@inproceedings{Berlin3478,
   Author = {Yang, Z. and LaConte, S. and Weng, X. and Hu, X.},
   Title ={Ranking and averaging independent component analysis by reproducibility ({R}{A}{I}{C}{A}{R})},
   BookTitle = {Proceedings 15th Scientific Meeting, International Society for Magnetic Resonance in Medicine, Berlin},
   Pages = {3478},
   Abstract = {We introduce a method, Ranking and Averaging Independent Component Analysis by Reproducibility (RAICAR), to improve the ICA method used for fMRI data analysis. By repeating ICA with different initial values, RAICAR utilizes the reproducibility between these repetitions to rank ICA components, determine the number of important components and obtain more stable result. The reproducibility provides a new index to compare fMRI components and its ranking makes the interpretation of ICA results easier. RAICAR was evaluated on simulated and experimental fMRI datasets and demonstrated to be effective and reproducible. In addition, a comparison in terms of the estimated number of components revealed that RAICAR performs much better than MELODIC and ICASSO.},
 Keywords = {Berlin3478},
   Year = {2007} }