Mr. Tsutomu Enjoji Profile

Tsutomu Enjoji

at Nagoya Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 30 April 2004 Paper

Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.536385

KEYWORDS: Cameras, Image registration, Filtering (signal processing), Motion estimation, Image processing, Endoscopes, Endoscopy, 3D image processing, Navigation systems, Medical imaging

Read Abstract +

This paper describes a new method for calculating image similarity between a real bronchoscopic (RB) image and a virtual endoscopic (VE) image for bronchoscope tracking based on image registration. Camera motion tracking is sequentially done by finding viewing parameters (camera position and orientation) that can render the most similar VE image to a currently processing RB frame based on image similarity, since it is difficult to attach a positional sensor at the tip of a bronchoscope. In the previous method, image similarity was calculated between real and virtual endoscopic images by summing gray-level differences up for all pixels of two images. This method could not estimate positions and orientations of a real bronchoscope camera properly, when image similarity changed only a little (but partly changed significantly) due to averaging of gray-level differences for the entire image. The proposed method divides the real and virtual endoscopic images into a set of subregions and selects the subregions that contain characteristic shapes such as the bifurcation and folding patterns of the bronchus. The proposed image similarity measure is implemented in the bronchoscope navigation system that equips the prediction function of the bronchoscope motion based on Kalman filtering. The predicted results are used as initial estimations of image registration. We applied the proposed method to eight pairs of bronchoscopic videos and three-dimensional (3-D) chest CT images. The experimental results showed that the proposed method improved the tracking performance by five orders of magnitude over the previous method. Computation time for one frame decreased to 20% of the previous method's.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

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.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years