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A novel polar space random field model for the detection of glandular structures

Fu, Hao; Qiu, Guoping; Shu, Jie; Ilyas, Mohammad


Hao Fu

Professor of Visual Information Processing

Jie Shu


In this paper, we propose a novel method to detect glandular structures in microscopic images of human tissue. We first convert the image from Cartesian space to polar space and then introduce a novel random field model to locate the possible boundary of a gland. Next, we develop a visual feature-based support vector regressor to verify if the detected contour corresponds to a true gland. And finally, we combine the outputs of the random field and the regressor to form the GlandVision algorithm for the detection of glandular structures. Our approach can not only detect the existence of the gland, but also can accurately locate it with pixel accuracy. In the experiments, we treat the task of detecting glandular structures as object (gland) detection and segmentation problems respectively. The results indicate that our new technique outperforms state-of-the-art computer vision algorithms in respective fields.


Fu, H., Qiu, G., Shu, J., & Ilyas, M. (2014). A novel polar space random field model for the detection of glandular structures. IEEE Transactions on Medical Imaging, 33(3), 764-776.

Journal Article Type Article
Acceptance Date Dec 17, 2013
Online Publication Date Jan 6, 2014
Publication Date 2014-03
Deposit Date Oct 25, 2017
Journal IEEE Transactions on Medical Imaging
Print ISSN 0278-0062
Electronic ISSN 1558-254X
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 33
Issue 3
Pages 764-776
Keywords Gland; polar space; random field
Public URL
Publisher URL
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