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Online estimation of laser incision depth for transoral microsurgery: approach and preliminary evaluation
Author(s) -
Fichera Loris,
Pardo Diego,
Illiano Placido,
Ortiz Jesùs,
Caldwell Darwin G.,
Mattos Leonardo S.
Publication year - 2016
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1656
Subject(s) - laser , computer science , ex vivo , soft tissue , mean squared error , biomedical engineering , surgery , in vivo , medicine , mathematics , optics , statistics , biology , physics , microbiology and biotechnology
Background The use of lasers in transoral surgery enables precise tissue incision with minimal adverse effects on surrounding structures. Nonetheless, the lack of haptic feedback during laser cutting impairs the surgeon's perception of the incision depth, potentially leading to undesired tissue damage. Methods This paper presents a novel approach, based on statistical regression analysis, to estimate the laser incision depth in soft tissue. User trials were conducted in a laser surgery set‐up, to verify the effectiveness of online estimation of incision depth in supporting precise tissue cutting. Results The estimation accuracy was verified on ex vivo muscle tissue, revealing a root mean squared error (RMSE) of 0.1 mm for depths ranging up to 1.4 mm. Online estimation of depth has the potential to significantly improve the incision control of users. Conclusions The proposed approach was successful in producing estimations of laser cutting depth in ex vivo muscle tissue. Further investigation is required to validate this approach on other types of tissue. Providing depth estimation during laser cutting allows users to perform more precise incisions. Copyright © 2015 John Wiley & Sons, Ltd.