Segmentation of malignant gliomas through remote collaboration and statistical fusion

Purpose: Malignant gliomas represent an aggressive class of central nervous system neoplasms. Correlation of interventional outcomes with tumor morphometry data necessitates 3D segmentation of tumors (typically based on magnetic resonance imaging). Expert delineation is the long-held gold standard f...

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Veröffentlicht in:	Medical physics (Lancaster) Jg. 39; H. 10; S. 5981 - 5989
Hauptverfasser:	Xu, Zhoubing, Asman, Andrew J., Singh, Eesha, Chambless, Lola, Thompson, Reid, Landman, Bennett A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States American Association of Physicists in Medicine 01.10.2012
Schlagworte:	Anatomy biomedical MRI Blood-Brain Barrier - metabolism Brain Cancer Central nervous system collaborative labeling Computer software Cooperative Behavior Data Interpretation, Statistical Digital computing or data processing equipment or methods, specially adapted for specific applications Edema - complications Edge enhancement gadolinium Glioma - complications Glioma - diagnosis Glioma - metabolism Graduates Humans Image data processing or generation, in general image enhancement Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image image fusion Image Processing, Computer-Assisted - methods image sampling image segmentation Imaging, Three-Dimensional Information integration Internet Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging Magnetic Resonance Imaging Magnetic Resonance Physics Malignant glioma medical image processing Medical image segmentation Medical imaging MRI: anatomic, functional, spectral, diffusion neurophysiology Probability theory, stochastic processes, and statistics Segmentation statistical analysis statistical fusion tumor segmentation tumours tumor segmentation Malignant glioma collaborative labeling statistical fusion
ISSN:	0094-2405, 2473-4209, 0094-2405
Online-Zugang:	Volltext
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