Soltaninejad, Mohammadreza, Ye, Xujiong, Yang, Guang , Allinson, Nigel and Lambrou, Tryphon (2014) Brain tumour grading in different MRI protocols using SVM on statistical features. In: MIUA 2014, 9th July 2014, Royal Holloway.
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15957 Brain Tumour Grading_15957.pdf - Whole Document 366kB | |
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| Item Type: | Conference or Workshop contribution (Paper) |
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| Item Status: | Live Archive |
Abstract
In this paper a feasibility study of brain MRI dataset classification, using ROIs which have been segmented either manually or through a superpixel based method in conjunction with statistical pattern recognition methods is presented. In our study, 471 extracted ROIs from 21 Brain MRI datasets are used, in order to establish which features distinguish better between three grading classes. 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 the 1st and 2nd order statistics, achieved high classification accuracy in pair-wise grading comparisons.
| Keywords: | Brain tumour grading, MRI images, superpixel segmentation, pattern recognition, SVM classification. |
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| Subjects: | G Mathematical and Computer Sciences > G740 Computer Vision |
| Divisions: | College of Science > School of Computer Science |
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| ID Code: | 15957 |
| Deposited On: | 08 Nov 2014 18:16 |
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