Overview of automatic seed selection methods for biomedical images Segmentation
Joint Authors
Mulawwih, Ahlem
Layachi, Sumayyah
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 3 (31 May. 2018), pp.499-504, 6 p.
Publisher
Publication Date
2018-05-31
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Abstract EN
In biomedical image processing, image segmentation is a relevant research area due to its wide spread usage and application.
Seeded region growing is very attractive for semantic image segmentation by involving the high-level knowledge of image components in the seed point selection procedure.
However, the seeded region growing algorithm suffers from the problems of automatic seed point generation.
A seed point is the starting point for region growing and its selection is very important for the success of segmentation process.
This paper presents an extensive survey on works carried out in the area of automatic seed point selection for biomedical images segmentation by seeded region growing algorithm.
The main objective of this study is to provide an overview of the most recent trends for seed point selection in biomedical image segmentation.
American Psychological Association (APA)
Mulawwih, Ahlem& Layachi, Sumayyah. 2018. Overview of automatic seed selection methods for biomedical images Segmentation. The International Arab Journal of Information Technology،Vol. 15, no. 3, pp.499-504.
https://search.emarefa.net/detail/BIM-839273
Modern Language Association (MLA)
Mulawwih, Ahlem& Layachi, Sumayyah. Overview of automatic seed selection methods for biomedical images Segmentation. The International Arab Journal of Information Technology Vol. 15, no. 3 (May. 2018), pp.499-504.
https://search.emarefa.net/detail/BIM-839273
American Medical Association (AMA)
Mulawwih, Ahlem& Layachi, Sumayyah. Overview of automatic seed selection methods for biomedical images Segmentation. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 3, pp.499-504.
https://search.emarefa.net/detail/BIM-839273
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 503-504
Record ID
BIM-839273