Optimized segmentation of brain images using shuffled frog leaping algorithm – Tabu search framework
- Citation data:
International Journal of Pharmaceutical Research, ISSN: 0975-2366, Vol: 10, Issue: 4, Page: 197-206
- Publication Year:
- Pharmacology, Toxicology and Pharmaceutics
Magnetic Resonance Imaging (MRI) technology allows us for obtaining digital images of brain. The real challenge is to accurately detect the tumor area in the brain, which is composed of the tumor and any edema. It comes to isolate a specific area among the other brain anatomical structures. Image segmentation is one of the most important operations in the field of medical image analysis. Thresholding is basically used because it provides high-speed operation and ease of implementation. This paper contains a new optimized method called Hybrid Shuffled Frog leaping Algorithm –Tabu search(SFLA-TS) method, a robust and fast algorithm, to detect the tumor part in MRI Brain images effectively. This method overcomes the limitations of local optimality of Shuffled Frog leaping Algorithm –Expected Maximization (SFLA-EM) method. In this proposed work hybrid SFLA with TS is used to improve the solution.