White-Matter Lesion Segmentation In Brain Mri Using Adaptive Trimmed Mean Approach
White Matter (WM) lesions are diffuse white matter abnormalities, that appear as hyperintense (bright) regions in cranial Magnetic Resonance Imaging (MRI). WM lesions are often observed in older population and are important indicators of stroke, multiple sclerosis, dementia and other brain-related d...
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| 主要作者: | |
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2011
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| 主题: | |
| 在线阅读: | http://eprints.usm.my/42262/1/ONG_KOK_HAUR.pdf |
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| 总结: | White Matter (WM) lesions are diffuse white matter abnormalities, that appear as hyperintense (bright) regions in cranial Magnetic Resonance Imaging (MRI). WM lesions are often observed in older population and are important indicators of stroke, multiple sclerosis, dementia and other brain-related disorders. Manual detection of WM lesions is laborious and the currently adopted visual scoring approaches for lesion grading is very subjective. In this thesis, a new approach for automated WM Lesions Segmentation is presented. In the proposed approach, the presence of WM lesions is detected as outliers in the intensity distribution of the
Fluid Attenuated Inversion Recovery (FLAIR) MR images using an Adaptive Outlier Detection technique. |
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