Print Email Facebook Twitter Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy Title Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy Author Geldof, Freija (Netherlands Cancer Institute) Dashtbozorg, Behdad (Netherlands Cancer Institute) Hendriks, B.H.W. (TU Delft Medical Instruments & Bio-Inspired Technology; Philips Research) Sterenborg, Henricus J.C.M. (Netherlands Cancer Institute; Amsterdam UMC) Ruers, Theo J.M. (Netherlands Cancer Institute; University of Twente) Date 2022 Abstract During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice. To reference this document use: http://resolver.tudelft.nl/uuid:7f8d91b5-19ab-4ecf-a7d7-f11c213ef34d DOI https://doi.org/10.1038/s41598-022-05751-5 ISSN 2045-2322 Source Scientific Reports, 12 (1) Part of collection Institutional Repository Document type journal article Rights © 2022 Freija Geldof, Behdad Dashtbozorg, B.H.W. Hendriks, Henricus J.C.M. Sterenborg, Theo J.M. Ruers Files PDF s41598_022_05751_5.pdf 2.45 MB Close viewer /islandora/object/uuid:7f8d91b5-19ab-4ecf-a7d7-f11c213ef34d/datastream/OBJ/view