Renal segmentation in physiological feature space with dynamic contrast enhanced MR Urography: preliminary research

Yang Tang; Hollie A. Jackson M.D.; Roger E. De Filippo; Susan Lee; Marvin D. Nelson Jr.; Rex A. Moats

doi:10.1117/12.833682

30 October 2009 Renal segmentation in physiological feature space with dynamic contrast enhanced MR Urography: preliminary research

Yang Tang, Hollie A. Jackson M.D., Roger E. De Filippo, Susan Lee, Marvin D. Nelson Jr., Rex A. Moats

Author Affiliations +

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74971J (2009) https://doi.org/10.1117/12.833682
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

The kidney is composed of many structurally and functionally different tissues. These functionally distinct tissues exhibit different magnetic resonance signal characteristics in typical MR Urography. This work exploits the tissue functional differences to construct a physiological feature space for renal segmentation, which has the more distinct meaning for directly functional evaluation, and lower requirements for storage and computation. In this preliminary research, a segmentation method was developed and investigated to demonstrate its feasibility on images obtained using a typical MR Urograpy protocol.

Citation Download Citation

Yang Tang, Hollie A. Jackson M.D., Roger E. De Filippo, Susan Lee, Marvin D. Nelson Jr., and Rex A. Moats "Renal segmentation in physiological feature space with dynamic contrast enhanced MR Urography: preliminary research", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74971J (30 October 2009); https://doi.org/10.1117/12.833682

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