Hao Fu
A novel polar space random field model for the detection of glandular structures
Fu, Hao; Qiu, Guoping; Shu, Jie; Ilyas, Mohammad
Authors
Professor GUOPING QIU GUOPING.QIU@NOTTINGHAM.AC.UK
VICE PROVOST FOR EDUCATION AND STUDENTEXPERIENCE
Jie Shu
Professor MOHAMMAD ILYAS mohammad.ilyas@nottingham.ac.uk
PROFESSOR OF PATHOLOGY
Abstract
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.
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), 764-776. https://doi.org/10.1109/TMI.2013.2296572
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 |
DOI | https://doi.org/10.1109/TMI.2013.2296572 |
Keywords | Gland; polar space; random field |
Public URL | https://nottingham-repository.worktribe.com/output/722377 |
Publisher URL | http://ieeexplore.ieee.org/document/6697841/ |
Additional Information | ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Contract Date | Oct 25, 2017 |
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