NDLI: Non-local-based spatially constrained hierarchical fuzzy C-means method for brain magnetic resonance imaging segmentation

Content Provider	IET Digital Library
Author	Chen, Yunjie Li, Jian Zhang, Hui Zheng, Yuhui Jeon, Byeungwoo Wu, Qingming Jonathan
Abstract	Owing to the existence of noise and intensity inhomogeneity in brain magnetic resonance (MR) images, the existing segmentation algorithms are hard to find satisfied results. In this study, the authors propose an improved fuzzy C-mean clustering method (FCM) to obtain more accurate results. First, the authors modify the traditional regularisation smoothing term by using the non-local information to reduce the effect of the noise. Second, inspired by the mechanism of the Gaussian mixture model, the distance function of FCM is defined by using the form of certain exponential function consisting of not only the distance but also the covariance and the prior probability to improve the robustness. Meanwhile, the bias field is modelled by using orthogonal basis functions to reduce the effect of intensity inhomogeneity. Finally, they use the hierarchical strategy to construct a more flexibility function, which considers the improved distance function itself as a sub-FCM, to make the method more robust and accurate. Compared with the state-of-the-art methods, experiment results based on synthetic and real MR images demonstrate its accuracy and robustness.
Starting Page	865
Ending Page	876
Page Count	12
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 11, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0271
Journal	IET Image Processing
Publisher Date	2016-06-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Brain Magnetic Resonance Imaging Segmentation Combinatorial Mathematics Computer Vision And Image Processing Technique Exponential Function FCM Flexibility Function Fuzzy Set Theory Gaussian Mixture Model Gaussian Processes Graph Theory Hierarchical Strategy Image Denoising Image Segmentation Improved Distance Function Intensity Inhomogeneity Effect Reduction Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy Mixture Model MR Image Noise Effect Reduction Nonlocal-based Spatially Constrained Hierarchical Fuzzy C-means Method Optical, Image And Video Signal Processing Orthogonal Basis Function Patient Diagnostic Method And Instrumentation Pattern Clustering Probability Regularisation Smoothing Term Set Theory Spectroscopy Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Generalised rough intuitionistic fuzzy c-means for magnetic resonance brain image segmentation

Fast and Automatically Adjustable GRBF Kernel Based Fuzzy C-Means for Cluster-wise Coloured Feature Extraction and Segmentation of MR Images

Robust fuzzy c-means clustering algorithm using non-parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation

Segmentation of brain magnetic resonance images using a novel fuzzy clustering based method

Novel fuzzy clustering-based bias field correction technique for brain magnetic resonance images

Brain MRI segmentation by combining different MRI modalities using Dempster–Shafer theory

Multilabel statistical shape prior for image segmentation

MRI Brain Tumor Segmentation with Intuitionist Possibilistic Fuzzy Clustering and Morphological Operations

Fuzzy farthest point first method for MRI brain image clustering

Non-local-based spatially constrained hierarchical fuzzy C-means method for brain magnetic resonance imaging segmentation

Similar Documents

Generalised rough intuitionistic fuzzy c-means for magnetic resonance brain image segmentation

Fast and Automatically Adjustable GRBF Kernel Based Fuzzy C-Means for Cluster-wise Coloured Feature Extraction and Segmentation of MR Images

Robust fuzzy c-means clustering algorithm using non-parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation

Segmentation of brain magnetic resonance images using a novel fuzzy clustering based method

Novel fuzzy clustering-based bias field correction technique for brain magnetic resonance images

Brain MRI segmentation by combining different MRI modalities using Dempster–Shafer theory

Multilabel statistical shape prior for image segmentation

MRI Brain Tumor Segmentation with Intuitionist Possibilistic Fuzzy Clustering and Morphological Operations

Fuzzy farthest point first method for MRI brain image clustering

Non-local-based spatially constrained hierarchical fuzzy C-means method for brain magnetic resonance imaging segmentation