We propose a method for the three-dimensional reconstruction from a single-shot colonoscopic image. Extracting a three-dimensional colon structure is an important task in colonoscopy. However, a colonoscope captures only two-dimensional information as colonoscopic images. Therefore, an estimation of three-dimensional information from two-dimensional images has potential demands. In this paper, we integrate deep-learning-based depth estimation to three-dimensional reconstruction. This approach omits the inaccurate corresponding matching from the procedure of conventional three-dimensional reconstruction. We experimentally demonstrated accurate reconstructions with comparisons between a polyp size in three-dimensional reconstruction and an endoscopist's measurement.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.