Brain tumour grading in different MRI protocols using SVM on statistical features

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Title: Brain tumour grading in different MRI protocols using SVM on statistical features
Authors: Soltaninejad, M
Ye, X
Yang, G
Allinson, N
Lambrou, T
Item Type: Conference Paper
Abstract: In this paper a feasibility study of brain MRI data set classification, using ROIs which have been segmented either manually or throug h a superpixel based method in conjunction with statistical pattern recognition me thods is presented. In our study, 471 extracted ROIs from 21 Brain MRI datasets are u sed, in order to establish which features distinguish better between three grading c lasses. Thirty-eight statistical measurements were collected from the ROIs. We found by using the Leave-One-Out method that the combination of the features from th e 1 st and 2 nd order statistics, achieved high classification accuracy in pair-wise grading comparisons.
Issue Date: 8-Nov-2014
Date of Acceptance: 8-Nov-2014
URI: http://hdl.handle.net/10044/1/43282
Publisher: British Machine Vision Association
Journal / Book Title: Medical Image Understanding and Analysis
Copyright Statement: © 2014 The Author(s).
Conference Name: Medical Image Understanding and Analysis
Publication Status: Published
Start Date: 2014-07-09
Finish Date: 2014-07-11
Conference Place: Egham, UK
Open Access location: http://cityuni.staging.squizedge.net/__data/assets/pdf_file/0003/225084/Paper59.pdf
Appears in Collections:National Heart and Lung Institute



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