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.

Quality-driven Deep Active Learning Method for 3D Brain MRI Segmentation

2021 ◽  
Author(s):  
Zhenxi Zhang ◽  
Jie Li ◽  
Chunna Tian ◽  
Zhusi Zhong ◽  
Zhicheng Jiao ◽  
...  
Keyword(s):  
Active Learning ◽  
Brain Mri ◽  
Learning Method ◽  
Mri Segmentation ◽  
Active Learning Method

scholarly journals Leveraging 3d Information In Unsupervised Brain Mri Segmentation

2021 ◽  
Author(s):  
Benjamin Lambert ◽  
Maxime Louis ◽  
Senan Doyle ◽  
Florence Forbes ◽  
Michel Dojat ◽  
...  
Keyword(s):  
Brain Mri ◽  
Mri Segmentation ◽  
3D Information

Left ventricular dysfunction is associated with cerebral grey matter injury: An in-vivo brain MRI segmentation study

2012 ◽  
Vol 321 (1-2) ◽  
pp. 111-113 ◽  
Author(s):  
Pratik Bhattacharya ◽  
Fen Bao ◽  
Megha Shah ◽  
Gautam Ramesh ◽  
Ramesh Madhavan ◽  
...  
Keyword(s):  
Left Ventricular Dysfunction ◽  
Grey Matter ◽  
Ventricular Dysfunction ◽  
Brain Mri ◽  
Left Ventricular ◽  
Mri Segmentation ◽  
Cerebral Grey Matter ◽  
Grey Matter Injury

scholarly journals Automated claustrum segmentation in human brain MRI using deep learning

2021 ◽  
Author(s):  
Hongwei Li ◽  
Aurore Menegaux ◽  
Benita Schmitz‐Koep ◽  
Antonia Neubauer ◽  
Felix J. B. Bäuerlein ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Brain ◽  
Brain Mri

scholarly journals DFENet: A Novel Dimension Fusion Edge Guided Network for Brain MRI Segmentation

2021 ◽  
Vol 2 (6) ◽  
Author(s):  
Hritam Basak ◽  
Rukhshanda Hussain ◽  
Ajay Rana
Keyword(s):  
Brain Mri ◽  
Mri Segmentation
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