Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network

Alex Tinggaard Årsvold; Andreas Sørensen Zeltner; Zhuoqi Cheng; Kim Lindberg Schwaner; Pernille Tine Jensen; Thiusius Rajeeth Savarimuthu

doi:10.1109/ISMR48346.2021.9661502

Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network

Alex Tinggaard Årsvold, Andreas Sørensen Zeltner, Zhuoqi Cheng^*, Kim Lindberg Schwaner, Pernille Tine Jensen, Thiusius Rajeeth Savarimuthu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Lymphadenectomy is frequently performed as a surgical treatment for cancer. Lymph nodes grow inside fat and have similar color as fat, making them difficult to detect. In Robotic Assisted Minimally Invasive Surgery (RAMIS), it can be even more challenging due to the lack of haptic feedback. This study proposes a novel method to measure the electrical property of a target tissue site and determine whether a lymph node is present underneath through an Artificial Neural Network classifier. The proposed system and method are built, analyzed, and evaluated based on simulation and ex vivo tissue phantom experiments. The experimental results show a very high accuracy (93.49 %) in detecting a lymph node that is embedded deep inside fat. Given the promising results and the portability of the proposed system, we believe it has great potential to improve the quality of related surgical procedures.

Original language	English
Title of host publication	2021 International Symposium on Medical Robotics (ISMR)
Number of pages	6
Publisher	IEEE
Publication date	Nov 2021
ISBN (Electronic)	978-1-6654-0622-2
DOIs	https://doi.org/10.1109/ISMR48346.2021.9661502
Publication status	Published - Nov 2021
Event	2021 International Symposium on Medical Robotics (ISMR) - Georgia Tech, Atlanta, United States Duration: 17. Nov 2021 → 19. Nov 2021 http://www.ismr.gatech.edu/

Conference

Conference	2021 International Symposium on Medical Robotics (ISMR)
Location	Georgia Tech
Country/Territory	United States
City	Atlanta
Period	17/11/2021 → 19/11/2021
Internet address	http://www.ismr.gatech.edu/

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10.1109/ISMR48346.2021.9661502

Arsvold2021_LymphNodeDetectionUsingRobotAssistedElectricalImpedanceScanningAccepted manuscript, 575 KB
Open Access VersionAccepted manuscript, 587 KB

Best Student Paper Award
Årsvold, Alex Tinggaard (Recipient), Zeltner, Andreas Sørensen (Recipient), Cheng, Zhuoqi (Recipient), Schwaner, Kim Lindberg (Recipient), Jensen, Pernille Tine (Recipient) & Savarimuthu, Thiusius R. (Recipient), 19. Nov 2021
Prize: Prizes, scholarships, distinctions

Cite this

@inproceedings{d0b7d85093a54e8ea5b0a668d70cf4da,

title = "Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network",

abstract = "Lymphadenectomy is frequently performed as a surgical treatment for cancer. Lymph nodes grow inside fat and have similar color as fat, making them difficult to detect. In Robotic Assisted Minimally Invasive Surgery (RAMIS), it can be even more challenging due to the lack of haptic feedback. This study proposes a novel method to measure the electrical property of a target tissue site and determine whether a lymph node is present underneath through an Artificial Neural Network classifier. The proposed system and method are built, analyzed, and evaluated based on simulation and ex vivo tissue phantom experiments. The experimental results show a very high accuracy (93.49 %) in detecting a lymph node that is embedded deep inside fat. Given the promising results and the portability of the proposed system, we believe it has great potential to improve the quality of related surgical procedures.",

author = "{\AA}rsvold, {Alex Tinggaard} and Zeltner, {Andreas S{\o}rensen} and Zhuoqi Cheng and Schwaner, {Kim Lindberg} and Jensen, {Pernille Tine} and Savarimuthu, {Thiusius Rajeeth}",

year = "2021",

month = nov,

doi = "10.1109/ISMR48346.2021.9661502",

language = "English",

booktitle = "2021 International Symposium on Medical Robotics (ISMR)",

publisher = "IEEE",

address = "United States",

note = "2021 International Symposium on Medical Robotics (ISMR), ISMR 2021 ; Conference date: 17-11-2021 Through 19-11-2021",

url = "http://www.ismr.gatech.edu/",

}

Årsvold, AT, Zeltner, AS, Cheng, Z , Schwaner, KL , Jensen, PT & Savarimuthu, TR 2021, Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network. in 2021 International Symposium on Medical Robotics (ISMR). IEEE, 2021 International Symposium on Medical Robotics (ISMR), Atlanta, Georgia, United States, 17/11/2021. https://doi.org/10.1109/ISMR48346.2021.9661502

TY - GEN

T1 - Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network

AU - Årsvold, Alex Tinggaard

AU - Zeltner, Andreas Sørensen

AU - Cheng, Zhuoqi

AU - Schwaner, Kim Lindberg

AU - Jensen, Pernille Tine

AU - Savarimuthu, Thiusius Rajeeth

PY - 2021/11

Y1 - 2021/11

N2 - Lymphadenectomy is frequently performed as a surgical treatment for cancer. Lymph nodes grow inside fat and have similar color as fat, making them difficult to detect. In Robotic Assisted Minimally Invasive Surgery (RAMIS), it can be even more challenging due to the lack of haptic feedback. This study proposes a novel method to measure the electrical property of a target tissue site and determine whether a lymph node is present underneath through an Artificial Neural Network classifier. The proposed system and method are built, analyzed, and evaluated based on simulation and ex vivo tissue phantom experiments. The experimental results show a very high accuracy (93.49 %) in detecting a lymph node that is embedded deep inside fat. Given the promising results and the portability of the proposed system, we believe it has great potential to improve the quality of related surgical procedures.

AB - Lymphadenectomy is frequently performed as a surgical treatment for cancer. Lymph nodes grow inside fat and have similar color as fat, making them difficult to detect. In Robotic Assisted Minimally Invasive Surgery (RAMIS), it can be even more challenging due to the lack of haptic feedback. This study proposes a novel method to measure the electrical property of a target tissue site and determine whether a lymph node is present underneath through an Artificial Neural Network classifier. The proposed system and method are built, analyzed, and evaluated based on simulation and ex vivo tissue phantom experiments. The experimental results show a very high accuracy (93.49 %) in detecting a lymph node that is embedded deep inside fat. Given the promising results and the portability of the proposed system, we believe it has great potential to improve the quality of related surgical procedures.

U2 - 10.1109/ISMR48346.2021.9661502

DO - 10.1109/ISMR48346.2021.9661502

M3 - Article in proceedings

BT - 2021 International Symposium on Medical Robotics (ISMR)

PB - IEEE

T2 - 2021 International Symposium on Medical Robotics (ISMR)

Y2 - 17 November 2021 through 19 November 2021

ER -

Lymph Node Detection Using Robot Assisted Electrical Impedance Scanning and an Artificial Neural Network

Abstract

Conference

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Related Prizes

Best Student Paper Award

Cite this