Segmentation of Endothelial Cell Boundaries of Rabbit Aortic Images Using a Machine Learning Approach
Joint Authors
Wagan, Asim I.
Bond, Andrew R.
Iftikhar, Saadia
Bharath, Anil A.
Weinberg, Peter D.
Source
International Journal of Biomedical Imaging
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper presents an automatic detection method for thin boundaries of silver-stained endothelial cells (ECs) imaged using light microscopy of endothelium mono-layers from rabbit aortas.
To achieve this, a segmentation technique was developed, which relies on a rich feature space to describe the spatial neighbourhood of each pixel and employs a Support Vector Machine (SVM) as a classifier.
This segmentation approach is compared, using hand-labelled data, to a number of standard segmentation/thresholding methods commonly applied in microscopy.
The importance of different features is also assessed using the method of minimum Redundancy, Maximum Relevance (mRMR), and the effect of different SVM kernels is also considered.
The results show that the approach suggested in this paper attains much greater accuracy than standard techniques; in our comparisons with manually labelled data, our proposed technique is able to identify boundary pixels to an accuracy of 93%.
More significantly, out of a set of 56 regions of image data, 43 regions were binarised to a useful level of accuracy.
The results obtained from the image segmentation technique developed here may be used for the study of shape and alignment of ECs, and hence patterns of blood flow, around arterial branches.
American Psychological Association (APA)
Iftikhar, Saadia& Bond, Andrew R.& Wagan, Asim I.& Weinberg, Peter D.& Bharath, Anil A.. 2011. Segmentation of Endothelial Cell Boundaries of Rabbit Aortic Images Using a Machine Learning Approach. International Journal of Biomedical Imaging،Vol. 2011, no. 2011, pp.1-11.
https://search.emarefa.net/detail/BIM-459078
Modern Language Association (MLA)
Iftikhar, Saadia…[et al.]. Segmentation of Endothelial Cell Boundaries of Rabbit Aortic Images Using a Machine Learning Approach. International Journal of Biomedical Imaging No. 2011 (2011), pp.1-11.
https://search.emarefa.net/detail/BIM-459078
American Medical Association (AMA)
Iftikhar, Saadia& Bond, Andrew R.& Wagan, Asim I.& Weinberg, Peter D.& Bharath, Anil A.. Segmentation of Endothelial Cell Boundaries of Rabbit Aortic Images Using a Machine Learning Approach. International Journal of Biomedical Imaging. 2011. Vol. 2011, no. 2011, pp.1-11.
https://search.emarefa.net/detail/BIM-459078
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-459078