Abstract:
BACKGROUND AND OBJECTIVE:Accurate and fast vessel segmentation from liver slices remain challenging and important tasks for clinicians. The algorithms from the literature are slow and less accurate. We propose fast parallel gradient based seeded region growing for vessel segmentation. Seeded region growing is tedious when the inter connectivity between the elements is unavoidable. Parallelizing region growing algorithms are essential towards achieving real time performance for the overall process of accurate vessel segmentation. METHODS:The parallel implementation of seeded region growing for vessel segmentation is iterative and hence time consuming process. Seeded region growing is implemented as kernel termination and relaunch on GPU due to its iterative mechanism. The iterative or recursive process in region growing is time consuming due to intermediate memory transfers between CPU and GPU. We propose persistent and grid-stride loop based parallel approach for region growing on GPU. We analyze static region of interest of tiles on GPU for the acceleration of seeded region growing. RESULTS:We aim fast parallel gradient based seeded region growing for vessel segmentation from CT liver slices. The proposed parallel approach is 1.9x faster compared to the state-of-the-art. CONCLUSION:We discuss gradient based seeded region growing and its parallel implementation on GPU. The proposed parallel seeded region growing is fast compared to kernel termination and relaunch and accurate in comparison to Chan-Vese and Snake model for vessel segmentation.
journal_name
Comput Methods Programs Biomedjournal_title
Computer methods and programs in biomedicineauthors
Satpute N,Naseem R,Palomar R,Zachariadis O,Gómez-Luna J,Cheikh FA,Olivares Jdoi
10.1016/j.cmpb.2020.105430subject
Has Abstractpub_date
2020-08-01 00:00:00pages
105430eissn
0169-2607issn
1872-7565pii
S0169-2607(19)32381-8journal_volume
192pub_type
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journal_title:Computer methods and programs in biomedicine
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journal_title:Computer methods and programs in biomedicine
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journal_title:Computer methods and programs in biomedicine
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journal_title:Computer methods and programs in biomedicine
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