BACKGROUND: Thyroidectomy is one of the most commonly performed surgical procedures. The region of the neck has a very complex structural organization. It would be beneficial to introduce a tool that can assist the surgeon in tissue discrimination during the procedure. One such solution is the noninvasive and contactless technique, called hyperspectral imaging (HSI). METHODS: To interpret the HSI data, we implemented a supervised classification method to automatically discriminate the parathyroid, the thyroid, and the recurrent laryngeal nerve from surrounding tissue(muscle, skin) and materials (instruments, gauze). A leave-one-patient-out cross-validation was performed. RESULTS: The best performance was obtained using support vector machine (SVM) with a classification and visualization in less than 1.4 seconds. A mean patient accuracy of 68\% $\pm$ 23\% was obtained for all tissues and material types. CONCLUSIONS: The proposed method showed promising results and have to be confirmed on a larger cohort of patient data.
%0 Journal Article
%1 Maktabi2020-fk
%A Maktabi, Marianne
%A Köhler, Hannes
%A Ivanova, Magarita
%A Neumuth, Thomas
%A Rayes, Nada
%A Seidemann, Lena
%A Sucher, Robert
%A Jansen-Winkeln, Boris
%A Gockel, Ines
%A Barberio, Manuel
%A Chalopin, Claire
%D 2020
%I Wiley
%J Int. J. Med. Robot.
%K and assisted computer guided head imaged imaging; intraoperative neck; surgery; thyroidectomy
%N 5
%P 1--10
%T Classification of hyperspectral endocrine tissue images using support vector machines
%V 16
%X BACKGROUND: Thyroidectomy is one of the most commonly performed surgical procedures. The region of the neck has a very complex structural organization. It would be beneficial to introduce a tool that can assist the surgeon in tissue discrimination during the procedure. One such solution is the noninvasive and contactless technique, called hyperspectral imaging (HSI). METHODS: To interpret the HSI data, we implemented a supervised classification method to automatically discriminate the parathyroid, the thyroid, and the recurrent laryngeal nerve from surrounding tissue(muscle, skin) and materials (instruments, gauze). A leave-one-patient-out cross-validation was performed. RESULTS: The best performance was obtained using support vector machine (SVM) with a classification and visualization in less than 1.4 seconds. A mean patient accuracy of 68\% $\pm$ 23\% was obtained for all tissues and material types. CONCLUSIONS: The proposed method showed promising results and have to be confirmed on a larger cohort of patient data.
@article{Maktabi2020-fk,
abstract = {BACKGROUND: Thyroidectomy is one of the most commonly performed surgical procedures. The region of the neck has a very complex structural organization. It would be beneficial to introduce a tool that can assist the surgeon in tissue discrimination during the procedure. One such solution is the noninvasive and contactless technique, called hyperspectral imaging (HSI). METHODS: To interpret the HSI data, we implemented a supervised classification method to automatically discriminate the parathyroid, the thyroid, and the recurrent laryngeal nerve from surrounding tissue(muscle, skin) and materials (instruments, gauze). A leave-one-patient-out cross-validation was performed. RESULTS: The best performance was obtained using support vector machine (SVM) with a classification and visualization in less than 1.4 seconds. A mean patient accuracy of 68\% $\pm$ 23\% was obtained for all tissues and material types. CONCLUSIONS: The proposed method showed promising results and have to be confirmed on a larger cohort of patient data.},
added-at = {2024-09-10T11:54:51.000+0200},
author = {Maktabi, Marianne and K{\"o}hler, Hannes and Ivanova, Magarita and Neumuth, Thomas and Rayes, Nada and Seidemann, Lena and Sucher, Robert and Jansen-Winkeln, Boris and Gockel, Ines and Barberio, Manuel and Chalopin, Claire},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/25a5f1758ecc38c4c6b4a26664d80cb18/scadsfct},
copyright = {http://creativecommons.org/licenses/by-nc/4.0/},
interhash = {286852a1e027aa07962543539cc016df},
intrahash = {5a5f1758ecc38c4c6b4a26664d80cb18},
journal = {Int. J. Med. Robot.},
keywords = {and assisted computer guided head imaged imaging; intraoperative neck; surgery; thyroidectomy},
language = {en},
month = oct,
number = 5,
pages = {1--10},
publisher = {Wiley},
timestamp = {2024-09-10T11:54:51.000+0200},
title = {Classification of hyperspectral endocrine tissue images using support vector machines},
volume = 16,
year = 2020
}