Paper Contents
Abstract
Image segmentation is the most challenging task in the field of medical image processing.Medical image segmentation is the most essential and crucial process in order to facilitate thecharacterization and visualization of the structure of interest in medical images. Segmentation of braintumor plays an important role in medical image analysis. Impact of tumor from MRI brain image dataremains an onerous task because of complex structure of brain tumors. To palliate the image artifactssuch as noise, intensity inhomogeneity, and improve the segmentation accuracy, a fruitful hybridclustering approach is proposed. This paper presents an efficient image segmentation approach usingan optimized hybrid clustering approach based on advanced morphological operations and dynamichistogram equalization. Results have been achieved using evaluation parameters like F score,precision, accuracy, specificity, and recall.
Copyright
Copyright © 2023 NANDHINI I. This is an open access article distributed under the Creative Commons Attribution License.
