Dr. Zhen Ye Profile

Dr. Zhen Ye

at Kent State Univ

SPIE Involvement:

Author

Publications (2)

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 | 12 May 2004 Paper

A fast 3D region growing approach for CT angiography applications

Zhen Ye, Zhongmin Lin, Cheng-chang Lu

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.533741

KEYWORDS: Image segmentation, 3D image processing, Bone, Image processing algorithms and systems, Skull, Angiography, Computed tomography, Brain, 3D applications, 3D displays

Read Abstract +

Region growing is one of the most popular methods for low-level image segmentation. Many researches on region growing have focused on the definition of the homogeneity criterion or growing and merging criterion. However, one disadvantage of conventional region growing is redundancy. It requires a large memory usage, and the computation-efficiency is very low especially for 3D images. To overcome this problem, a non-recursive single-pass 3D region growing algorithm named SymRG is implemented and successfully applied to 3D CT angiography (CTA) applications for vessel segmentation and bone removal. The method consists of three steps: segmenting one-dimensional regions of each row; doing region merging to adjacent rows to obtain the region segmentation of each slice; and doing region merging to adjacent slices to obtain the final region segmentation of 3D images. To improve the segmentation speed for very large volume 3D CTA images, this algorithm is applied repeatedly to newly updated local cubes. The next new cube can be estimated by checking isolated segmented regions on all 6 faces of the current local cube. This local non-recursive 3D region-growing algorithm is memory-efficient and computation-efficient. Clinical testings of this algorithm on Brain CTA show this technique could effectively remove whole skull, most of the bones on the skull base, and reveal the cerebral vascular structures clearly.

Proceedings Article | 15 May 1997 Paper

Stereoscopic display using multimedia and depth sense test

Jiaxin Wang, Zaixing Zhang, Peifa Jia, Zhen Ye

Proceedings Volume 3012, (1997) https://doi.org/10.1117/12.274472

KEYWORDS: Cameras, Multimedia, Stereoscopic displays, Head, CRTs, Projection systems, Spherical lenses, Video, RGB color model, Nanoelectromechanical systems

Read Abstract +

A vision telepresence system was built in our lab, including stereoscopic display on a CRT and a spherical screen. Two images from two cameras are sent to two multimedia video cards (grand-video cards), Ml and Mr. The two cards, Ml and Mr, transform from two video signals of two cameras to RGB signals in its memory. The field synchronism signal of a VGA card is used as a switch, which takes the two RGB signals in Ml and Mr alternately and sends them into a CRT display or a projector for the spherical screen. In fact, the images of two cameras are put into multimedia cards at lower frequency, but are taken from multimedia cards and shown on CRT at higher frequency, the display may be at higher field frequency. The twinkle can be improved. In order to test the depth sense of the stereoscopic display, an experiment was made in our lab. The purpose of the test is to check the effect for the subjects to use the stereoscopic display to recognize the depth of objects. The test result gives some conclusion. (1) The stereo-display-mode (SDM) using 124 mm camera-distance is worse (has bigger depth-error) than the nude-eye-mode (NEM). But the SDM using 226 mm camera-distance is better than the NEM. (2) The 20 m object-distance has bigger depth-error than the 10 m object-distance. And the 30 m object-distance has very big depth-errors

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