; torque features; two level fuzzy lattice; Auditory system; Bones; Drilling; Ear; Electronic mail; Lattices; Pistons; Prosthetics; Surgery; Torque;
Conference_Titel :
Intelligent Information Systems, 1997. IIS '97. Proceedings
Conference_Location :
Grand Bahama Island
Print_ISBN :
0-8186-8218-3
DOI :
10.1109/IIS.1997.645190
