Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning
Joint Authors
Kim, Kwang Baek
Park, Hyun Jun
Song, Doo Heon
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Accurate diagnosis of acute appendicitis is a difficult problem in practice especially when the patient is too young or women in pregnancy.
In this paper, we propose a fully automatic appendix extractor from ultrasonography by applying a series of image processing algorithms and an unsupervised neural learning algorithm, self-organizing map.
From the suggestions of clinical practitioners, we define four shape patterns of appendix and self-organizing map learns those patterns in pixel clustering phase.
In the experiment designed to test the performance for those four frequently found shape patterns, our method is successful in 3 types (1 failure out of 45 cases) but leaves a question for one shape pattern (80% correct).
American Psychological Association (APA)
Kim, Kwang Baek& Song, Doo Heon& Park, Hyun Jun. 2016. Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning. BioMed Research International،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1098040
Modern Language Association (MLA)
Kim, Kwang Baek…[et al.]. Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning. BioMed Research International No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1098040
American Medical Association (AMA)
Kim, Kwang Baek& Song, Doo Heon& Park, Hyun Jun. Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1098040
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1098040