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Correlation filters for detection of cellular nuclei in histopathology images

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Ahmad, Asif, Asif, Amina, Rajpoot, Nasir, Arif, Muhammad and Minhas, Fayyaz ul Amir Afsar (2018) Correlation filters for detection of cellular nuclei in histopathology images. Journal of Medical Systems, 42 (7). doi:10.1007/s10916-017-0863-8

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Official URL: http://dx.doi.org/10.1007/s10916-017-0863-8

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Abstract

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. Availability: A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Q Science > QH Natural history
R Medicine > RB Pathology
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Histology, Pathological -- Imaging, Cells—Morphology -- Analysis, Machine learning
Journal or Publication Title: Journal of Medical Systems
Publisher: Springer New York LLC
ISSN: 0148-5598
Official Date: January 2018
Dates:
DateEvent
January 2018Published
21 November 2017Available
10 November 2017Accepted
Volume: 42
Number: 7
DOI: 10.1007/s10916-017-0863-8
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): This is a post-peer-review, pre-copyedit version of an article published in Journal of Medical Systems. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10916-017-0863-8
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
FellowshipPakistan Institute of Engineering and Applied Scienceshttp://www.pieas.edu.pk/
IT and Telecom Endowment FundPakistan Institute of Engineering and Applied Scienceshttp://www.pieas.edu.pk/

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