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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

Guoping Qiu

Jie Shu

Mohammad Ilyas


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.

Journal Article Type Article
Publication Date Jan 2, 2014
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
APA6 Citation 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), doi:10.1109/tmi.2013.2296572
Keywords Gland; polar space; random field
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