Real-time 3D medical structure segmentation using fast evolving active contours

Xiaotao Wang; Qiang Wang; Zhihui Hao; Kuanhong Xu; Ping Guo; Haibing Ren; Wooyoung Jang; Jung-bae Kim

doi:10.1117/12.2042974

21 March 2014 Real-time 3D medical structure segmentation using fast evolving active contours

Xiaotao Wang, Qiang Wang, Zhihui Hao, Kuanhong Xu, Ping Guo, Haibing Ren, Wooyoung Jang, Jung-bae Kim

Author Affiliations +

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 903443 (2014) https://doi.org/10.1117/12.2042974
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Segmentation of 3D medical structures in real-time is an important as well as intractable problem for clinical applications due to the high computation and memory cost. We propose a novel fast evolving active contour model in this paper to reduce the requirements of computation and memory. The basic idea is to evolve the brief represented dynamic contour interface as far as possible per iteration. Our method encodes zero level set via a single unordered list, and evolves the list recursively by adding activated adjacent neighbors to its end, resulting in active parts of the zero level set moves far enough per iteration along with list scanning. To guarantee the robustness of this process, a new approximation of curvature for integer valued level set is proposed as the internal force to penalize the list smoothness and restrain the list continual growth. Besides, list scanning times are also used as an upper hard constraint to control the list growing. Together with the internal force, efficient regional and constrained external forces, whose computations are only performed along the unordered list, are also provided to attract the list toward object boundaries. Specially, our model calculates regional force only in a narrowband outside the zero level set and can efficiently segment multiple regions simultaneously as well as handle the background with multiple components. Compared with state-of-the-art algorithms, our algorithm is one-order of magnitude faster with similar segmentation accuracy and can achieve real-time performance for the segmentation of 3D medical structures on a standard PC.

Citation Download Citation

Xiaotao Wang, Xiaotao Wang, Qiang Wang, Qiang Wang, Zhihui Hao, Zhihui Hao, Kuanhong Xu, Kuanhong Xu, Ping Guo, Ping Guo, Haibing Ren, Haibing Ren, Wooyoung Jang, Wooyoung Jang, Jung-bae Kim, Jung-bae Kim, "Real-time 3D medical structure segmentation using fast evolving active contours", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903443 (21 March 2014); doi: 10.1117/12.2042974; https://doi.org/10.1117/12.2042974

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

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: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years