Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities
Joint Authors
Source
International Journal of Biomedical Imaging
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-08
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema.
In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method.
Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study.
The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs.
In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.
American Psychological Association (APA)
Zayed, Nourhan& Elnemr, Heba A.. 2015. Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities. International Journal of Biomedical Imaging،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1065278
Modern Language Association (MLA)
Zayed, Nourhan& Elnemr, Heba A.. Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities. International Journal of Biomedical Imaging No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1065278
American Medical Association (AMA)
Zayed, Nourhan& Elnemr, Heba A.. Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities. International Journal of Biomedical Imaging. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1065278
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1065278