Gaussian Based Image Segmentation In The Presence Of Intensity Inhomogeneity
W. Shylu, A.Jackson Ribero · IOSR Journal of Electronics and Communication Engineering · 2014
In this project a variational level set approach for bias correction and segmentation in the analysis of magnetic resonance (MR) images with intensity inhomogeneities is proposed. Local intensity variations in relatively smaller regions are separable, despite of the inseparability of the whole image. Local intensity variations are described by the Gaussian distributions with different mean and variance. In this work the objective functions are integrated over the entire domain with local Gaussian distribution of fitting energy, ultimately analyzing the data with a level set framework.