Earticle

초록

영어

Prostate segmentation from MRI is a necessary first step and plays an important role in clinical decision making process. A MR T1 Image segmentation method of the prostate based on distance regularized level set evolution (DRLSE) is proposed. To smooth the prostate image to reduce the noise, a preprocessed prostate image with Gaussian kernel and get an edge indicator is convolved. We construct an energy function with a distance regularization term and an external energy term containing the edge indicator and minimize it by solving the gradient flow which can be implemented with a finite difference scheme. In segmentation experiments, the impact of parameters λ , μ , α and ε in DRLSE model on the image segmentation is analyzed, and an optimal value of these parameters is given. The experiment results confirm the effectiveness of the MRI segmentation method of prostate for different situation of different patients.

목차

Abstract
 1. Introduction
 2. DRLSE
 3. Segmentation of the Prostate Based on DRLSE
  3.1. Preprocessing
 4. Experiment Results
 5. Conclusion
 Acknowledgements
 Reference

키워드

저자

• Yong-de Zhang [ Intelligent Machine Institute, Harbin University of Science and Technology, China ]
• Jing-chun Peng [ Intelligent Machine Institute, Harbin University of Science and Technology, China, Harbin Huade University, China ]
• Gang Liu [ Intelligent Machine Institute, Harbin University of Science and Technology, China ]
• Jin-gang Jiang [ Intelligent Machine Institute, Harbin University of Science and Technology, China ]
• Yan-jiang Zhao [ Intelligent Machine Institute, Harbin University of Science and Technology, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605