Generalized rough fuzzy c-means algorithm for brain MR image segmentation

Fuzzy sets and rough sets have been widely used in many clustering algorithms for medical image segmentation, and have recently been combined together to better deal with the uncertainty implied in observed image data. Despite of their wide spread applications, traditional hybrid approaches are sens...

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Veröffentlicht in:	Computer methods and programs in biomedicine Jg. 108; H. 2; S. 644 - 655
Hauptverfasser:	Ji, Zexuan, Sun, Quansen, Xia, Yong, Chen, Qiang, Xia, Deshen, Feng, Dagan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ireland Ltd 01.11.2012 Elsevier
Schlagworte:	Algorithms Bias Biological and medical sciences Brain Brain - anatomy & histology Brain magnetic resonance image Clustering Fuzzy c-means algorithm Fuzzy Logic Fuzzy set theory Humans Image segmentation Intensity inhomogeneity Internal Medicine Magnetic Resonance Imaging - methods Mathematical models Medical sciences Other Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Rough set Rough-fuzzy c-means algorithm Technology. Biomaterials. Equipments. Material. Instrumentation Image segmentation Intensity inhomogeneity Fuzzy c-means algorithm Brain magnetic resonance image Rough-fuzzy c-means algorithm Rough set Image processing Nuclear magnetic resonance imaging Biomedical engineering
ISSN:	0169-2607, 1872-7565, 1872-7565
Online-Zugang:	Volltext
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