Morphological Operations to Segment a Tumor from a Magnetic Resonance Image

• Published in: Journal of Information and Communication Convergence Engineering, 12(1) Vol. 12; no. 1; pp. 60 - 65
• Main Authors: Thapaliya, Kiran, Kwon, Goo-Rak
• Format: Journal Article
• Language: English
• Published: 한국정보통신학회 31.03.2014
• Subjects: 전자/정보통신공학
• ISSN: 2234-8255; 2234-8883
• DOI: 10.6109/jicce.2014.12.1.060

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. KCI Citation Count: 1