Optoacoustic Tissue Differentiation Using a Mach-Zehnder Interferometer

Kenhagho, Herve Nguendon and Rauter, Georg and Guzman, Raphael and Cattin, Philippe C. and Zam, Azhar. (2019) Optoacoustic Tissue Differentiation Using a Mach-Zehnder Interferometer. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control (IEEE T ULTRASON FERR), 66 (9). pp. 1435-1443.

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Official URL: https://edoc.unibas.ch/78666/

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Laser osteotomy offers a way to make precise and less traumatic cuts smaller than conventional mechanical bone surgery tools. To fully exploit the advantages of laser osteotomy over conventional osteotomy, real-time feedback to differentiate the hard bone from the surrounding soft tissues is desired. In this study, we differentiated various tissue types-hard and soft bone, fat, muscle, and skin tissues from five proximal and distal fresh porcine femurs-based on cutting sounds. For laser ablation, an Nd:YAG laser was used to create ten craters on the surface of each proximal and distal femurs. For sound recording, the probing beam of a Mach-Zehnder interferometer was placed 5 cm away from each ablation site. For offline tissue differentiation, we investigated the measurements by looking at the amplitude frequency band between 0.83 and 1.25 MHz, which provides the least average classification error. Then, we used principal component analysis to reduce the dimensionality and the 95% confidence ellipsoid (Mahalanobis distance) method to differentiate between tissues based on the acoustic shock wave. A set of 14 400 data points, measured from ten craters in four proximal and distal femurs, was used as "training data," while a set of 3600 data points from ten craters in the remaining proximal and distal femurs was considered as "testing data." As is seen in the confusion matrix, the experimental-based scores of hard and soft bones, fat, muscles, and skin yielded average classification errors (with leave-one-out cross validation) of 0.11%, 57.69%, 0.06%, 0.14%, and 2.92%, respectively. The results of this study demonstrate a promising technique for differentiating tissues during laser osteotomy.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Laser and Robotics > Bio-Inspired Robots for Medicine-Lab (Rauter)
UniBasel Contributors:Rauter, Georg
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:01 Oct 2020 06:54
Deposited On:01 Oct 2020 06:54

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