Vo K, Jaremenko C, Bohr C, Neumann H, Maier A (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Springer Vieweg
Edited Volumes: Informatik aktuell
City/Town: Heidelberg
Pages Range: 312-317
Conference Proceedings Title: Bildverarbeitung für die Medizin 2017 Algorithmen Systeme Anwendungen
Event location: Heidelberg
ISBN: 978-3-662-54344-3
URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Vo17-ACA.pdf
DOI: 10.1007/978-3-662-54345-0_70
Confocal laser endomicroscopy is a novel imaging technique which provides real-time in vivo examination and histological analysis of tissue during an ongoing endoscopy. We present an automatic classification system that is able to differentiate between healthy and cancerous tissue of the vocal cords. Textural as well as CNN features are encoded using Fisher vectors and vector of locally aggregated descriptors while the classification is performed using random forests and support vector machines. Two experiments are investigated following a leave-one-sequence-out cross-validation and a fixed training and test set approach. Classification rates reach up to 87.6 % and 81.5 %, respectively.
APA:
Vo, K., Jaremenko, C., Bohr, C., Neumann, H., & Maier, A. (2017). Automatic Classification and Pathological Staging of Confocal Laser Endomicroscopic Images of the Vocal Cords. In Bildverarbeitung für die Medizin 2017 Algorithmen Systeme Anwendungen (pp. 312-317). Heidelberg: Heidelberg: Springer Vieweg.
MLA:
Vo, Kim, et al. "Automatic Classification and Pathological Staging of Confocal Laser Endomicroscopic Images of the Vocal Cords." Proceedings of the Bildverarbeitung für die Medizin 2017, Heidelberg Heidelberg: Springer Vieweg, 2017. 312-317.
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