Graph-based interactive three-dimensional segmentation of magnetic resonance images of brain tumors / 南方医科大学学报
Journal of Southern Medical University
; (12): 140-143, 2009.
Article
in Zh
| WPRIM
| ID: wpr-339044
Responsible library:
WPRO
ABSTRACT
We propose a graph-based three-dimensional (3D) algorithm to automatically segment brain tumors from magnetic resonance images (MRI). The algorithm uses minimum s/t cut criteria to obtain a global optimal result of objective function formed according to Markov Random Field Model and Maximum a posteriori (MAP-MRF) theory, and by combining the expectation-maximization (EM) algorithm to estimate the parameters of mixed Gaussian model for normal brain and tumor tissues. 3D segmentation results of brain tumors are fast achieved by our algorithm. The validation of the algorithm was tested and showed good accuracy and adaptation under simple interactions with the physicians.
Full text:
1
Index:
WPRIM
Main subject:
Algorithms
/
Image Processing, Computer-Assisted
/
Brain Neoplasms
/
Pattern Recognition, Automated
/
Magnetic Resonance Imaging
/
Image Interpretation, Computer-Assisted
/
Imaging, Three-Dimensional
/
Diagnosis
/
Methods
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Humans
Language:
Zh
Journal:
Journal of Southern Medical University
Year:
2009
Type:
Article