PMID- 26649068
OWN - NLM
STAT- MEDLINE
DCOM- 20160829
LR  - 20181113
IS  - 1748-6718 (Electronic)
IS  - 1748-670X (Print)
IS  - 1748-670X (Linking)
VI  - 2015
DP  - 2015
TI  - A Hybrid Method for Image Segmentation Based on Artificial Fish Swarm Algorithm 
      and Fuzzy c-Means Clustering.
PG  - 120495
LID - 10.1155/2015/120495 [doi]
LID - 120495
AB  - Image segmentation plays an important role in medical image processing. Fuzzy 
      c-means (FCM) clustering is one of the popular clustering algorithms for medical 
      image segmentation. However, FCM has the problems of depending on initial 
      clustering centers, falling into local optimal solution easily, and sensitivity 
      to noise disturbance. To solve these problems, this paper proposes a hybrid 
      artificial fish swarm algorithm (HAFSA). The proposed algorithm combines 
      artificial fish swarm algorithm (AFSA) with FCM whose advantages of global 
      optimization searching and parallel computing ability of AFSA are utilized to 
      find a superior result. Meanwhile, Metropolis criterion and noise reduction 
      mechanism are introduced to AFSA for enhancing the convergence rate and antinoise 
      ability. The artificial grid graph and Magnetic Resonance Imaging (MRI) are used 
      in the experiments, and the experimental results show that the proposed algorithm 
      has stronger antinoise ability and higher precision. A number of evaluation 
      indicators also demonstrate that the effect of HAFSA is more excellent than FCM 
      and suppressed FCM (SFCM).
FAU - Ma, Li
AU  - Ma L
AD  - School of Information Science and Technology, Jinan University, Guangzhou 510632, 
      China.
FAU - Li, Yang
AU  - Li Y
AD  - School of Information Science and Technology, Jinan University, Guangzhou 510632, 
      China.
FAU - Fan, Suohai
AU  - Fan S
AD  - School of Information Science and Technology, Jinan University, Guangzhou 510632, 
      China.
FAU - Fan, Runzhu
AU  - Fan R
AD  - International School, Jinan University, Guangzhou 510632, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20151116
PL  - United States
TA  - Comput Math Methods Med
JT  - Computational and mathematical methods in medicine
JID - 101277751
SB  - IM
MH  - *Algorithms
MH  - Animals
MH  - Behavior, Animal
MH  - Brain/pathology
MH  - Cluster Analysis
MH  - Computational Biology
MH  - Fishes/physiology
MH  - Fuzzy Logic
MH  - Humans
MH  - Image Interpretation, Computer-Assisted/methods
MH  - Image Processing, Computer-Assisted/*methods
MH  - Magnetic Resonance Imaging/methods
MH  - Pattern Recognition, Automated/methods
PMC - PMC4663300
EDAT- 2015/12/10 06:00
MHDA- 2016/08/30 06:00
PMCR- 2015/11/16
CRDT- 2015/12/10 06:00
PHST- 2015/07/09 00:00 [received]
PHST- 2015/10/19 00:00 [accepted]
PHST- 2015/12/10 06:00 [entrez]
PHST- 2015/12/10 06:00 [pubmed]
PHST- 2016/08/30 06:00 [medline]
PHST- 2015/11/16 00:00 [pmc-release]
AID - 10.1155/2015/120495 [doi]
PST - ppublish
SO  - Comput Math Methods Med. 2015;2015:120495. doi: 10.1155/2015/120495. Epub 2015 
      Nov 16.