DocumentCode :
3586086
Title :
MRI brain tumor recognition using Modified Shuffled Frog Leaping Algorithm
Author :
Ladgham, Anis ; Sakly, Anis ; Mtibaa, Abdellatif
Author_Institution :
Electr. Dept., Nat. Sch. of Eng. of Monastir, Ibn Eljazzar, Tunisia
fYear :
2014
Firstpage :
504
Lastpage :
507
Abstract :
This paper presents a novel optimal algorithm for MRI brain tumor recognition. To do this, we use the newly developed meta-heuristic MSFLA (Modified Shuffled Frog Leaping Algorithm). Otherwise, a suitable choice of the fitness function ensures faster time of research with greater chance of convergence to the optimal value. The calculation of the used fitness function is linked to the image. The image must be scanned to calculate this function. For this, this function assists to quickly discover the adequate area modeling the tumor. Computer simulation results illustrate the effectiveness of the developed algorithm.
Keywords :
biomedical MRI; evolutionary computation; medical image processing; object recognition; tumours; MRI brain tumor recognition; fitness function; magnetic resonance imaging; metaheuristic MSFLA; modified shuffled frog leaping algorithm; Algorithm design and analysis; Genetic algorithms; Image recognition; Image segmentation; Magnetic resonance imaging; Optimization; Tumors; Fitness function; MRI tumor; MSFLA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014 15th International Conference on
Type :
conf
DOI :
10.1109/STA.2014.7086694
Filename :
7086694
Link To Document :
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