Gewählte Publikation:
SHR
Neuro
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Maktabi, M; Köhler, H; Ivanova, M; Neumuth, T; Rayes, N; Seidemann, L; Sucher, R; Jansen-Winkeln, B; Gockel, I; Barberio, M; Chalopin, C.
Classification of hyperspectral endocrine tissue images using support vector machines.
Int J Med Robot. 2020; 16(5):1-10
Doi: 10.1002/rcs.2121
Web of Science
PubMed
FullText
FullText_MUG
- Co-Autor*innen der Med Uni Graz
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Sucher Robert
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- 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% ± 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.
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Humans - administration & dosage
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Support Vector Machine - administration & dosage
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Thyroid Gland - diagnostic imaging, surgery
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Thyroidectomy - administration & dosage
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computer assisted surgery
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head and neck
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imaged guided surgery
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intraoperative imaging
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surgery
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thyroidectomy