Title :
Segmentation of brain tumors in computed tomography images using SVM classifier
Author :
Shanmugapriya, B. ; Ramakrishnan, T.
Author_Institution :
Dept. of Electron. & Instrum., Nat. Eng. Coll., Kovilpatti, India
Abstract :
Medical image processing is an interdisciplinary field that has been attracted by various fields such as applied mathematics, computer science and engineering, biology and medicine etc. Due to the development of technologies in imaging modalities, more challenges arise, how to process and analyze a huge volume of images for the diagnosis of diseases and treatment procedure. In this Support Vector Machines (SVMs) has been used to segment the brain tumors in Computed Tomography (CT) images. The two Kernel function of the SVM has been compared in which the RBF-SVM outperforms the other one.
Keywords :
brain; computerised tomography; diseases; image segmentation; medical image processing; radial basis function networks; support vector machines; tumours; Kernel function; RBF-SVM; SVM classifier; applied mathematics; biology; brain tumor segmentation; computed tomography images; computer science; disease diagnosis; engineering; imaging modalities; interdisciplinary field; medical image processing; medicine; support vector machines; treatment procedure; Accuracy; Image segmentation; Kernel; Medical diagnostic imaging; Polynomials; Support vector machines; CT; Polynomial; RBF; SVM; Segmentation;
Conference_Titel :
Electronics and Communication Systems (ICECS), 2014 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-2321-2
DOI :
10.1109/ECS.2014.6892709
