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Proceedings Paper

Symmetry analysis to detect pathological brain in MRI
Author(s): Enmin Song; Qian Wang; Guangzhi Ma
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Paper Abstract

This paper focuses on the symmetry analysis for brain MRI images in 2D slices. It can be used to detect 2D pathological brain automatically. The main challenges in this work are the extraction of the geometry symmetry axis (GSA) from both normal and pathological neuroimages and the quantification of the symmetry for the gray level distribution (GLS) of the brain with the GSA. We present a fast approach to extract the GSA based on a group of assistant parallel lines and to make veracity estimation for the GSA using the resultant moment of gravitational force (RMGF), followed by quantification for the two hemispheres partitioned by the GSA based on the correlation to the GLS. Finally, the quantification results are considered as a feature to distinguish the normal and abnormal brain slices. In the experiment result, the mean running time of each symmetry quantization measure for 181×217 2D 8bits MRI images was 0.91 seconds, the area of the corresponding ROC curve to distinguish the normal and abnormal brain of this approach is 0.9628, which shows that to detect the pathological brain in MRI based on this symmetry analysis is fast and effective.

Paper Details

Date Published: 14 November 2007
PDF: 6 pages
Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67891F (14 November 2007); doi: 10.1117/12.750987
Show Author Affiliations
Enmin Song, Huazhong Univ. of Science and Technology (China)
Qian Wang, Huazhong Univ. of Science and Technology (China)
Guangzhi Ma, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6789:
MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques

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