
Proceedings Paper
Validation of two techniques for intraoperative hyperspectral human tissue determinationFormat | Member Price | Non-Member Price |
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Paper Abstract
Hyperspectral imaging (HSI) is a non-contact optical imaging technique with the potential to serve as an intraoperative computer-aided diagnostic tool. This work analyzes the optical properties of visible structures in the surgical field for automatic tissue categorization. Building an HSI-based computer-aided tissue analysis system requires accurate ground truth and validation of optical soft tissue properties as these show large variability. In this paper, we introduce and validate two different hyperspectral intraoperative imaging setups and their use for the analysis of optical tissue properties. First, we present an improved multispectral filter-wheel setup integrated into a fully digital microscope. Second, we present a novel setup of two hyperspectral snapshot cameras for intraoperative usage. Both setups are operating in the spectral range of 400 nm up to 975 nm. They are calibrated and validated using the same database and calibration set. For validation, a color chart with 18 well-defined color spectra in the visual range is analyzed. Thus, the results acquired with both settings become transferable and comparable to each other as well as between different interventions. Clinical in-vivo data of two different oral and maxillofacial surgical procedures underline the potential of HSI as an intraoperative diagnostic tool and the clinical usability of both setups. Thereby, we demonstrate their feasibility for the in-vivo analysis and differentiation of different human soft tissues.
Paper Details
Date Published: 8 March 2019
PDF: 15 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511Z (8 March 2019); doi: 10.1117/12.2512811
Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)
PDF: 15 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511Z (8 March 2019); doi: 10.1117/12.2512811
Show Author Affiliations
Eric L. Wisotzky, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Humboldt-Univ. zu Berlin (Germany)
Benjamin Kossack, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Florian C. Uecker, Charité Universitätsmedizin Berlin (Germany)
Philipp Arens, Charité Universitätsmedizin Berlin (Germany)
Humboldt-Univ. zu Berlin (Germany)
Benjamin Kossack, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Florian C. Uecker, Charité Universitätsmedizin Berlin (Germany)
Philipp Arens, Charité Universitätsmedizin Berlin (Germany)
Steffen Dommerich, Charité Universitätsmedizin Berlin (Germany)
Anna Hilsmann, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Peter Eisert, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Humboldt-Univ. zu Berlin (Germany)
Anna Hilsmann, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Peter Eisert, Fraunhofer-Institut für Nachrichtentechnik Heinrich-Hertz-Institut (Germany)
Humboldt-Univ. zu Berlin (Germany)
Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)
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