Identification and extraction of brain tumor from MRI using local statistics of Zernike moments
Kiran Thapaliya, Goo‐Rak Kwon · International Journal of Imaging Systems and Technology · 2014
ABSTRACT In this article, a novel method is proposed for the detection of brain tumor in magnetic resonance images (MRIs). The features of Zernike moments are used to analyze the MRIs. The image is divided into two parts from the center of the image based on the average value of the pixel located at the center boundary, and new image vectors are formed to extract the tumor. The local statistics values obtained from the low and high order Zernike moments are used to calculate the appropriate threshold value for efficient tumor extraction. The proposed method successfully analyzes the tumor part of the image on testing with different MRIs.