T1- and T2-weighted spatially constrained fuzzy c-means clustering for brain MRI segmentation

2010 ◽  
Author(s):  
Ivana Despotović ◽  
Bart Goossens ◽  
Ewout Vansteenkiste ◽  
Wilfried Philips
Keyword(s):  
Brain Mri ◽  
Mri Segmentation ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
T1 And T2

Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation

2021 ◽  
Vol 16 ◽  
Author(s):  
Ghazanfar Latif ◽  
Jaafar Alghazo ◽  
Fadi N. Sibai ◽  
D.N.F. Awang Iskandar ◽  
Adil H. Khan
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Mri ◽  
Tumor Segmentation ◽  
Brain Anatomy ◽  
Mri Segmentation ◽  
Brain Tumor Segmentation ◽  
Brain Images ◽  
Low Contrast ◽  
Fuzzy C Means

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

A new method based on Dempster–Shafer theory and fuzzy c-means for brain MRI segmentation

2015 ◽  
Vol 26 (10) ◽  
pp. 105402 ◽  
Author(s):  
Jie Liu ◽  
Xi Lu ◽  
Yunpeng Li ◽  
Xiaowu Chen ◽  
Yong Deng
Keyword(s):  
Brain Mri ◽  
New Method ◽  
Mri Segmentation ◽  
Fuzzy C Means ◽  
Dempster Shafer Theory ◽  
Shafer Theory

A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image

2018 ◽  
Vol 78 (10) ◽  
pp. 12663-12687 ◽  
Author(s):  
Dhirendra Kumar ◽  
Hanuman Verma ◽  
Aparna Mehra ◽  
R. K. Agrawal
Keyword(s):  
Human Brain ◽  
Brain Mri ◽  
Fuzzy C Means ◽  
Intuitionistic Fuzzy ◽  
Fuzzy C Means Clustering ◽  
Clustering Approach ◽  
Mri Image
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