Multiresolutional graph cuts for brain extraction from MR images

2013 ◽  
Author(s):  
Yong-Sheng Chen ◽  
Li-Fen Chen ◽  
Yi-Ting Wang
Keyword(s):  
Graph Cuts ◽  
Mr Images ◽  
Brain Extraction

Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts

NeuroImage ◽  
2008 ◽  
Vol 43 (4) ◽  
pp. 708-720 ◽  
Author(s):  
Fedde van der Lijn ◽  
Tom den Heijer ◽  
Monique M.B. Breteler ◽  
Wiro J. Niessen
Keyword(s):  
Graph Cuts ◽  
Mr Images ◽  
Atlas Registration ◽  
Hippocampus Segmentation ◽  
Voxel Classification

scholarly journals Segmentation of abdomen MR images using kernel graph cuts with shape priors

2013 ◽  
Vol 12 (1) ◽  
pp. 124 ◽  
Author(s):  
Qing Luo ◽  
Wenjian Qin ◽  
Tiexiang Wen ◽  
Jia Gu ◽  
Nikolas Gaio ◽  
...  
Keyword(s):  
Graph Cuts ◽  
Shape Priors ◽  
Mr Images

scholarly journals Consistent 4D brain extraction of serial brain MR images

2013 ◽  
Author(s):  
Yaping Wang ◽  
Gang Li ◽  
Jingxin Nie ◽  
Pew-Thian Yap ◽  
Lei Guo ◽  
...  
Keyword(s):  
Mr Images ◽  
Brain Extraction ◽  
Brain Mr Images ◽  
Serial Brain

scholarly journals Brain Extraction Using Active Contour Neighborhood-Based Graph Cuts Model

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 559 ◽  
Author(s):  
Shaofeng Jiang ◽  
Yu Wang ◽  
Xuxin Zhou ◽  
Zhen Chen ◽  
Suhua Yang
Keyword(s):  
Local Convergence ◽  
Active Contour ◽  
Sagittal Plane ◽  
Brain Mri ◽  
Graph Cuts ◽  
Dice Similarity Coefficient ◽  
Data Sets ◽  
Similarity Coefficients ◽  
Data Set ◽  
Brain Extraction

The extraction of brain tissue from brain MRI images is an important pre-procedure for the neuroimaging analyses. The brain is bilaterally symmetric both in coronal plane and transverse plane, but is usually asymmetric in sagittal plane. To address the over-smoothness, boundary leakage, local convergence and asymmetry problems in many popular methods, we developed a brain extraction method using an active contour neighborhood-based graph cuts model. The method defined a new asymmetric assignment of edge weights in graph cuts for brain MRI images. The new graph cuts model was performed iteratively in the neighborhood of brain boundary named the active contour neighborhood (ACN), and was effective to eliminate boundary leakage and avoid local convergence. The method was compared with other popular methods on the Internet Brain Segmentation Repository (IBSR) and OASIS data sets. In testing cross IBSR data set (18 scans with 1.5 mm thickness), IBSR data set (20 scans with 3.1 mm thickness) and OASIS data set (77 scans with 1 mm thickness), the mean Dice similarity coefficients obtained by the proposed method were 0.957 ± 0.013, 0.960 ± 0.009 and 0.936 ± 0.018 respectively. The result obtained by the proposed method is very similar with manual segmentation and achieved the best mean Dice similarity coefficient on IBSR data. Our experiments indicate that the proposed method can provide competitively accurate results and may obtain brain tissues with sharp brain boundary from brain MRI images.

Measuring atrophy by simultaneous segmentation of serial MR images using 4-D graph-cuts

2010 ◽  
Author(s):  
Robin Wolz ◽  
Rolf A. Heckemann ◽  
Paul Aljabar ◽  
Joseph V. Hajnal ◽  
Alexander Hammers ◽  
...  
Keyword(s):  
Graph Cuts ◽  
Mr Images

Infant Brain Extraction in T1-Weighted MR Images Using BET and Refinement Using LCDG and MGRF Models

2016 ◽  
Vol 20 (3) ◽  
pp. 925-935 ◽  
Author(s):  
Amir Alansary ◽  
Marwa Ismail ◽  
Ahmed Soliman ◽  
Fahmi Khalifa ◽  
Matthew Nitzken ◽  
...  
Keyword(s):  
Mr Images ◽  
Brain Extraction ◽  
Infant Brain
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