257 / 1971-01-01 00:00:00
3d Mr Brain Image Segmentation Through Quantum Particle Swarm Optimization-based Algorithm
MRI,Segmentation,QPSO,HMRF,EM
终稿
Jun Sun / 江南大学
Xiwei Mei / 江南大学
Jiajia Shi / 江南大学
In this paper, a novel segmentation methodol-
ogy for Magnetic Resonance Image (MRI) of brain tissues
is presented and validated. The method is inspired by
our previously developed quantum-behaved particle swarm
optimization (QPSO) algorithm, and combined with Hid-
den Markov Random Field model and the Expectation-
Maximization algorithm (HMRF-EM), which can be applied
to MRIs in real-time environments. The QPSO is a stochastic
optimization algorithm, which shows better performance
than the standard particle swarm optimization (PSO) algo-
rithm. This hybrid method shows less sensitivity to the initial
estimation of parameters in contrast with other traditional
stochastic optimization techniques for MRF. Experimental
results on both simulated and real MR images are presented
to verify the advantages of the proposed method over its
competitors.
重要日期
  • 会议日期

    01月22日

    2015

    02月23日

    2015

  • 12月20日 2014

    初稿截稿日期

  • 12月20日 2014

    提前注册日期

  • 12月31日 2014

    终稿截稿日期

  • 02月23日 2015

    注册截止日期

  • 04月20日 2015

    摘要截稿日期

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