Open AccessIdentification of high grade and low grade tumors in MR Brain Image using Modified Monkey Search Algorithm
Author(s) -
Saravanan Alagarsamy,
T. Abitha,
S. Ajitha,
Sangeetha T.S,
Vishnuvarthanan Govindaraj
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/993/1/012052
Subject(s) - segmentation , artificial intelligence , identification (biology) , computer science , pixel , process (computing) , position (finance) , image segmentation , magnetic resonance imaging , pattern recognition (psychology) , computer vision , task (project management) , boundary (topology) , field (mathematics) , mathematics , radiology , medicine , biology , engineering , botany , finance , pure mathematics , economics , operating system , mathematical analysis , systems engineering
Detection of tumors present in the Magnetic Resonance brain image is a challenging task in the research field of medical imaging processing. The tumors with distinguished boundaries are difficult to find in the MR brain images, while performing the manual segmentation process. There is a necessity of an automated segmentation technique for performing better segmentation in terms of tumors with distinguished boundaries. The automated modified monkey search technique is used to find the optimized cluster position, and a random search operation is performed is locate all the pixels present in the image and then finally the location of the tumor region is exactly segmented/predicted by using the suggested monkey search algorithm. The suggested technique will support the radiologist for finding the tumors with distinguishing boundaries and accuracy of prediction of tumors is also improved lot with this approach. Based on the early prediction of tumors, diagnosing procedures will save the lives of many human beings.