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,...
| Main Authors: | , , , , |
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| Format: | Book Section |
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International Association of Engineers
2012
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| _version_ | 1796857375469076480 |
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| author | Mohd. Saad, N. Syed Abu Bakar, Syed Abdul Rahman Muda, S. Mohd. Mokji, Musa Abdullah, A. R. |
| author_facet | Mohd. Saad, N. Syed Abu Bakar, Syed Abdul Rahman Muda, S. Mohd. Mokji, Musa Abdullah, A. R. |
| author_sort | Mohd. Saad, N. |
| collection | ePrints |
| description | 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. |
| first_indexed | 2024-03-05T18:56:44Z |
| format | Book Section |
| id | utm.eprints-34545 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T18:56:44Z |
| publishDate | 2012 |
| publisher | International Association of Engineers |
| record_format | dspace |
| spelling | utm.eprints-345452017-08-06T00:52:40Z http://eprints.utm.my/34545/ Automated region growing for segmentation of brain lesion in diffusion-weighted MRI Mohd. Saad, N. Syed Abu Bakar, Syed Abdul Rahman Muda, S. Mohd. Mokji, Musa Abdullah, A. R. TK Electrical engineering. Electronics Nuclear engineering 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. International Association of Engineers 2012 Book Section PeerReviewed Mohd. Saad, N. and Syed Abu Bakar, Syed Abdul Rahman and Muda, S. and Mohd. Mokji, Musa and Abdullah, A. R. (2012) Automated region growing for segmentation of brain lesion in diffusion-weighted MRI. In: Lecture Notes in Engineering and Computer Science. International Association of Engineers, Hung To Road, Hong Kong, pp. 674-677. ISBN 978-988192511-4 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd. Saad, N. Syed Abu Bakar, Syed Abdul Rahman Muda, S. Mohd. Mokji, Musa Abdullah, A. R. Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title | Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title_full | Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title_fullStr | Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title_full_unstemmed | Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title_short | Automated region growing for segmentation of brain lesion in diffusion-weighted MRI |
| title_sort | automated region growing for segmentation of brain lesion in diffusion weighted mri |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
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