Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-Site Robustness Assessment

Aubreville M, Goncalves M, Knipfer C, Oetter N, Würfl T, Neumann H, Stelzle F, Bohr C, Maier A (2018)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2018

Publisher: SCITEPRESS – Science and Technology Publications, Lda

Pages Range: 27-34

Conference Proceedings Title: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018)

Event location: Funchal

ISBN: 978-989-758-278-3

URI: http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006534700270034

DOI: 10.5220/0006534700270034

Abstract

Deep learning technologies such as convolutional neural networks (CNN) provide powerful methods for image recognition and have recently been employed in the field of automated carcinoma detection in confocal laser endomicroscopy (CLE) images. CLE is a (sub-)surface microscopic imaging technique that reaches magnifications of up to 1000x and is thus suitable for in vivo structural tissue analysis. In this work, we aim to evaluate the prospects of a priorly developed deep learning-based algorithm targeted at the identification of oral squamous cell carcinoma with regard to its generalization to further anatomic locations of squamous cell carcinomas in the area of head and neck. We applied the algorithm on images acquired from the vocal fold area of five patients with histologically verified squamous cell carcinoma and presumably healthy control images of the clinically normal contra-lateral vocal cord. We find that the network trained on the oral cavity data reaches an accuracy

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Involved external institutions

Universitätsklinikum Hamburg-Eppendorf (UKE) Germany (DE) Johannes Gutenberg-Universität Mainz (JGU) Germany (DE)

How to cite

APA:

Aubreville, M., Goncalves, M., Knipfer, C., Oetter, N., Würfl, T., Neumann, H.,... Maier, A. (2018). Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-Site Robustness Assessment. In Sheldon Wiebe, Hugo Gamboa,Ana Fred, Sergi Bermúdez i Badia (Eds.), Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) (pp. 27-34). Funchal, PT: SCITEPRESS – Science and Technology Publications, Lda.

MLA:

Aubreville, Marc, et al. "Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-Site Robustness Assessment." Proceedings of the BIOIMAGING 2018, Funchal Ed. Sheldon Wiebe, Hugo Gamboa,Ana Fred, Sergi Bermúdez i Badia, SCITEPRESS – Science and Technology Publications, Lda, 2018. 27-34.

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