Automated segmentation and characterization of esophageal wall in vivo by tethered capsule optical coherence tomography endomicroscopy.

Optical coherence tomography (OCT) is an optical diagnostic modality that can acquire cross-sectional images of the microscopic structure of the esophagus, including Barrett's esophagus (BE) and associated dysplasia. We developed a swallowable tethered capsule OCT endomicroscopy (TCE) device that acquires high-resolution images of entire gastrointestinal (GI) tract luminal organs. This device has a potential to become a screening method that identifies patients with an abnormal esophagus that should be further referred for upper endoscopy. Currently, the characterization of the OCT-TCE esophageal wall data set is performed manually, which is time-consuming and inefficient. Additionally, since the capsule optics optimally focus light approximately 500 µm outside the capsule wall and the best quality images are obtained when the tissue is in full contact with the capsule, it is crucial to provide feedback for the operator about tissue contact during the imaging procedure. In this study, we developed a fully automated algorithm for the segmentation of in vivo OCT-TCE data sets and characterization of the esophageal wall. The algorithm provides a two-dimensional representation of both the contact map from the data collected in human clinical studies as well as a tissue map depicting areas of BE with or without dysplasia. Results suggest that these techniques can potentially improve the current TCE data acquisition procedure and provide an efficient characterization of the diseased esophageal wall.