A Region Based Method for Bias Correction of Images in Relating to Intensity Inhomogeneity in MRI
Image segmentation, snake rule, bias correction, intensity irregularity, MRI.
Intensity irregularity may be a sizeable challenge in image segmentation. The foremost wide used image segmentation algorithms are square measure region-based and usually deem the homogeneity of the image intensities within the regions of interest, which frequently fail to supply correct segmentation results thanks to the intensity irregularity. This paper proposes a completely unique region-based technique for image segmentation that is ready to affect intensity in homogeneities within the segmentation. First, supported the model of pictures with intensity in homogeneities, we have a tendency to derive an area intensity agglomeration property of the image intensities, and outline an area agglomeration criterion perform for the image intensities in an exceedingly neighborhood of every purpose. Snake rule is meant to be interactive, therein it detects on wherever regarding the boundaries square measure, so snake’s square measure want to minimize the energy and then trace the contour or boundary. Therefore, by minimizing this energy, snake rule is ready to at the same time phase the image and estimate the bias field, and therefore the calculable bias field will be used for intensity irregularity correction or Bias correction. Our technique has been valid on artificial pictures and real pictures of varied modalities, with fascinating performance in presence of intensity in homogeneities.
Padmavathi.C. "A Region Based Method for Bias Correction of Images in Relating to Intensity Inhomogeneity in MRI".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 1, pp.1021-1031, URL :https://rjwave.org/ijedr/papers/IJEDR1401183.pdf
Volume 2 Issue 1
Pages. 1021-1031
