title: Multi-class biological tissue classification based on a multi-classifier: Preliminary study of an automatic output power control for ultrasonic surgical units.
abstract: Ultrasonic surgical units (USUs) have the advantage of minimizing tissue damage during surgeries that require tissue dissection by reducing problems such as coagulation and unwanted carbonization, but the disadvantage of requiring manual adjustment of power output according to the target tissue. In order to overcome this limitation, it is necessary to determine the properties of in vivo tissues automatically. We propose a multi-classifier that can accurately classify tissues based on the unique impedance of each tissue. For this purpose, a multi-classifier was built based on single classifiers with high classification rates, and the classification accuracy of the proposed model was compared with that of single classifiers for various electrode types (Type-I: 6 mm invasive; Type-II: 3 mm invasive; Type-III: surface). The sensitivity and positive predictive value (PPV) of the multi-classifier by cross checks were determined. According to the 10-fold cross validation results, the classification accuracy of the proposed model was significantly higher (p<0.05 or <0.01) than that of existing single classifiers for all electrode types. In particular, the classification accuracy of the proposed model was highest when the 3mm invasive electrode (Type-II) was used (sensitivity=97.33-100.00%; PPV=96.71-100.00%). The results of this study are an important contribution to achieving automatic optimal output power adjustment of USUs according to the properties of individual tissues.
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: younsh00@skku.edu.
authors.forename: Su Hyun
authors.initials: SH
authors.lastname: Youn
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: tysim@skku.edu.
authors.forename: Taeyong
authors.initials: T
authors.lastname: Sim
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: avery@skku.edu.
authors.forename: Ahnryul
authors.initials: A
authors.lastname: Choi
authors.affiliation: Department of Health Science and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: j.song@skku.edu.
authors.forename: Jinsung
authors.initials: J
authors.lastname: Song
authors.affiliation: Applied Electromagnetic Wave Research Center, Korea Electrotechnology Research Ins., 111, Hanggaul-ro, Ansan, Gyeonggi-do, Republic of Korea; Department of Energy and Power Conversion Engineering, University of Science & Technology, 217, Gajeong-ro, Yuseong-gu, Daejeon, Republic of Korea. Electronic address: kyshin@keri.re.kr.
authors.forename: Ki Young
authors.initials: KY
authors.lastname: Shin
authors.affiliation: Chungwoo Co., Ltd., 2, Gasan digital 1-ro, Geumcheon-gu, Seoul, Republic of Korea. Electronic address: lee@mycw.co.kr.
authors.forename: Il Kwon
authors.initials: IK
authors.lastname: Lee
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: hhmoo91@naver.com.
authors.forename: Hyun Mu
authors.initials: HM
authors.lastname: Heo
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: daeweon@skku.edu.
authors.forename: Daeweon
authors.initials: D
authors.lastname: Lee
authors.affiliation: Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, Republic of Korea. Electronic address: jmun@skku.edu.
authors.forename: Joung Hwan
authors.initials: JH
authors.lastname: Mun
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D059708:Ultrasonic Surgical Procedures / Q000295:instrumentation* / Q000379:methods*
keywords: Impedance; Multi-classifier; Power auto-control; Tissue classification; Ultrasonic surgical units