Author Description

Characterization of anatomical structure through segmentation has become essential for morphological assessment and localizing quantitative measures. Segmentation through registration and atlas label transfer has proven to be a flexible and fruitful approach as efficient, non-rigid image registration methods have become prevalent. Label transfer segmentation using multiple atlases has helped to bring statistical fusion, shape modeling, and meta-analysis techniques to the forefront of segmentation research. Numerous creative approaches have proposed to use atlas information to apply labels to brain anatomy. However, it is difficult to evaluate the relative advantages and limitations of these methods as they have been applied on very different datasets. This workshop provides a snapshot of the current progress in the field through extended discussions and provides researchers an opportunity to characterize their methods on standardized data in a grand challenge.