Automated Region Growing for Segmentation of Brain Lesion in Diffusion-weighted MRI
This paper presents an automatic segmentation of brain lesions from diffusion-weighted magnetic resonance imaging (DW-MRI or DWI) using region growing approach. The lesions are acute infarction, haemorrhage, tumour and abscess. Region splitting and merging is used to detect the lesion region. Then,...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/9482/1/2012_Paper_Automated_Region_Growing_for_Segmentation.pdf http://eprints.utem.edu.my/id/eprint/9482/ http://www.iaeng.org/IMECS2012/ |
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| Summary: | This paper presents an automatic segmentation of brain lesions from diffusion-weighted magnetic resonance imaging (DW-MRI or DWI) using region growing approach. The lesions are acute infarction, haemorrhage, tumour and abscess. Region splitting and merging is used to detect the lesion region. Then, histogram thresholding technique is applied to automate the seeds selection. The region is iteratively grown by comparing all unallocated neighbour pixels to the seeds. The difference between pixel’s intensity value and the region’s mean is used as the similarity measure. Evaluation is made for performance comparison between automatic and manual seeds selection. Overall, automated region growing algorithm provides comparable results with the semi-automatic segmentation. |
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