Cheng-Yi Liu, Juan Eugenio Iglesias, Zhuowen Tu, and Alzheimer’s Disease Neuroimaging Initiative. 2013. “
Deformable templates guided discriminative models for robust 3D brain MRI segmentation.” Neuroinformatics, 11, 4, Pp. 447-468.
Albert Montillo, Jilin Tu, Jamie Shotton, John Winn, Juan Eugenio Iglesias, Dimitris N Metaxas, and Antonio Criminisi. 2013. “
Entanglement and differentiable information gain maximization.” In Decision forests for computer vision and medical image analysis, Pp. 273-293. Springer, London.
Oula Puonti, Juan Eugenio Iglesias, and Koen Van Leemput. 2013. “
Fast, sequence adaptive parcellation of brain MR using parametric models.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg.
Susanne Mueller, Paul Yushkevich, Lei Wang, Koen Van Leemput, Adam Mezher, Juan Eugenio Iglesias, Sandhitsu Das, and Michael Weiner. 2013. “
IC‐P‐088: Collaboration for a systematic comparison of different techniques to measure subfield volumes: Announcement and first results.” Alzheimer's & Dementia, 9, Pp. P51-P51.
Juan Eugenio Iglesias, Mert Rory Sabuncu, Koen Van Leemput, and Alzheimer’s Disease Neuroimaging Initiative. 2013. “
Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry.” Medical image analysis, 17, 7, Pp. 766-778.
Juan Eugenio Iglesias, Mert Rory Sabuncu, and Koen Van Leemput. 2013. “
A probabilistic, non-parametric framework for inter-modality label fusion.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg.
Juan Eugenio Iglesias, Ender Konukoglu, Darko Zikic, Ben Glocker, Koen Van Leemput, and Bruce Fischl. 2013. “
Is synthesizing MRI contrast useful for inter-modality analysis?” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg.
Juan Eugenio Iglesias, Mert Rory Sabuncu, and Koen Van Leemput. 2013. “
A unified framework for cross-modality multi-atlas segmentation of brain MRI.” Medical image analysis, 17, 8, Pp. 1181-1191.