Yahya, Rafaa I. and Shamsuddin, Siti Mariyam and Yahya, Salah I. and Alsalibi, Bisan and Al-Khafaji, Ghada K. (2018) Membrane Computing for Real Medical Image Segmentation. ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 6 (2). pp. 27-38. ISSN 2410-9355
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Abstract
In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels of 8-adjacency give better results compared with the 4-adjacency neighborhood relations, because the 8-adjacency considers the eight pixels around the center pixel, which reduces the required communication rules to obtain the final segmentation results. The experimental results proved that the proposed approach has superior results in terms of the number of computational steps and processing time. To the best of our knowledge, this is the first time an evaluation procedure is conducted to evaluate the efficiency of real image segmentations using membrane computing.
| Item Type: | Article |
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| Uncontrolled Keywords: | Edge-based segmentation; medical images; membrane computing; P-Lingua; region-based segmentation; tissue-like P system |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | ARO-The Scientific Journal of Koya University > VOL 6, NO 2 (2018) |
| Depositing User: | Dr Salah Ismaeel Yahya |
| Date Deposited: | 17 Feb 2019 19:39 |
| Last Modified: | 30 Mar 2020 22:54 |
| URI: | http://eprints.koyauniversity.org/id/eprint/178 |
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