Earticle

초록

영어

Two region graph cut image partitioning after mapping entire image of brain in brain MRI. It is seen that piecewise constant model of the graph cut formulation becomes applicable when the image data is transformed by a main function. The proposed function contains data term to evaluate the deviation of the transformed data within two segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. Using a common function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation. The method results in good segmentations and runs faster the graph cut methods. The segmentation of MRI image is challenging due to the high diversity in appearance of tissue among the patient. An automatic interactive brain MRI image segmentation system with the ability to adjust operator control is achieved through this method.

목차

Abstract
 1. Introduction
 2. Graph Cut Segmentation
 3. Segmentation in the Kernel Induced Space
 4. Results
 5. Conclusions
 References

키워드

저자

• Jitendra Singh Sengar [ JSSRLPSP, Gwalior, India, ITM University, Gwalior, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605