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5 March 2021 Location-aware optical coherent tomography (OCT) tethered capsule endomicroscopy (TCE) of the small intestine
Du-Ri Song, David Odeke Otuya, Markus D. Herrmann, Camille Cunin, Patricia Grahmann, Mikayla Farham Tinus, Sarah Lynn Giddings, Guillermo J. Tearney
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Proceedings Volume 11620, Endoscopic Microscopy XVI; 1162006 (2021) https://doi.org/10.1117/12.2582910
Event: SPIE BiOS, 2021, Online Only
Abstract
For OCT-tethered capsule endomicroscopy (TCE) to be a useful minimally invasive tool for evaluating Crohn’s disease, the capsule must be able to be localized within the terminal ileum where the disease often manifests. Here, we developed a machine learning algorithm to assign OCT images of the small intestine into their corresponding anatomical regions. We selected a convolutional neural network and trained it on a set of 2108 cross-sectional images obtained from four swine ex vivo imaging studies to classify images into duodenum, jejunum, or terminal ileum. The model achieved 93±1.72% (95% confidence interval) accuracy on a separate test set of 846 images. These results suggest machine learning may be used to automatically determine when the capsule is in the terminal ileum, enabling microscopic evaluation of this anatomical segment that exhibits pathology in Crohn’s disease.
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Du-Ri Song, David Odeke Otuya, Markus D. Herrmann, Camille Cunin, Patricia Grahmann, Mikayla Farham Tinus, Sarah Lynn Giddings, and Guillermo J. Tearney "Location-aware optical coherent tomography (OCT) tethered capsule endomicroscopy (TCE) of the small intestine", Proc. SPIE 11620, Endoscopic Microscopy XVI, 1162006 (5 March 2021); https://doi.org/10.1117/12.2582910
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KEYWORDS
Optical coherence tomography
Intestine
Endomicroscopy
Data modeling
Tomography
Algorithm development
Imaging devices
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