TY - GEN
T1 - Optoacoustic Tissue Differentiation Using a Mach-Zehnder Interferometer
T2 - 2018 IEEE International Ultrasonics Symposium, IUS 2018
AU - Kenhagho, Herve Nguendon
AU - Rauter, Georg
AU - Guzman, Raphael
AU - Cattin, Philippe
AU - Zam, Azhar
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/17
Y1 - 2018/12/17
N2 - As laser osteotomy offers precise and small cuts with less trauma compared to conventional mechanical bone surgery. To fully exploit the advantages of laserosteotomes over conventional osteotomes, real-time feedback to differentiate hard bone from surrounding soft tissues is desired. In this study, we differentiated various tissue types - hard bone, fat and muscle tissue from an upper and lower fresh porcine thigh - based on cutting sounds. For laser ablation, an Nd:YAG laser was used to create ten craters on the surface of each upper and lower thigh. For sound recording, the probing beam of a Mach-Zehnder interferometer was placed 5cm away from each ablation site. For offline tissue differentiation, we investigated the measurements by looking at the amplitude of the spectrum. Then, we used Principle Component Analysis (PCA) to reduce the dimensionally and the 95% confidence ellipsoid (Mahalanobis distance) method to differentiate between tissues based on the acoustic shock wave. A set of 2520 data points, measured from the first seven craters of the upper and lower thigh, was used as 'training data' a set of 1080 data points from the last three craters was considered as 'testing data'. As seen in the confusion matrix, the experimental data from hard bone, fat and muscle yielded error rates of 0.46%, 0.19% and 1.30%, respectively. Preliminary results of this study demonstrate a promising technique for differentiating bone, fat and muscle tissues during laser surgery.
AB - As laser osteotomy offers precise and small cuts with less trauma compared to conventional mechanical bone surgery. To fully exploit the advantages of laserosteotomes over conventional osteotomes, real-time feedback to differentiate hard bone from surrounding soft tissues is desired. In this study, we differentiated various tissue types - hard bone, fat and muscle tissue from an upper and lower fresh porcine thigh - based on cutting sounds. For laser ablation, an Nd:YAG laser was used to create ten craters on the surface of each upper and lower thigh. For sound recording, the probing beam of a Mach-Zehnder interferometer was placed 5cm away from each ablation site. For offline tissue differentiation, we investigated the measurements by looking at the amplitude of the spectrum. Then, we used Principle Component Analysis (PCA) to reduce the dimensionally and the 95% confidence ellipsoid (Mahalanobis distance) method to differentiate between tissues based on the acoustic shock wave. A set of 2520 data points, measured from the first seven craters of the upper and lower thigh, was used as 'training data' a set of 1080 data points from the last three craters was considered as 'testing data'. As seen in the confusion matrix, the experimental data from hard bone, fat and muscle yielded error rates of 0.46%, 0.19% and 1.30%, respectively. Preliminary results of this study demonstrate a promising technique for differentiating bone, fat and muscle tissues during laser surgery.
KW - Acoustic tissue response
KW - laser ablation
KW - Mach-Zehnder interferometer
KW - tissue differentiation
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U2 - 10.1109/ULTSYM.2018.8579654
DO - 10.1109/ULTSYM.2018.8579654
M3 - Conference contribution
AN - SCOPUS:85057978975
T3 - IEEE International Ultrasonics Symposium, IUS
BT - 2018 IEEE International Ultrasonics Symposium, IUS 2018
PB - IEEE Computer Society
Y2 - 22 October 2018 through 25 October 2018
ER -