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Novel Methods for Microglia Segmentation, Feature Extraction, and Classification

Ding, Yuchun; Pardon, Marie Christine; Agostini, Alessandra; Faas, Henryk; Duan, Jinming; Ward, Wil O.C.; Easton, Felicity; Auer, Dorothee P.; Bai, Li

Authors

Yuchun Ding

Alessandra Agostini

Henryk Faas

Jinming Duan

Wil O.C. Ward

Felicity Easton

DOROTHEE AUER dorothee.auer@nottingham.ac.uk
Professor of Neuroimaging

Li Bai



Abstract

© 2017 IEEE. Segmentation and analysis of histological images provides a valuable tool to gain insight into the biology and function of microglial cells in health and disease. Common image segmentation methods are not suitable for inhomogeneous histology image analysis and accurate classification of microglial activation states has remained a challenge. In this paper, we introduce an automated image analysis framework capable of efficiently segmenting microglial cells from histology images and analyzing their morphology. The framework makes use of variational methods and the fast-split Bregman algorithm for image denoising and segmentation, and of multifractal analysis for feature extraction to classify microglia by their activation states. Experiments show that the proposed framework is accurate and scalable to large datasets and provides a useful tool for the study of microglial biology.

Citation

Ding, Y., Pardon, M. C., Agostini, A., Faas, H., Duan, J., Ward, W. O., …Bai, L. (2016). Novel Methods for Microglia Segmentation, Feature Extraction, and Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(6), 1366-1377. https://doi.org/10.1109/TCBB.2016.2591520

Journal Article Type Article
Acceptance Date Jul 10, 2016
Online Publication Date Jul 14, 2016
Publication Date Jul 14, 2016
Deposit Date Sep 5, 2016
Publicly Available Date Mar 29, 2024
Journal IEEE/ACM Transactions on Computational Biology and Bioinformatics
Print ISSN 1545-5963
Electronic ISSN 1557-9964
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 14
Issue 6
Pages 1366-1377
DOI https://doi.org/10.1109/TCBB.2016.2591520
Keywords microglia analysis, Mumford-Shah, fast split Bregman, fast Fourier transform, multifractal analysis, histology
data analysis
Public URL https://nottingham-repository.worktribe.com/output/781997
Publisher URL http://ieeexplore.ieee.org/document/7513440/?arnumber=7513440
Additional Information © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.

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