Segmentation of Brain MR Images by Using Fully Convolutional Network and Gaussian Mixture Model with Spatial Constraints
Joint Authors
Zhu, Hongqing
Lai, Jiawei
Ling, Xiaofeng
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-05-13
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Accurate segmentation of brain tissue from magnetic resonance images (MRIs) is a critical task for diagnosis, treatment, and clinical research.
In this paper, a novel algorithm (GMMD-U) that incorporates the modified full convolutional neural network U-net and Gaussian-Dirichlet mixture model (GMMD) with spatial constraints is presented.
The proposed GMMD-U considers the local spatial relationships by assuming that the prior probability obeys the Dirichlet distribution.
Specifically, GMMD is applied for extracting brain tissue that has a distinct intensity region and modified U-net is exploited to correct the wrong-classification areas caused by GMMD or other conventional approaches.
The proposed GMMD-U is designed to take advantage of the statistical model-based segmentation techniques and deep neural network.
We evaluate the performance of GMMD-U on a publicly available brain MRI dataset by comparing it with several existing algorithms, and the results reported reveal that the proposed framework can accurately detect the brain tissue from MRIs.
The proposed learning-based integrated framework could be effective for brain tissue segmentation, which will be helpful for surgeons in brain disease diagnosis.
American Psychological Association (APA)
Lai, Jiawei& Zhu, Hongqing& Ling, Xiaofeng. 2019. Segmentation of Brain MR Images by Using Fully Convolutional Network and Gaussian Mixture Model with Spatial Constraints. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1195693
Modern Language Association (MLA)
Lai, Jiawei…[et al.]. Segmentation of Brain MR Images by Using Fully Convolutional Network and Gaussian Mixture Model with Spatial Constraints. Mathematical Problems in Engineering No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1195693
American Medical Association (AMA)
Lai, Jiawei& Zhu, Hongqing& Ling, Xiaofeng. Segmentation of Brain MR Images by Using Fully Convolutional Network and Gaussian Mixture Model with Spatial Constraints. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1195693
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195693