Polyp-size classification with RGB-D features for colonoscopy

Hayato Itoh; Holger R. Roth; Yuichi Mori; Masashi Misawa; Masahiro Oda; Shin-ei Kudo; Kensaku Mori

doi:10.1117/12.2513093

13 March 2019 Polyp-size classification with RGB-D features for colonoscopy

Hayato Itoh, Holger R. Roth, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori

Proceedings Volume 10950, Medical Imaging 2019: Computer-Aided Diagnosis; 1095015 (2019) https://doi.org/10.1117/12.2513093
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Measurement of a polyp size is an essential task in colon cancer screening, since the polyp-size information has critical roles for decision on colonoscopy. However, an estimation of a polyp size from a single view of colonoscope without a measurement device is quite difficult even for expert physicians. To overcome this difficulty, automated size estimation techniques would be desirable for clinical scenes. This paper presents polyp-size classification method with a single colonoscopic image for colonoscopy. Our proposed method estimates depth information from a single colonoscopic image with trained model and utilises the estimated information for the classification. In our method, the model for depth information is obtained by deep learning with colonoscopic videos. Experimental results show the achievement of binary and trinary polyp-size classification with 79% and 74% accuracy from a single still image of a colonoscopic movie.

Conference Presentation

Citation Download Citation

Hayato Itoh, Holger R. Roth, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, and Kensaku Mori "Polyp-size classification with RGB-D features for colonoscopy", Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 1095015 (13 March 2019); https://doi.org/10.1117/12.2513093

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available