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

fYear

35765

fDate

8-10 Dec1997

Firstpage

80

Lastpage

84

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Systems, 1997. IIS '97. Proceedings

Conference_Location

Grand Bahama Island

Print_ISBN

0-8186-8218-3

Type

conf

DOI

10.1109/IIS.1997.645190

Filename

645190