Manual MRI brain tumor segmentation is a difficult and time consuming task which makes computer support highly desirable. This paper presents a hybrid brain tumor segmentation strategy characterized by the allied use of Graph Cut segmentation method and Competitive Expectation Maximization (CEM) algorithm. Experimental results were obtained by processing inhouse collected data and public data from benchmark data sets. To see if the proposed method can be considered an alternative to contemporary methods, the results obtained were compared with those obtained by authors who undertook the Multi-modal Brain Tumor Segmentation challenge. The results obtained prove that the method is competitive with recently proposed approaches.

Fully automatic brain tumor segmentation by using competitive EM and graph cut

BALBI, SERGIO;BINAGHI, ELISABETTA
2015-01-01

Abstract

Manual MRI brain tumor segmentation is a difficult and time consuming task which makes computer support highly desirable. This paper presents a hybrid brain tumor segmentation strategy characterized by the allied use of Graph Cut segmentation method and Competitive Expectation Maximization (CEM) algorithm. Experimental results were obtained by processing inhouse collected data and public data from benchmark data sets. To see if the proposed method can be considered an alternative to contemporary methods, the results obtained were compared with those obtained by authors who undertook the Multi-modal Brain Tumor Segmentation challenge. The results obtained prove that the method is competitive with recently proposed approaches.
2015
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783319232300
18th International Conference on Image Analysis and Processing, ICIAP 2015
Genoa, italy
September 2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2026923
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