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This paper presents segmentation of brain's Magnetic Resonance image for tumor detection using Grammatical Swarm based clustering algorithm. Grammatical Swarm is a variant of Grammatical Evolution which can generate computer programs. First, MR images of brain are de-noised using Discrete Wavelet Transform based soft-thresholding technique. Grammatical Swarm based clustering algorithm is developed...
This paper presents a proof of concept for Artificial Neural Network training using Grammatical Swarm. Grammatical Swarm is a variant of Grammatical Evolution. The synaptic weight coefficients of a multilayer feed-forward neural network are evolved using Grammatical Swarm. The synaptic weight coefficients are derived from predefined Backus-Naur Form grammar for real value generation in a specified...
This paper presents an improved Particle Swarm Optimizer with opposition based learning method. The key feature of this method is that opposition based learning scheme is employed in personal best position of particles called pbest position in order to improve the performance of particle swarm optimizer. The proposed method is termed as OpbestPSO. OpbestPSO is applied on 12 benchmark problems. The...
A method of registration of progressively transmitted MR images with lesions are proposed. The MR image is segmented using Entropy Maximization together with Hybrid Particle Swarm Optimization that incorporates Wavelet Mutation operation. The segmented MR image is progressively received at the receiver's end. Registration is used to ensure correct transmission and fusion of segmented MR image with...
A Hybrid Particle Swarm Optimization algorithm that incorporates a Wavelet theory based mutation operation is used for segmentation of Magnetic Resonance Images. We use Entropy maximization using Hybrid Particle Swarm algorithm with Wavelet based mutation operation to get the region of interest of the Magnetic Resonance Image. It applies the Multi-resolution Wavelet theory to enhance the Particle...
We have devised a new technique to segment an diseased MRI image wherein the diseased part is segregated using a masking based thresholding technique together with entropy maximization. The particle swarm optimization technique (PSO) is used to get the region of interest (ROI) of the MRI image. The mask used is a variable mask. The rectangular mask is grown using an algorithm provided in the subsequent...
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