Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource MR Brain Tumor Classification and Segmentation Via Wavelets Subject The topic of the resource Discrete Wavelet Transform (DWT); Fejerkorovkin Filter; Kernel Support vector Machine (KSVM); Principlecomponent Analysis (PCA); Thresholding Description An account of the resource Timely, accurate detection of magnetic resonance (MR) images of brain is most important in the medical analysis. Many methods have already explained about the tumor classification in the literature. This paper explains the method of classifying MR brain images into normal or abnormal (affected by tumor), abnormality segments present in the image. This paper proposes DWT-discrete wavelet transform in first step to extract the image features from the given input image. To reduce the dimensions of the feature image principle component Analysis (PCA) is employed. Reduced extracted feature image is given to kernel support vector machine (KSVM) for processing. The data set has 90 brain MR images (both normal and abnormal) with seven common diseases. These images are used in KSVM process. Gaussian Radial Basis (GRB) kernel is used for the classification method proposed and yields maximum accuracy of 98% compared to linear kernel (LIN). From the analysis, compared with the existing methods GRB kernel method was effective. If this classification finds abnormal MR image with tumor then the corresponding part is separated and segmented by thresholding technique. 2018 IEEE. Creator An entity primarily responsible for making the resource Menaka Devi T.; Ramani G.; Xavier Arockiaraj S. Source A related resource from which the described resource is derived 2018 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2018 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/WiSPNET.2018.8538643" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/WiSPNET.2018.8538643</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059420027&amp;doi=10.1109%2FWiSPNET.2018.8538643&amp;partnerID=40&amp;md5=2f7735aeefa4acd13b69b342756f1577" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059420027&amp;doi=10.1109%2fWiSPNET.2018.8538643&amp;partnerID=40&amp;md5=2f7735aeefa4acd13b69b342756f1577</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-153863624-4 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Menaka Devi T., Department of Electronics and Communication Engineering, Adhiyamann College of Engineering, Hosur, 635109, India; Ramani G., Department of Electronics and Communication Engineering, CHRIST, Faculty of Engineering, Bengaluru, 560074, India; Xavier Arockiaraj S., Department of Electronics and Communication Engineering, CHRIST, Faculty of Engineering, Bengaluru, 560074, India