Simultaneous Truth and Performance Level Estimation Through Fusion of Probabilistic Segmentations

Recent research has demonstrated that improved image segmentation can be achieved by multiple template fusion utilizing both label and intensity information. However, intensity weighted fusion approaches use local intensity similarity as a surrogate measure of local template quality for predicting t...

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Veröffentlicht in:	IEEE transactions on medical imaging 2013-10, Vol.32 (10), p.1840-1852
Hauptverfasser:	Akhondi-Asl, Alireza, Warfield, Simon K.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Brain - anatomy & histology Databases, Factual Equations Estimation Humans Image Processing, Computer-Assisted - methods Image segmentation Label fusion Magnetic Resonance Imaging Mathematical model performance evaluation Probabilistic logic probabilistic segmentation reference standard simultaneous truth and performance level estimation (STAPLE)
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