Morphological Operations to Segment a Tumor from a Magnetic Resonance Image

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. A...

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Bibliographic Details
Published inJournal of information and communication convergence engineering Vol. 12; no. 1; pp. 60 - 65
Main Authors Thapaliya, Kiran, Kwon, Goo-Rak
Format Journal Article
LanguageKorean
Published 2014
Subjects
Gradient
Thresholding
Flood-fill algorithm
Morphological operations
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Summary:This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.
Bibliography:KISTI1.1003/JNL.JAKO201411560018350
ISSN:2234-8255
2234-8883