Differentiation between nerve and adipose tissue using wide‐band spectroscopy 2 features is allowed. Binary logistic regression identified gradient Ft5 (B1 – W1) and amplitude difference Ft7 (B5 – B1) as most promising combination for differentiation of RLN from surrounding adipose tissue. Figure 9.4 shows a scatter plot for these Si‐sensor based features, extracted for nerve and adipose tissue. Data for both thyroid and parathyroid surgery, and carpal tunnel release surgery are included. The quantitative results of classification performance are listed in Table 9.2 for both cross‐validation approaches. LOO cross‐validation is solely based on Si‐sensor range data from thyroid and parathyroid surgery for train and test purposes. TT cross‐validation is based on data from thyroid and parathyroid surgery for train purposes and 137 on additional carpal tunnel release surgery data for test purposes. Figure 9.4 Scatter plot of two selected features within Si‐range Scatter plot showing two computer‐selected features (gradient Ft5 and amplitude difference Ft7). Data measured during thyroid and parathyroid surgery and carpal tunnel release surgery are included.
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