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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| Format: | Article |
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2012
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| author | Mohd. Saad, Norhashimah Syed Abu Bakar, Syed Abd. Rahman Muda, Sobri Mohd. Mokji, Musa Abdullah, Abdul Rahim |
| author_facet | Mohd. Saad, Norhashimah Syed Abu Bakar, Syed Abd. Rahman Muda, Sobri Mohd. Mokji, Musa Abdullah, Abdul Rahim |
| author_sort | Mohd. Saad, Norhashimah |
| 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 | 2024-03-05T19:20:36Z |
| format | Article |
| id | utm.eprints-46631 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:20:36Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | utm.eprints-466312017-09-17T07:58:50Z http://eprints.utm.my/46631/ Automated region growing for segmentation of brain lesion in diffusion-weighted MRI Mohd. Saad, Norhashimah Syed Abu Bakar, Syed Abd. Rahman Muda, Sobri Mohd. Mokji, Musa Abdullah, Abdul Rahim QA Mathematics 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. 2012 Article PeerReviewed Mohd. Saad, Norhashimah and Syed Abu Bakar, Syed Abd. Rahman and Muda, Sobri and Mohd. Mokji, Musa and Abdullah, Abdul Rahim (2012) Automated region growing for segmentation of brain lesion in diffusion-weighted MRI. Lecture Notes In Engineering And Computer Science, 1 . pp. 674-677. ISSN 2078-0966 |
| spellingShingle | QA Mathematics Mohd. Saad, Norhashimah Syed Abu Bakar, Syed Abd. Rahman Muda, Sobri Mohd. Mokji, Musa Abdullah, Abdul Rahim 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 | QA Mathematics |
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